Directions: please follow explicitly *** primarily this assignment is filling in the tables- have attached all articles to use **** Use the attached “Literature Evaluation Table to complete this a
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please follow explicitly
*** primarily this assignment is filling in the tables- have attached all articles to use ****
“Literature Evaluation Table to complete this assignment
(not a word document)
- Refer to the “Levels of Evidence in Research” resource,
- While APA style is not required for the body of this assignment, solid academic writing is expected,
Using the “Levels of Evidence in Research” document (
attached) to rank the articles
Present your PICOT-D question
( this is already done already )
- Table 1: fill in five primary quantitative research articles ( I have attached 5 articles to use)
- Table 2: fill in 5 primary or secondary quantitative research studies ( I have attached 5 articles )
- Table 3: Present the nursing and change theory use- (nursing – Virginia Henderson) (change theory- Kotter change model) pls find articles, be sure to cite approx 250 word (each)
- Table 4: fill in explanation -Use DEVLIN et al., 2018 (its attached)
Directions: please follow explicitly *** primarily this assignment is filling in the tables- have attached all articles to use **** Use the attached “Literature Evaluation Table to complete this a
Levels of Evidence in Research Evidence Level Types of Evidence Primary Research Secondary Research LEVEL 1 Randomized-Controlled Trial: Subjects randomly assigned to intervention or control groups. Intervention group receives treatment/intervention. Comparison group receives no treatment/intervention. Clinician conducting study is unaware which group participants are assigned to which typically leads to unbiased results. X Systematic Review: Comprehensive review of existing literature which involves analyzing all articles related to the research question and summarizing findings. Researchers then make recommendations for clinical practice based on evidence from articles reviewed. X Meta-Analysis: Synthesis of findings from all single, independent studies to calculate an effect. X LEVEL 2 Cohort Studies: Studies observe large groups of people that record exposure to risk factors to find possible causes of disease. Studies gather data either moving forward (prospective) or review past data already recorded (retrospective). X LEVEL 3 Case Report Studies: Studies used to determine if there is an association between exposure and specific health outcome. Frequently used when studying rare health outcomes or diseases. X LEVEL 4 Case Report: Provides detailed report of diagnosis, treatment, response to treatment, and follow-up care of an individual patient. Case Series: Group of case reports involving patients who were given the same treatment. LEVEL 5 Animal or Laboratory Studies Primary Research: Involves active participation/observation by researchers themselves. Secondary Research: Involves summary or synthesis of data/literature that has been organized by others. *Adapted from Johns Hopkins Nursing Evidence-Based Practice: Models and Guidelines and University of Michigan Library © 2022. Grand Canyon University. All Rights Reserved.
Directions: please follow explicitly *** primarily this assignment is filling in the tables- have attached all articles to use **** Use the attached “Literature Evaluation Table to complete this a
Literature Evaluation Table – DPI Intervention Learner Name: Instructions: Use this table to evaluate and record the literature gathered for your DPI Project. Refer to the assignment instructions for guidance on completing the various sections. Empirical research articles must be published within 5 years of your anticipated graduation date. Add or delete rows as needed. PICOT-D Question: In adult patients in the high observation unit (HOU) at a long-term acute care hospital will implementing the Society of Critical Care Medicine (SCCM) ICU Liberation Bundle (ABCDEF), compared to current practice impact ICU readmissions over an eight-week period? Table 1: Primary Quantitative Research – Intervention (5 Articles) complete table with listed articles APA Reference (Include the GCU permalink or working link used to access the article.) Research Questions/ Hypothesis, and Purpose/Aim of Study Type of Primary Research Design Research Methodology Setting/Sample (Type, country, number of participants in study) Methods (instruments used; state if instruments can be used in the DPI project) How was the data collected? Interpretation of Data (State p-value: acceptable range is p= 0.000 – p= 0.05) Outcomes/Key Findings (Succinctly states all study results applicable to the DPI Project.) Limitations of Study and Biases Recommendations for Future Research Explanation of How the Article Supports Your Proposed Intervention Balas Barnes-Daly Devlin Hsien Pun Table 2: Additional Primary and Secondary Quantitative Research (10 Articles) complete table with listed articles APA Reference (Include the GCU permalink or working link used to access the article.) Research Questions/ Hypothesis, and Purpose/Aim of Study Type of Primary or Secondary Research Design Research Methodology Setting/Sample (Type, country, number of participants in study) Methods (instruments used; state if instruments can be used in the DPI project) How was the data collected? Interpretation of Data (State p-value: acceptable range is p= 0.000 – p= 0.05) Outcomes/Key Findings (Succinctly states all study results applicable to the DPI Project.) Limitations of Study and Biases Recommendations for Future Research Explanation of How the Article Supports Your Proposed DPI Project Collinsworth Demellow Loberg Oflufison Van dee Boogard Table 3: Theoretical Framework Aligning to DPI Project Nursing Theory Selected APA Reference – Seminal Research References (Include the GCU permalink or working link used to access each article.) Explanation for the Nursing Theory Guides the Practice Aspect of the DPI Project Virginia Henderson’s Nursing Needs Theory Ahtisham, Y., & Jacoline, S. (2015). Integrating Nursing Theory and Process into Practice; Virginia’s Henderson Need Theory. International Journal of Caring Sciences, 8(2), 443–450. https://lopes.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=102972280&site=eds-live&scope=site&custid=s8333196&groupid=main&profile=eds1 Fill in 250 words Change Theory Selected APA Reference – Seminal Research References (Include the GCU permalink or working link used to access each article.) Explanation for How the Change Theory Outlines the Strategies for Implementing the Proposed Intervention John Kotter’s Change Model Kang, S. P., Chen, Y., Svihla, V., Gallup, A., Ferris, K., & Datye, A. K. (2022). Guiding change in higher education: an emergent, iterative application of Kotter’s change model. Studies in Higher Education, 47(2), 270–289. https://doi-org.lopes.idm.oclc.org/10.1080/03075079.2020.1741540 https://lopes.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=155185571&site=eds-live&scope=site&custid=s8333196&groupid=main&profile=eds1 Fill in 250 words Table 4: Clinical Practice Guidelines (If applicable to your project/practice) APA Reference – Clinical Guideline (Include the GCU permalink or working link used to access the article.) APA Reference – Original Research (All) (Include the GCU permalink or working link used to access the article.) Explanation for How Clinical Practice Guidelines Align to DPI Project Pun, B. T., Balas, M. C., Barnes-Daly, M. A., Thompson, J. L., Aldrich, J. M., Barr, J., Byrum, D., Carson, S. S., Devlin, J. W., Engel, H. J., Esbrook, C. L., Hargett, K. D., Harmon, L., Hielsberg, C., Jackson, J. C., Kelly, T. L., Kumar, V., Millner, L., Morse, A., … Ely, E. W. (2018). Caring for Critically Ill Patients with the ABCDEF Bundle: Results of the ICU Liberation Collaborative in Over 15,000 Adults. Critical Care Medicine. https://doi-org.lopes.idm.oclc.org/10.1097/CCM.0000000000003482 https://lopes.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edsovi&AN=edsovi.10.1097.CCM.0000000000003482&site=eds-live&scope=site&custid=s8333196&groupid=main&profile=eds1 Devlin, John W. PharmD, FCCM (Chair)1,2; Skrobik, Yoanna MD, FRCP(c), MSc, FCCM (Vice-Chair)3,4; Gélinas, Céline RN, PhD5; Needham, Dale M. MD, PhD6; Slooter, Arjen J. C. MD, PhD7; Pandharipande, Pratik P. MD, MSCI, FCCM8; Watson, Paula L. MD9; Weinhouse, Gerald L. MD10; Nunnally, Mark E. MD, FCCM11,12,13,14; Rochwerg, Bram MD, MSc15,16; Balas, Michele C. RN, PhD, FCCM, FAAN17,18; van den Boogaard, Mark RN, PhD19; Bosma, Karen J. MD20,21; Brummel, Nathaniel E. MD, MSCI22,23; Chanques, Gerald MD, PhD24,25; Denehy, Linda PT, PhD26; Drouot, Xavier MD, PhD27,28; Fraser, Gilles L. PharmD, MCCM29; Harris, Jocelyn E. OT, PhD30; Joffe, Aaron M. DO, FCCM31; Kho, Michelle E. PT, PhD30; Kress, John P. MD32; Lanphere, Julie A. DO33; McKinley, Sharon RN, PhD34; Neufeld, Karin J. MD, MPH35; Pisani, Margaret A. MD, MPH36; Payen, Jean-Francois MD, PhD37; Pun, Brenda T. RN, DNP23; Puntillo, Kathleen A. RN, PhD, FCCM38; Riker, Richard R. MD, FCCM29; Robinson, Bryce R. H. MD, MS, FACS, FCCM39; Shehabi, Yahya MD, PhD, FCICM40; Szumita, Paul M. PharmD, FCCM41; Winkelman, Chris RN, PhD, FCCM42; Centofanti, John E. MD, MSc43; Price, Carrie MLS44; Nikayin, Sina MD45; Misak, Cheryl J. PhD46; Flood, Pamela D. MD47; Kiedrowski, Ken MA48; Alhazzani, Waleed MD, MSc (Methodology Chair)16,49 Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU, Critical Care Medicine: September 2018 – Volume 46 – Issue 9 – p e825-e873 doi: 10.1097/CCM.0000000000003299 https://journals.lww.com/ccmjournal/Fulltext/2018/09000/Clinical_Practice_Guidelines_for_the_Prevention.29.aspx Fill in read Devlin’s article to fill in © 2022. Grand Canyon University. All Rights Reserved.
Directions: please follow explicitly *** primarily this assignment is filling in the tables- have attached all articles to use **** Use the attached “Literature Evaluation Table to complete this a
Downloaded from<004B005700570053001D00120012004D00520058005500510044004F00560011004F005A005A001100460052005000120046 00460050004D00520058005500510044004F> by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on02/20/2022 Downloadedfrom<004B005700570053001D00120012004D00520058005500510044004F00560011004F005A005A001100460052005000120046 00460050004D00520058005500510044004F> by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on02/20/2022Critical Care Medicine www.ccmjournal.org 171 Objectives: To track compliance by an interprofessional team with the Awakening and Breathing Coordination, Choice of drugs, Delirium monitoring and management, Early mobility, and Family engagement (ABCDEF) bundle in implementing the Pain, Agita- tion, and Delirium guidelines. The aim was to study the association between ABCDEF bundle compliance and outcomes including hospital survival and delirium-free and coma-free days in commu- nity hospitals. Design: A prospective cohort quality improvement initiative involv- ing ICU patients. Setting: Seven community hospitals within California’s Sutter Health System. Patients: Ventilated and nonventilated general medical and surgi- cal ICU patients enrolled between January 1, 2014, and December 31, 2014. Measurements and Main Results: Total and partial bundle compli- ance were measured daily. Random effects regression was used to determine the association between ABCDEF bundle compliance accounting for total compliance (all or none) or for partial compliance (“dose” or number of bundle elements used) and outcomes of hos- pital survival and delirium-free and coma-free days, after adjusting for age, severity of illness, and presence of mechanical ventilation. Of 6,064 patients, a total of 586 (9.7%) died before hospital dis- charge. For every 10% increase in total bundle compliance, patients had a 7% higher odds of hospital survival (odds ratio, 1.07; 95% CI, 1.04–1.11; p < 0.001). Likewise, for every 10% increase in par- tial bundle compliance, patients had a 15% higher hospital survival (odds ratio, 1.15; 95% CI, 1.09–1.22; p < 0.001). These results were even more striking (12% and 23% higher odds of survival per 10% increase in bundle compliance, respectively, p < 0.001) in a sensitivity analysis removing ICU patients identified as receiv- ing palliative care. Patients experienced more days alive and free of delirium and coma with both total bundle compliance (incident rate ratio, 1.02; 95% CI, 1.01–1.04; p = 0.004) and partial bundle com- pliance (incident rate ratio, 1.15; 95% CI, 1.09–1.22; p < 0.001). Conclusions: The evidence-based ABCDEF bundle was success- fully implemented in seven community hospital ICUs using an inter- professional team model to operationalize the Pain, Agitation, and Delirium guidelines. Higher bundle compliance was independently associated with improved survival and more days free of delirium and coma after adjusting for age, severity of illness, and presence of mechanical ventilation. (Crit Care Med 2017; 45:171–178) Key Words: ABCDEF bundle; delirium; ICU liberation; interprofessional; mobilization; sedation K nowledge derived through epidemiologic investigations has contributed to a growing understanding of the far- reaching effects of critical illness (1, 2), emphasizing the need to help mitigate patient suffering and improve quality of care and patient safety both during and after care in the ICU. Society of Critical Care Medicine’s (SCCM’s) “Clinical Practice Copyright © 2017 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. DOI: 10.1097/CCM.0000000000002149 *See also p. 363.1Office of Patient Experience, Sutter Health Systems, Sacramento, CA.2Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, OH. 3Department of Medicine, Pulmonary and Critical Care and Health Services Research Center, Vanderbilt University School of Medicine, Nashville, TN. 4The Tennessee Valley Veteran’s Affairs Geriatric Research Education Clinical Center (GRECC), Nashville, TN. Supported, in part, by a grant from the Gordon and Betty Moore Foundation. Dr. Barnes-Daly has received honoraria from the Society of Critical Care Medicine and a grant from the Gordon and Betty Moore Foundation for the ICU Liberation project. Her institution received funding from the Gordon a nd Betty Moore Foundation. Mr. Phillips received funding from Sutter Health. Dr. Ely has received honoraria from Abbott Laboratories, Hospira, and Orio n for continuing medical education activities and is funded by both the Na tional Institutes of Health (NIH) and Veteran’s Affairs Geriatric Research Education Clinical Center. He received support for article research from the NIH and received funding from Orion and Abbott. His institution received funding from the NIH and Hospira. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals.lww.com/ccmjournal). For information regarding this article, E-mail: [email protected] Improving Hospital Survival and Reducing Brain Dysfunction at Seven California Community Hospitals: Implementing PAD Guidelines Via the ABCDEF Bundle in 6,064 Patients* Mary Ann Barnes-Daly, MS, RN, CCRN, DC 1; Gary Phillips, MAS 2; E. Wesley Ely, MD, MPH, FCCM 3,4 Copyright © 2016 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Barnes-Daly et al 172 www.ccmjournal.org February 2017 • Volume 45 • Number 2 Guidelines for the Management of Pain, Agitation, and Delirium in Adult Patients in the Intensive Care Unit” (PAD guideline) is an extensive set of evidence-based recommendations address- ing key elements of quality and safety and suffering for patients during critical illness (3). The R ethinking Critical Care initia- tive sponsored by the Institute for Healthcare Improvement and other investigations over the past 20 years have helped hun- dreds of hospitals focus on patient comfort and safety issues in the ICU related to pain, sedation, delirium, and early mobility, evolving into a bundle of care (4–6). Subsequent investigations of various permutations of this bundle have been favorable (4, 7–13), yet more data are needed. To that end, the revised A ssess, prevent, and manage pain; Both spontaneous awakening trials (SATs) and spontaneous breathing trials (SBTs); C hoice of Seda- tion/Analgesia; Delirium monitoring and management; E arly mobility and exercise; and F amily engagement and empower – ment (ABCDEF) bundle was developed as an evidence-based strategy to implement the P AD guidelines. The robust nature of the evidence in support of this bundle’s individual elements (3–5, 7, 11, 14–37) led the SCCM to begin its national ICU Lib- eration Collaborative. At the same time, continuing to generate an understanding of the utility of these elements as a b undle in a community setting is important. The quality improvement (QI) initiative described here was designed to utilize an interprofes- sional team (IPT) model to implement the ABCDEF bundle as configured by Sutter Health in seven community-based ICUs in California (38). The aim was to study the relationship between ABCDEF bundle compliance and outcomes including hospital survival and delirium-free and coma-free days (DFCFDs). MATERIALS AND METHODS Study Design One IPT at each of seven Sutter Health–affiliated ICUs was trained on IPT concepts and the clinical aspects of the ABCDEF bundle. Each ICU-based team consisted of a dedicated regis- tered nurse (RN), an administrative RN, a pharmacist, a physi- cal therapist, a respiratory care practitioner (RCP), and an ICU physician. This project was reviewed by the Sutter Health Insti- tutional Review Board, who considered it a QI initiative that did not require consent. Timeline The study period was calendar year 2014. A 12-week IPT training and multiple clinical education programs were provided to each ICU team in a staggered fashion beginning the fourth quarter of 2013 through the second quarter of 2014. The IPT educa- tion program, IPT model, and collaborative functionality of the IPT have previously been well-described (38). Additional clini- cal education was provided to the IPT members through atten- dance at conferences and lectures given by nationally recognized subject matter experts early in the study period. Study Sites The ABCDEF bundle was implemented by the IPT in ICUs ranging from six to 16 beds at seven Sutter Health community hospitals. All units were open, mixed general medical and sur – gical ICUs, and only the three largest hospitals were staffed with intensivists. All hospitals had care augmentation from the remote electronic ICU (eICU) RN and physician staff. Study Procedures The ABCDEF bundle elements were implemented for every patient every day. The elements are described in detail at www. iculiberation.org (39) and by Frimpong et al (40). Note that as part of the 2015–2017 ICU Liberation Collaborative, the bun- dle letters were adjusted to reflect explicitly the inclusion of assessment, prevention, and management of pain as Element A. Accordingly, we advise the reader to see www.iculiberation. org and www.icudelirium.org (39, 41) for the most current description of the ABCDEF bundle. At the time of this 2014 QI study, we operated with the following rubric: Element A: SAT involved completely turning off all sedative infusions as well as analgesic infusions if the patient was not having active pain. Element B: SBT was considered compliant for patients receiv- ing mechanical ventilation (MV) if they were placed on CPAP/ PSV 5/5 or blow-by for a minimum of 30 minutes after having passed a safety screen. Element C1 required the coordination of Elements A and B by actual communication between the RN and RCP performing Elements A and B. This was verbalized in rounds as having happened or not. Element C2 consisted of a statement by the ICU pharmacist that the PAD guidelines for sedation were being followed (i.e., light sedation target, avoid- ance of benzodiazepines, and an analgosedation [pain-first] approach). Element D was met if the Confusion Assessment Method for the ICU (CAM-ICU) had been used to assess the patient on both the current shift and the prior shift. Element E was met if the patient had been mobilized to maximum potential after passing a mobility safety screen. Element F was met if the patient/family had participated in rounds or a fam- ily conference had been held. All of these elements had to be accomplished during the previous 24 hours (rounds yesterday to rounds today) to be considered total compliance for that time period. Patient characteristics are shown in Table 1. The ABCDEF bundle was addressed each morning during ICU rounds using the IPT collaborative model. Both MV and nonventilated patients were eligible for the bundle in an opt-out fashion. All elements of the bundle were contained in a standardized order set (Supplemental Fig. 1, Supplemental Digital Content 1, http:// links.lww.com/CCM/C232). Patients were excluded in certain instances such as active ethanol/drug withdrawal, open abdo- men, significant hemodynamic or respiratory instability, new coronary ischemia, therapeutic neuromuscular blockade, or intubation within the previous 6 hours without stabilization. Bundle-specific safety screens were used to exclude patients who were not clinically stable to have the SAT, the SBT, and the exercise/ early-mobility protocol (E) (supplemental data, Supplemental Digital Content 2, http://links.lww.com/CCM/C233). Each patient was evaluated for level of arousal/sedation and for the presence of delirium using the Richmond Agitation and Sedation Scale (RASS) and the CAM-ICU (22, 23, 37). Sedation Copyright 2016 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Critical Care Medicine www.ccmjournal.org 173 was titrated or removed completely to meet a prescribed RASS target. This target allowed patients to be awake and respon- sive, permitting performance of the delirium assessment and completion of the other bundle elements.During discussion of the implementation of the ABCDEF bundle, the full impact of the bundle was thought to be most evident in patients explicitly seeking recovery and survival. In contrast, patients whose focus of care had shifted to palliation of suffering were expected to be affected less by implementa- tion of the ABCDEF bundle. Therefore, a subgroup analysis of patients with and without a palliative care consult was planned a priori to measure the differential importance of bundle com- pliance in those two groups of patients related to survival and DFCFDs. Data Collection Data were collected each day by the IPT RN in each ICU dur – ing daily rounds and entered into an electronic data collection tool (MIDAS; Kitware, Clifton Park, NY). To reduce the data burden for the individual units, data collection responsibilities were transitioned to the eICU staff, who participated in rounds remotely as active members of the ICU care team and entered the data in real time. Monthly dashboard reports were gener – ated to track total and partial bundle compliance and patient outcome data. Statistical Methods Analyses addressed the relationship between bundle com- pliance (independent variable) versus hospital survival and DFCFDs (two dependent/outcome variables). Independent Variables. Bundle compliance was mea- sured in two ways: 1) total compliance was defined as the proportion of days during a patient’s ICU stay that he or she received all elements of the ABCDEF bundle for which the patient was eligible on a given day and 2) partial compliance was an acknowledgment that some effect on outcomes may result from clinicians’ using some elements of the bundle even though not all bundle elements could be completed. Thus, partial compliance was used to determine the dose of compliance when something less than total compliance was provided to a given patient on a given day. This was calcu- lated in two steps. First, a proportion was generated by tak- ing the number of the individual elements in a particular day that a patient received and dividing that by the number of elements that he or she was eligible to receive. Then the partial compliance was defined as the mean of all of that patient’s proportions during his or her ICU stay (i.e., for all ICU days). Dependent (Outcome) Variables. The two main out- comes variables are: 1) hospital survival was tracked pro- spectively and calculated as the percent of patients still alive at hospital discharge; 2) DFCFDs were also tracked prospec- tively using the CAM-ICU (37) and RASS (22, 23) and cal- culated as the number of days a patient was alive and free of both delirium (i.e., CAM-ICU negative) and coma (i.e., any RASS other than –4 or –5) of that person’s total ICU dura- tion. CAM-ICU and RASS monitoring were only conducted while patients were in the ICU, thus only ICU days were used to determine the presence or absence of delirium and coma. Statistical Modeling. The two outcomes were regressed on each of the two independent variables (total and partial com- pliance). Because patients were seen in seven ICUs (affiliates) in the Sutter Health System, the analysis included the specific ICU as a random term in the regression analysis. Random effects logistic regression was used when analyzing hospital survival, whereas random effects negative binomial regression was used T Ab LE 1. Patient Demographics and baseline Clinical Characteristics Characteristic Statistic No. of patients in study, n6,064 Age in years, mean ( sd) 63.1 (17.4) Sex, n (%) Male 3,236 (53.1) Female 2,828 (46.6) Race, n (%) White 4,468 (73.7) Black 638 (10.5) Asian 319 (5.3) Native American 56 (0.9) Other/unknown 583 (9.6) Acute Physiology and Chronic Health Evaluation III, mean ( sd) 92.0 (26.0) Percent with any mechanical ventilation, n (%) 1,438 (23.7) Admit status, n (%) Elective 627 (10.3) Emergency 3,957 (65.3) Urgent/trauma 1,480 (24.4) Palliative care, n (%) No 5,471 (90.2) Ye s 593 (9.8) Affiliate, n (%) 1 495 (8.2) 2 505 (8.3) 3 213 (3.5) 4 1,061 (17.5) 5 1,575 (26.0) 6 1,269 (20.9) 7 946 (15.6) Acute Physiology and Chronic Health Evaluation III range is 0–299. Copyright © 2016 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Feature Articles Barnes-Daly et al 174 www.ccmjournal.org February 2017 • Volume 45 • Number 2 when analyzing the number of DFCFDs. Both of these regres- sion methods were run separately when total compliance was the independent variable and when partial compliance was the independent variable. Negative binomial regression was used as opposed to Poisson regression because the variance was over dispersed. ICU length of stay (LOS) was used as the exposure variable in this regression to control for the variable length of time the patient was in the ICU. Random effects logistic regression analysis produced hospi- tal survival odds ratios (ORs) for a 0.1 unit increase for both independent (i.e., bundle compliance) variables. Thus the ORs estimate the increase in hospital survival for every 0.1 increase in the bundle compliance proportion. Similarly, random effect negative binomial regression produced incident rate ratios (IRRs) for a 0.1 unit increase for both bundle compli- ance variables. Here the IRRs estimate the increase in the rate of DFCFDs for every 0.1 increase in the proportion of bundle compliance. The goal of this investigation was to identify the true relation- ship between total or partial compliance and hospital survival; therefore, a risk factor (bundle compliance as the independent variable) modeling approach was used to determine which covariates to add to the random effect regression model. The OR and the IRR describe the relationship between the depen- dent variable (i.e., hospital survival and DFCFDs, respectively) and total or partial bundle compliance in the regression. When determining other covariates to add to the regression model, only covariates that change the total or partial compliance OR or IRR (i.e., confounders) were included. These confounders of the relationship were determined as those that changed the relationship by more than 10% in either direction. Covariates that had a statistically significant interaction with total or par – tial compliance (p < 0.05) were also included in the model as they are effect modifiers. If a confounder or an effect modifier was found, the analysis was adjusted for this covariate. It was determined a priori that age and Acute Physiology and Chronic Health Evaluation (APACHE) III would be included in all risk-adjusted models regardless of whether or not they were confounders. APACHE III was missing in 2.9% of the observations and was thus imputed using multiple imputation (M = 20) using truncated linear regression where the lower and upper limit of the truncation was set at the observed minimum and maximum values of 7 and 194, respec- tively. The predictor variables in the imputation included patient age, sex, race, admission status (elective, emergency, trauma, or urgent), whether or not the patient was receiving sedation, hospital LOS, and affiliate location. All analyses were run using Stata 14.1 (StataCorp, College Station, TX). RESULTS Demographics and baseline Characteristics In total, 6,064 unique patients were included in the study. Patient demographic information and baseline characteris- tics are summarized in Table 1. Approximately one quarter of the patients were on MV at some point during their ICU stay making them eligible for all ABCDEF bundle elements on those days. Patients who were not receiving MV on a par – ticular day and those who never received MV would not be eligible for the A, B, or C 1 elements of the bundle on those particular days, which was accounted for in assessing bundle compliance. Patient Outcomes and Compliance Statistics Table 2 shows that one in 10 patients died before they left the hospital (n = 586 [9.7%]), after a median ICU and hospital LOS of 3 and 5 days, respectively. Table 2 also demonstrates a high rate for both total (all or none; 89%, 95% CI) and partial ABCDEF bundle compliance (95%, 95% CI). Ab CDEF bundle Compliance Versus Hospital Survival Figure 1, A and B encompass the data demonstrating the effect of the ABCDEF bundle on survival analyzed by all- or-none compliance in Figure 1A and by partial compli- ance (dose response) in Figure 1B . Two models were used for each analysis to consider the relative difference in the bundle effect on the overall patient group (model 1) as well as on the patients who were or were not transitioned into palliative care (model 2). These results are also presented in Supplemental Table 1 (Supplemental Digital Content 3, http://links.lww.com/CCM/C234). Model 1 shows that with each 10% incremental increase in total bundle compliance, the odds of hospital survival increase to 7% (OR, 1.07; 95% CI, 1.04–1.11; p < 0.001). Model 2 shows that, as suspected, total bundle compliance in patients receiving palliative care did not demonstrate improved survival benefit; however, patients not receiving palliative care demonstrated a 12% increase in survival with each 10% incremental increase in total bundle compliance for nonpalliative care patients (OR, 1.12; 95% CI, 1.07–1.17; p < 0.001). Figure 1B shows that with each 10% increase in partial bundle compliance, the odds of hospital survival increase to 15% (OR, 1.15; 95% CI, 1.09–1.22; p < 0.001). Again, model 2 demonstrates that for patients not receiving palliative care, the odds of hospital survival increase to 23% (OR, 1.23; 95% CI, 1.14–1.32; p < 0.001). These results are also presented in Supplemental Table 2 (Supplemental Digital Content 4, http:// links.lww.com/CCM/C235). Ab CDEF bundle Compliance Versus DFCFDs Figure 2, A and B encompass the data showing the associa- tion of bundle compliance with DFCFDs, that is, a day during which the patient was alive and both not delirious (CAM-ICU negative) and not in a coma (RASS, –3 or higher). These results are also presented in Supplemental Table 3 (Supplemen- tal Digital Content 5, http://links.lww.com/CCM/C236). In 483 of the patients, DFCFDs could not be calculated because these patients’ records did not include either RASS scores or delirium assessments (CAM-ICU). The presence or absence of coma and/or delirium was unknown; thus, the number of observations used in the analysis is 5,581. These data show that Copyright 2016 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Critical Care Medicine www.ccmjournal.org 175 for every 10% increase in total bundle compliance, patients had a 2% increase of DFCFDs (IRR, 1.02; 95% CI, 1.01–1.04; p = 0.004), and for every 10% increase in partial bundle com- pliance, there was a 15% increase in DFCFDs (IRR, 1.15; 95% CI, 1.09–1.22; p < 0.001). The evidence-based ABCDEF bundle was implemented with high levels of compliance in all seven hospitals (Supplemental Table 4, Supplemental Digital Content 6, http://links.lww.com/ CCM/C237), which showed that the findings from Figures 1A and 2A held up even when the bundle was not implemented completely. Distribution of patients by compliance range for both total and partial compliance is shown in Supplemental Table 5, which shows that the bulk of the data for compliance by decile fall in the higher ranges of compliance. DISCUSSION This large-scale QI project in more than 6,000 patients at seven community hospitals demonstrated the value of imple- menting the PAD guidelines using a bundle of evidence-based steps through interprofessional teamwork. Incorporating the evidence of the PAD guidelines that appears in the ABCDEF bundle demonstrated that compliance with the bundle was independently associated with better patient survival and more days alive and free of delirium and coma even after adjusting for age, severity of illness, and MV (Figs. 1A and 2A). Impor – tantly, these findings held up even when the bundle was not implemented completely. That is, the ABCDEF bundle dose, as measured by partial compliance, data shown in Figures 1B and 2B were strikingly positive for both the survival and the brain dysfunction outcomes of delirium and coma. These par – tial bundle compliance figures showed that both ICU survival and DFCFDs displayed steeper increases than total compliance figures. Partial compliance was likely a more sensitive indicator of these relationships as it demonstrated the dose-effect of the bundle, whereas the total compliance had only two variables, all or none. This study adds the largest cohort to date on this topic and is complementary to and consistent with findings from pre- vious studies, which have shown that different approaches to this evidence-based bundle have been associated with favor – able clinical outcomes (7–13, 17). Balas et al (8) conducted a cohort study using the earlier ABCDE bundle and demon- strated improvements in ventilator-free days, delirium rates, adoption of early mobility, and trends toward improved 28-day survival. In that study, bundle compliance was an inde- pendent predictor of reducing delirium by half and doubling mobility. A Centers for Disease Control and Prevention–led QI initiative that implemented the bundle’s ABC portion in more than 5,000 ventilated patients successfully reduced noso- comial, infectious-related complications (11). The 51-hospital Keystone initiative showed that ICUs that implemented SATs and delirium screening were 3.5 times more likely to exercise ventilated patients, concluding that their data were “another layer of evidence that for the ABCDEs, the whole is greater than the sum of the parts.” (12) Some hospitals criticize the bundle specifically because it does have so many “parts,” claiming that this makes effecting lasting change too difficult. Trogrlić et al (13), in a study of 21 previous publications examining the assessment, prevention, T Ab LE 2. Patient Outcomes and Compliance Statistics Characteristic n Hospital survival, n (%) No 586 (9.7) Ye s 5,478 (90.3) ICU LOS in days, median (IQR) 3.0 (3.0–5.4) Hospital LOS in days, median (IQR) 5.0 (3.0–8.8) Delirium- and/or coma-free days, mean (95% CI) a 1.61 (1.55–1.67) Proportion of days mechanically ventilated, mean (95% CI) 0.180 (0.171–0.189) Proportion total compliance, mean (95% CI) b 0.891 (0.884–0.897) Proportion partial compliance, mean (95% CI) c 0.952 (0.949–0.957) IQR = interquartile range, LOS = length of stay.a Delirium- and coma-free days were also tracked prospectively using the Confusion Assessment Method for the ICU (CAM-ICU) (37) and Richmond Agitation Sedation Scale (RASS) (22, 23) and calculated as the number of days a patient was alive and free of both delirium (i.e., CAM-ICU negative) and coma (i.e., RASS other than –4 or –5) of that person’s total ICU duration. CAM-ICU and RASS monitoring were only conducted while patients were in the ICU, thus only ICU days were used to determine the presence or absence of delirium and co ma. b Total bundle compliance was defined as the proportion of days during a patient’s ICU stay that he or she received all elements of the Awakening and Breathing Coordination, Choice of drugs, Delirium monitoring and management, Early mobility, and Family engagement bundle for which the patient was eligible on a given day. c Partial bundle compliance was an acknowledgment that some effect on outcomes may result from clinicians’ using some elements of the bundle even though not all bundle elements could be completed. Thus, partial compliance was used to determine the dose of compliance when something less than total compliance was provided to a given patient on a given day. This was calculated in two steps. First, a proportion was generated by taking the number of the individual elements in a particular day that a patient received and divi ding that by the number of elements that he or she was eligible to receive. Then the partial compliance was defined as the mean of all of that patient’s proport ions during his or her ICU stay. Copyright © 2016 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Feature Articles Barnes-Daly et al 176 www.ccmjournal.org February 2017 • Volume 45 • Number 2 and management of ICU delirium, found that it was the num- ber of implementation strategies used (in fact, six or more, equal to the number of steps in the ABCDEF bundle) that sta- tistically predicted reductions in ICU LOS and mortality. This quality improvement project, unlike others previously under- taken, ascribed equal importance to both the clinical improve- ments as well as IPT collaboration. The tenets of the IPT model, the training provided to the unit-based teams, and the opportu- nity given to team members to practice and embed the behav- iors of collaboration and shared decision making into everyday practice were felt to be the key components contributing to success in improving patient outcomes. The use of dedicated team members was also important, as these individuals were true champions for the project and the patients. Real-time data collection and feedback were achieved each day in ICU rounds. This facilitated focus on bundle element performance as a pri- ority of ICU care. Limitations of this report should be acknowledged. First, this QI project lacked the strict protocols found in random- ized, controlled trials. The IPT RNs, in their role as initial data collectors, were invested in the performance of their unit and team. This could have affected data integrity; however, random audits were performed to combat this as well as basic human error. In addition, very strict and well-defined data definitions and compliance rules were used for analysis. The bundle was applied across the entire patient cohort, in some cases includ- ing patients receiving palliative care. This resulted in bundle elements being used on the very ill and the lesser critically ill ICU patients alike, thus making it impossible to predict how compliance would factor into clinical outcome analyses. Real- world issues affecting bundle compliance included non-IPT physician buy-in and patient and family acceptance. Also, this was not a randomized controlled trial; thus, causation has not Figure 2. A, Delirium-free and coma-free days (DFCFDs) plotted in relationship to total compliance with the Awakening and Breathing Coordination, Choice of drugs, Delirium monitoring and management, Early mobility, and Family engagement (ABCDEF) bundle after adjusting for patient age, Acute Physiology and Chronic Health Evaluation (APACHE) III, and the proportion of days a patient was mechanically ventilated. b, DFCFDs plotted in relationship to partial compliance with the ABCDEF bundle after adjusting for patient age, APACHE III, and the proportion of days a patient was mechanically ventilated. Point estimates and confidence limit per decile of compliance increase are detailed in the Results section. IRR = incident rate ratio. Figure 1. A, Hospital survival plotted in relationship to total compliance with the Awakening and Breathing Coordination, Choice of drugs, Delirium monitoring and management, Early mobility, and Family engagement (ABCDEF) bundle after adjusting for patient age, Acute Physiology and Chronic Health Evaluation (APACHE) III, and the proportion of days a patient was mechanically ventilated. b , Hospital survival plotted in relationship to partial compliance with the ABCDEF bundle after adjusting for patient age, APACHE III, and the proportion of days a patient was mechanically ventilated. Point estimates and confidence limit per decile of compliance increase are detailed in the Results section. OR = odds ratio. Copyright 2016 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Critical Care Medicine www.ccmjournal.org 177 been ascribed to the outcome benefits. The strength of the experience lies in the very fact that it was not a randomized trial. This real-world experience can and should lend con- fidence to many hospitals that want to implement the PAD guidelines. These new outcomes data for the bundle as a whole can additionally help support quality improvement initiatives. Additional limitations that should be acknowledged include the following: the design and sample size benefits of our inves- tigation do not necessarily trump other statistical concerns. For example, it is helpful that our multivariable analysis allowed us to adjust for covariates and determine point estimates for the independent relationship between a dose response for bundle implementation and outcomes, thus building both on the data provided for individual bundle elements by prior randomized controlled trials and on data from the pre-post implementation of those individual elements once bundled by previous investiga- tors. In addition, though, it is important to consider for future work that more advanced study designs such as interrupted time series or stepped-wedge approaches would be valuable methods by which to gain an understanding of the relationship among the bundle elements, compliance, and clinical outcomes. It is reason- able to imagine that outcomes are a function both of compliance dose as well as severity of illness, clinician uptake and acceptance, and eICU versus bedside rounds implementation. Although we used palliative care as a barometer of severity of illness and aggressiveness of treatment to bolster our analysis beyond just APACHE III scores, future work could also incorporate an ongo- ing measure of severity such as daily Sequential Organ Failure Assessment scores. It was not possible to determine all the effects of the staff- ing model on compliance or the effect of implementation over time across an individual hospital or in relationship to other sites. In a future investigation, either a model that does not, for example, treat hospital as the random effect or another nuanced approach of assessing hospital, size, staffing, and the effect of time course on clinical outcomes could be studied. Some might consider it a limitation that we have not reported on the individual contributions of the bundle itself versus IPT. We considered these inextricably linked in the overall pro- cess of patient management and resultant clinical outcomes, and thus in our methodology, we did not attempt to conduct this large QI project in a way that would measure the effect of one versus the other, but rather take them as parts of a whole. Finally, although some view the lack of a rigorous study pro- tocol as a weakness, this experience in the community hospi- tal setting demonstrated the ability of community hospitals to implement evidence-based changes successfully. CONCLUSIONS The SCCM’s PAD guidelines can be implemented using the evidence-based ABCDEF bundle with significant and marked associated improvements for both in-hospital survival and days alive and free of delirium and coma even after adjusting for age, severity of illness, and MV. Further, even when delivered incom- pletely, bundle implementation results demonstrate that perfec- tion is not required to see improvements in patient outcomes. This project complements other recent publications in collec- tively providing the needed framework for large-scale quality improvement programs across a spectrum of hospital models. ACKNOWLEDGMENTS We thank the Gordon and Betty Moore Foundation for enabling conduct of this project. Sutter Health, Sacramento- Sierra Regional and Affiliate-Based ICU liberation teams’ dedication to the project allowed us to show the value of appli- cation of the bundle. Rebecca Petrella was instrumental as she provided data management and analysis. 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Directions: please follow explicitly *** primarily this assignment is filling in the tables- have attached all articles to use **** Use the attached “Literature Evaluation Table to complete this a
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Online Special Article Critical Care Medicine www.ccmjournal.org e825 1School of Pharmacy, Northeastern University, Boston, MA.2Division of Pulmonary, Critical Care and Sleep Medicine, Tufts Medical Center, Boston, MA. 3Faculty of Medicine, McGill University, Montreal, QC, Canada.4Regroupement de Soins Critiques Respiratoires, Réseau de Santé Res-piratoire, Montreal, QC, Canada. 5Ingram School of Nursing, McGill University, Montreal, QC, Canada.6Division of Pulmonary and Critical Care Medicine, Department of Physi-cal Medicine and Rehabilitation, School of Medicine, Johns Hopkins Uni- versity, Baltimore, MD. 7Department of Intensive Care Medicine, Brain Center Rudolf Magnus, University Medical Center, Utrecht University, Utrecht, The Netherlands. 8Department of Anesthesiology, Division of Anesthesiology Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN. 9Division of Sleep Medicine, Vanderbilt University Medical Center, Nash-ville, TN. 10 Division of Pulmonary and Critical Care, Brigham and Women’s Hospital and School of Medicine, Harvard University, Boston, MA. 11 Division of Anesthesiology, Perioperative Care and Pain Medicine, New York University Langone Health, New York, NY. 12 Division of Medicine, New York University Langone Health, New York, N Y. 13 Division of Neurology, New York University Langone Health, New York, N Y. 14Division of Surgery, New York University Langone Health, New York, NY.15 Department of Medicine (Critical Care), McMaster University, Hamilton, ON, Canada. 16 Department of Health Research Methods, Impact and Evidence, McMas- ter University, Hamilton, ON, Canada. 17 The Ohio State University, College of Nursing, Center of Excellence in Critical and Complex Care, Columbus, OH. 18The Ohio State University Wexner Medical Center, Columbus, OH.19 Department of Intensive Care Medicine, Radboud University Medical Center, Nijmegen, The Netherlands. 20 Division of Critical Care, London Health Sciences Centre, London, ON, Canada. 21 Schulich School of Medicine & Dentistry, University of Western Ontario, London, ON, Canada. 22 Center for Quality Aging, Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN. 23 Center for Health Services Research, Vanderbilt University Medical Cen- ter, Nashville, TN. DOI: 10.1097/CCM.0000000000003299 Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU John W. Devlin, PharmD, FCCM (Chair) 1,2; Yoanna Skrobik, MD, FRCP(c), MSc, FCCM (Vice-Chair) 3,4; Céline Gélinas, RN, PhD 5; Dale M. Needham, MD, PhD 6; Arjen J. C. Slooter, MD, PhD 7; Pratik P. Pandharipande, MD, MSCI, FCCM 8; Paula L. Watson, MD 9; Gerald L. Weinhouse, MD 10; Mark E. Nunnally, MD, FCCM 11,12,13,14 ; Bram Rochwerg, MD, MSc 15,16 ; Michele C. Balas, RN, PhD, FCCM, FAAN 17,18 ; Mark van den Boogaard, RN, PhD 19; Karen J. Bosma, MD 20,21 ; Nathaniel E. Brummel, MD, MSCI 22,23 ; Gerald Chanques, MD, PhD 24,25 ; Linda Denehy, PT, PhD 26; Xavier Drouot, MD, PhD 27,28 ; Gilles L. Fraser, PharmD, MCCM 29; Jocelyn E. Harris, OT, PhD 30; Aaron M. Joffe, DO, FCCM 31; Michelle E. Kho, PT, PhD 30; John P. Kress, MD 32; Julie A. Lanphere, DO 33; Sharon McKinley, RN, PhD 34; Karin J. Neufeld, MD, MPH 35; Margaret A. Pisani, MD, MPH 36; Jean-Francois Payen, MD, PhD 37; Brenda T. Pun, RN, DNP 23; Kathleen A. Puntillo, RN, PhD, FCCM 38; Richard R. Riker, MD, FCCM 29; Bryce R. H. Robinson, MD, MS, FACS, FCCM 39; Yahya Shehabi, MD, PhD, FCICM 40; Paul M. Szumita, PharmD, FCCM 41; Chris Winkelman, RN, PhD, FCCM 42; John E. Centofanti, MD, MSc 43; Carrie Price, MLS 44; Sina Nikayin, MD 45; Cheryl J. Misak, PhD 46; Pamela D. Flood, MD 47; Ken Kiedrowski, MA 48; Waleed Alhazzani, MD, MSc (Methodology Chair) 16,49 Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e826 www.ccmjournal.org September 2018 • Volume 46 • Number 9 24 Department of Anesthesia and Intensive Care, Montpellier University Saint Eloi Hospital, Montpellier, France. 25 PhyMedExp, INSERM, CNRS, University of Montpellier, Montpellier, France. 26 Melbourne School of Health Sciences, University of Melbourne, Mel- bourne, VIC, Australia. 27Faculte de Medecine Pharmacie, University of Poitiers, Poitiers, France.28Service de Neurophysiologie, CHU de Poitiers, Poitiers, France.29 Department of Critical Care, Maine Medical Center and School of Medi- cine, Tufts University, Portland, ME. 30 School of Rehabilitation Science, McMaster University, Hamilton, ON, Canada. 31 Department of Anesthesiology and Pain Medicine, Harborview Medical Center, University of Washington, Seattle, WA. 32 Division of Pulmonary and Critical Care Medicine, University of Chicago, Chicago, IL. 33 Department of Physical Medicine and Rehabilitation, Intermountain Healthcare, Salt Lake City, UT. 34 School of Nursing and Midwifery, Deakin University, Geelong, VIC, Aus- tralia. 35 Department of Psychiatry and Behavioral Sciences, Johns Hopkins Uni- versity School of Medicine, Baltimore, MD. 36 Division of Pulmonary, Critical Care and Sleep Medicine, School of Med- icine, Yale University, New Haven, CT. 37 Department of Anesthesiology and Critical Care, Grenoble Alpes Univer- sity Hospital, Grenoble, France. 38 School of Nursing, University of California San Francisco, San Fran- cisco, CA. 39Department of Surgery, University of Washington, Seattle, WA.40 Department of Critical Care and Perioperative Medicine, School of Clini- cal Sciences, Monash University, Melbourne, VIC, Australia. 41Department of Pharmacy, Brigham and Women’s Hospital, Boston, MA.42 Frances Payne Bolton School of Nursing, Case Western Reserve Uni- versity, Cleveland, OH. 43 Department of Anesthesia and Critical Care, McMaster University, Ham- ilton, ON, Canada. 44 Welch Medical Library, Johns Hopkins University, Baltimore, MD.45 Department of Psychiatry and Behavioral Sciences, New York Medical College, Valhalla, NY. 46Department of Philosophy, University of Toronto, Toronto, CA.47Division of Anesthesiology, Stanford University Hospital, Palo Alto, CA.48 Patient and Family Advisory Committee, Johns Hopkins Hospital, Balti- more, MD. 49 Department of Medicine (Critical Care and Gastroenterology), McMas- ter University, Hamilton, ON, Canada. These guidelines are endorsed by the American Association of Critical- Care Nurses, American College of Chest Physicians, American College of Clinical Pharmacy, American Delirium Society, Australian College of Criti- cal Care Nurses, Canadian Critical Care Society, Eastern Association for the Surgery of Trauma, European Delirium Association, European Federa- tion of Critical Care Nursing Associations, Neurocritical Care Society, and Society of Critical Care Anesthesiologists. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals.lww.com/ccmjournal). Dr. Devlin has received research funding from the National Institute of Aging, National Heart, Lung and Blood Institute, and AstraZeneca Pharmaceutical s, he is on the editorial board of Critical Care Medicine, and he is the president of the American Delirium Society. Dr. Skrobik participates in the ATS and the American College of Chest Physicians (ACCP), and she is on the editorial board for Intensive Care Medicine and Chest. Dr. Needham is a principal investiga- tor on a National Institutes of Health (NIH)-funded, multicentered randomized trial (R01HL132887) evaluating nutrition and exercise in acute respiratory failure and, related to this trial, is currently in receipt of an unrestricted r esearch grant and donated amino acid product from Baxter Healthcare and an equipment loan from Reck Medical Devices to two of the participating study sites, external to h is institution. Dr. Slooter has disclosed that he is involved in the development of an electroencephalogram-based delirium monitor, where any (future) profits from electroencephalogram-based delirium monitoring will be used for future s cien- tific research only. Dr. Pandharipande’s institution received funding from Hospira (research grant to purchase study drug [dexmedetomidine] in collaboration with a NIH-funded RO1 study) and disclosed that he is the past president of the American Delirium Society. Dr. Nunnally participates in the Society of Critical Care Anesthesiologists, International Anesthesia Research Society, and Ameri- can Society of Anesthesiology (ASA). Dr. Rochwerg participates as a guideline methodologist for other organizations (i.e., American Thoracic Society [ATS] and Canadian Blood Service) in addition to the Society of Critical Care Medicine. Dr. Balas received funding from Select Medical (primary investigator on rese arch study exploring Assess, Prevent, and Manage Pain, Both Spontaneous Awaken- ing Trials and Spontaneous Breathing Trials, Choice of analgesia and sedation, Delirium: Assess, Prevent, and Manage, Early mobility and Exercise, and Family engagement and empowerment bundle adoption). Dr. Bosma received fund- ing from the Canadian Institutes of Health Research (CIHR) where she is the primary investigator of an industry partnered research grant with Covidien as the industry partner of the CIHR for a study investigating proportional assist ventila- tion versus pressure support ventilation for weaning from mechanical ventilation. Dr. Brummel participates in the ATS (Aging and Geriatrics Working Group Co- Chair) and ArjoHuntleigh (advisory board activities). Dr. Chanques participates in other healthcare professional organization activities. Dr. Denehy participates in the Australian Physiotherapy Association. Dr. Drouot participates in the French Sleep Society and the French Institute for Sleep and Vigilance. Mr. Joffe par- ticipates on committees for ASA. Dr. Kho received funding from Restorative Therapies (Baltimore, MD) (loaned two supine cycle ergometers for ongoing research). Dr. Kress received funding from a dexmedetomidine speaker program, he participates in the ATS and ACCP, and he has served as an expert witness in medical malpractice. Dr. McKinley participates in the American Association of Critical-Care Nurses (AACN) (editorial board of American Journal of Critical Care) and the American Heart Association (editorial board of Journal of Car- diovascular Nursing). Dr. Neufeld participates in the American Delirium Society (board member). Dr. Pisani participates in the ACCP (Chair Scientific Program- ming Committee and Steering Committee Women’s Health Network). Dr. Payen received funding from Baxter SA (distributor of dexmedetomidine in France), and he has received honorariums from Baxter SA (oral presentations of dex- medetomidine). Ms. Pun participates as an AACN speaker at the National Con- ference. Dr. Puntillo participates in other healthcare professional organizations (e.g., AACN). Dr. Robinson participates in the Easter Association for the Surgery of Trauma, American College of Surgeons, and American Association for the Surgery of Trauma. Dr. Shehabi received funding from an unrestricted research grant (drug supply) from Pfizer (Hospira) and Orion Pharma to an o ngoing multi- national multicenter study. Mr. Szumita participates in several committees for the American Society of Health-System Pharmacists. Ms. Price has disclosed t hat she is a medical librarian working at Johns Hopkins University, and she consults as an information specialist to the Cochrane Urology Review Group. Dr. Flood participates on the Society of Obstetric Anesthesia and Perinatology research committee and the ASA Chronic Pain Committee. The remaining authors have disclosed that they do not have any potential conflicts of interest. The American College of Critical Care Medicine (ACCM), which honors indi- viduals for their achievements and contributions to multidisciplinary critical care medicine, is the consultative body of the Society of Critical Care Medi- cine (SCCM) that possesses recognized expertise in the practice of critical care. The College has developed administrative guidelines and clinical prac- tice parameters for the critical care practitioner. New guidelines and practice parameters are continually developed, and current ones are systematicall y reviewed and revised. For information regarding this article, E-mail: [email protected] Objective: To update and expand the 2013 Clinical Practice Guidelines for the Management of Pain, Agitation, and Delirium in Adult Patients in the ICU. Design: Thirty-two international experts, four methodologists, and four critical illness survivors met virtually at least monthly. All sec- tion groups gathered face-to-face at annual Society of Critical Care Medicine congresses; virtual connections included those unable to attend. A formal conflict of interest policy was developed a priori and enforced throughout the process. Teleconferences and Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e827 electronic discussions among subgroups and whole panel were part of the guidelines’ development. A general content review was completed face-to-face by all panel members in January 2017. Methods: Content experts, methodologists, and ICU survivors were represented in each of the five sections of the guidelines: Pain, Agita- tion/sedation, Delirium, Immobility (mobilization/rehabilitation), and Sleep (disruption). Each section created Population, Intervention, Comparison, and Outcome, and nonactionable, descriptive ques- tions based on perceived clinical relevance. The guideline group then voted their ranking, and patients prioritized their importance. For each Population, Intervention, Comparison, and Outcome ques- tion, sections searched the best available evidence, determined its quality, and formulated recommendations as “strong,” “conditional,” or “good” practice statements based on Grading of Recommenda- tions Assessment, Development and Evaluation principles. In addi- tion, evidence gaps and clinical caveats were explicitly identified. Results: The Pain, Agitation/Sedation, Delirium, Immobility (mobi- lization/rehabilitation), and Sleep (disruption) panel issued 37 recommendations (three strong and 34 conditional), two good practice statements, and 32 ungraded, nonactionable statements. Three questions from the patient-centered prioritized question list remained without recommendation. Conclusions: We found substantial agreement among a large, inter- disciplinary cohort of international experts regarding evidence sup- porting recommendations, and the remaining literature gaps in the assessment, prevention, and treatment of Pain, Agitation/sedation, Delirium, Immobility (mobilization/rehabilitation), and Sleep (disrup- tion) in critically ill adults. Highlighting this evidence and the rese arch needs will improve Pain, Agitation/sedation, Delirium, Immobility (mobilization/rehabilitation), and Sleep (disruption) management and provide the foundation for improved outcomes and science in this vulnerable population. (Crit Care Med 2018; 46 :e825– e873) Key Words: delirium; guidelines; immobility; intensive care; mobilization; pain; sedation; sleep C linical practice guidelines are published, often by pro- fessional societies, because they provide a current and transparently analyzed review of relevant research with the aim to guide clinical practice. The 2018 Pain, Agitation/ sedation, Delirium, Immobility (rehabilitation/mobilization), and Sleep (disruption) (PADIS) guideline builds on this mis- sion by updating the 2013 Pain, Agitation, and Delirium (PAD) guidelines (1); by adding two inextricably related clinical care topics—rehabilitation/mobilization and sleep; by including patients as collaborators and coauthors; and by inviting an international panel of experts from high-income countries as an early step toward incorporating more diverse practices and expertise from the global critical care community. Readers will find rationales for 37 recommendations (derived from actionable Patient, Intervention, Comparison, and Outcome [PICO] questions); two ungraded good practice statements (derived from actionable PICO questions where it is unequivo- cal, the benefits of the intervention outweigh the risks but direct evidence to support the intervention does not exist); and 32 ungraded statements (derived from nonactionable, descriptive questions) across the five guideline sections. The supplemental digital content figures and tables linked to this guideline provide background on how the questions were established, profiles of the evidence, the evidence-to-decision tables used to develop recom- mendations, and voting results. Evidence gaps and future research directions are highlighted in each section. The five sections of this guideline are interrelated, and thus, the guideline should be con- sidered in its entirety rather than as discrete recommendations. Knowledge translation and implementation effectiveness are an important segue to our guideline document and work to foster advances in clinical practice related to PADIS assessment, preven- tion, and treatment. A PADIS guideline implementation and inte- gration article separately created to facilitate this is available (2). Many challenges characterize developing effective PADIS-related educational and quality improvement programs. Although some have not achieved expected outcomes (3, 4), many quality improvement efforts in this field have been successful (5–10). METHODS The panel followed the Grading of Recommendations Assess- ment, Development and Evaluation (GRADE) working group’s methodology for clinical practice guideline development. Guideline chairs, with input from the methodology team, cre- ated a protocol before beginning formal work on the guideline. Chairs, group heads, and panel members, with input from ICU survivors (11), selected topics that are important to patients and practicing clinicians. A list of questions was developed for each topic, and questions and outcomes were prioritized through an electronic survey following the GRADE principles (12). Once the list of questions was finalized, a university-based librarian conducted a literature review of five electronic databases from 1990 to October 2015 based on priority topics voted on by the members and revised by critical illness survivors. The librarian finalized the relevant search terms with the groups and extracted literature based on these prioritized topics. These publications were then evaluated for their methodologic rigor that determined the highest quality of evidence available per outcome and per question in keeping with GRADE guidance. Evidence evaluation was performed by determining its relevance for each question; members with a financial or intellectual conflict of interest did not review questions related to their conflict. Full-text screening was performed in duplicate. Each group used the GRADE evidence- to-decision framework to formulate the preliminary recommen- dations (12). Further, all five groups’ comments on the overall recommendations and the literature provided to support it were reviewed by the chair and vice-chair after recommendation voting and screened for potential or perceived conflict. Subsequently, recommendations were discussed in person among the full panel. Then, only members who were free of overt or potential conflict of interest voted electronically for each recom- mendation. We defined consensus as greater than 80% agreement with greater than 70% response rate. ICU survivors participated in every step of the guideline development, which provided a unique perspective for this guideline. We used the GRADE cri- teria to formulate good practice statements where appropri- ate (11). For nonactionable, descriptive questions, evidence was Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e828 www.ccmjournal.org September 2018 • Volume 46 • Number 9 summarized and ungraded statements were provided. A complete description of the methods is found in Supplemental Appendix 1 (Supplemental Digital Content 1, http://links.lww.com/CCM/ D759). A detailed description of the methodologic innovations that characterize these guidelines is published separately (13). PA I N Pain management is complex because pain patterns are highly individual (e.g., acute, chronic, and acute-on-chronic), it arises from different sources (e.g., somatic, visceral, and neuropathic), and patients have subjective perceptions and have exceedingly variable tolerability. A consistent approach to pain assessment and management is paramount given the unique features of critically ill adults that include impaired communication, altered mental status, mechanical ventilation, procedures and use of invasive devices, sleep disruption, and immobility/mobility status (14). Critically ill adults experience moderate-to-severe pain at rest (15) and during standard care procedures (16). Pain is defined as “an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage” (17). Pain should be considered to be “whatever” the experiencing person says it is, existing “when- ever” the experiencing person says it does (18). Although the reference standard measure of pain is a patient’s self-report, the inability to communicate clearly does not negate a patient’s pain experience or the need for appropriate pain management (19). Fortunately, validated behavioral pain scales provide alter – native measures for pain assessment in those patients unable to self-report their pain. Severe pain negatively affects patient status (e.g., cardiac instability, respiratory compromise, immu- nosuppression) in critically ill adults; implementation of assess- ment-driven and standardized pain management protocols improves ICU outcomes and clinical practice (5, 20). Carefully titrated analgesic dosing is important when balancing the ben- efits versus potential risks of opioid exposure (21–25). In this guideline section, we address three actionable questions and two descriptive questions related to the pain experience of criti- cally ill adults (see prioritized topic list in Supplemental Table 1 [Supplemental Digital 2, http://links.lww.com/CCM/D760] and voting results in Supplemental Table 2 [Supplemental Digital Content 3, http://links.lww.com/CCM/D761]). The evidence summaries and evidence-to-decision tables used to develop recommendations for the pain group are available in Supplemental Table 3 (Supplemental Digital Content 4, http:// links.lww.com/CCM/D762), and the forest plots for all meta- analyses are available in Supplemental Figure 1 (Supplemental Digital Content 5, http://links.lww.com/CCM/D763). Risk Factors Question: What factors influence pain in critically ill adults during both rest and during procedures? Ungraded Statements: Pain at rest is influenced by both psycho- logic (e.g., anxiety and depression) and demographic (e.g., young age, one or more comorbidities, and history of surgery) factors. Pain during a procedure is influenced by preprocedural pain intensity, the type of procedure, underlying surgical or trauma diagnoses, and demographic factors (younger age, female sex, and non-white ethnicity). Rationale: Pain is common in critically ill adults at rest and during procedures including regular activities (e.g., turning) and discrete procedures (e.g., arterial catheter insertion). The prior guidelines document the incidence, frequency, severity, and impact of pain (1): 1) adult medical, surgical, and trauma ICU patients routinely experience pain, both at rest and dur – ing standard ICU care; 2) procedural pain is common in adult ICU patients; and 3) pain in adult cardiac surgery patients is common and poorly treated; women experience more pain than men. This guideline’s new descriptive question focuses on observational studies that have identified factors associated with pain in ICU patients at rest and during procedures. During Rest. Five studies (evaluating from 74 to 5,176 patients each) describe factors associated with pain in medical, surgical, and trauma ICU populations (26–30). The time from pain recognition to analgesic initiation, the pain being worse than what the patient expected, and ICU length of stay (LOS) are significant predictors of higher self-reported pain intensity (26). The amount of analgesic administered after cardiac and abdominal surgery in the ICU is a significant predictor of later pain intensity, pain affect (i.e., emotional experience), and pain sensation (i.e., quality of pain related to the sensory dimension of the pain experience) (27). Among 301 mechanically ven- tilated patients, younger age and prior surgery both predicted greater pain at rest (28). After cardiac surgery, patients with preoperative anxiety or depression have a higher level of self- reported pain intensity (29). One large cohort of 5,176 medical ICU adults reported the following baseline predictors of higher self-reported pain intensity during the ICU admission: younger age; need for support to conduct daily living activities; num- ber of comorbidities such as cardiac and pulmonary diseases; depression; anxiety; and an expectation of a future poor quality of life (30). Clinicians should make an effort to obtain informa- tion from all relevant sources, including family and other care- givers, about their patient’s pre-ICU illness background to better consider these factors in plans to improve patient comfort. During Procedures. A total of 12 studies (evaluating from 30 to 5,957 patients each) have evaluated pain level, mostly through patient self-reports, during 12 different procedures in various ICU populations (i.e., medical, surgical, cardiovascular, trauma, and neurologic) (27, 28, 31–37). The following proce- dures are associated with the greatest increased pain intensity: arterial catheter insertion, chest tube removal (CTR), wound drain removal (16), turning (32) and repositioning, and tra- cheal suctioning (37). (A complete list of painful procedures can be found in Supplemental Table 4 [Supplemental Digital Content 6, http://links.lww.com/CCM/D764].) Patients with a surgical history/diagnosis or trauma had worse procedural pain (32), as did younger (37), female (33), and non-white patients (34, 37); however, in one report evaluating six procedures (35), no association was found between procedural pain intensity and age except during wound care and tracheal suctioning. Opioid use before or during a procedure was found to be a risk factor for higher procedural pain in one recent, large multinational Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e829 study (16), but not in a smaller, older study limited to surgical ICU patients (27). This divergence may be due to a focus on the dose rather than efficacy of opioid therapy, mistimed opioid adminis- trations (relative to the procedure), and the inclusion of patients with prior opioid exposure. Such findings emphasize the impor – tance of preprocedural pain assessment and preemptive analgesia, when appropriate, for procedures known to cause pain. Indeed, severe procedural pain is associated with severe adverse events (e.g., tachycardia, bradycardia, hypertension, hypotension, desaturation, bradypnea, and ventilator distress) (21) that may be prevented with appropriate pain assessment and preemptive analgesia. Evidence Gaps: Future research should include the following: 1) an exploration of the affect of sociodemographic variables such as age, gender, and ethnicity that may affect pain and response to pharmacologic intervention; 2) identification of pharmaco- kinetic, pharmacogenomic, and gender-associated factors that influence analgesic responses; 3) a determination of what pain- related behaviors predict self-reported pain; 4) the development and study of objective measures (e.g., pupillary reflex dilatation response) to determine pain before and during a planned pro- cedure in patients unable to self-report pain; 5) identification of biomarkers associated with pain; 6) conduct of clinical trials of pain management interventions during procedures; and 7) inves- tigation of the relationship among opioid effectiveness, opioid tolerance, opioid-related hyperalgesia, and procedural pain (38). Assessment Question: What are the most reliable and valid pain assessment methods to use in critically ill adults? Self-Report Scales. Ungraded Statements: A patient’s self-report of pain is the reference standard for pain assessment in patients who can communicate reliably. Among critically ill adults who are able to self-report pain, the 0–10 Numeric Rating Scale (NRS) administered either ver – bally or visually is a valid and feasible pain scale. Rationale: Four studies served to answer the above ques- tion (39–42). One study evaluated 111 medical/surgical ICU patients for pain in a randomized order using five different self-report scales: 1) 0–10 cm Visual Analog Scale Horizontal (VAS-H); 2) 0–10 cm Visual Analog Scale (VAS) Vertical; 3) Verbal Descriptor Scale (VDS): no pain, mild pain, moder – ate pain, severe pain, and extreme pain); 4) 0–10 NRS Oral (NRS-O); and 5) 0–10 NRS Visual (NRS-V) in a horizontal format (39). The NRS-V had the highest rate of success (i.e., response obtained) (91%); the VAS-H the lowest (66%). The NRS-V success rate was significantly greater than the VDS and VAS (both p < 0.001) and NRS-O (p < 0.05). It also had the best sensitivity, negative predictive value, and accuracy; given its ease of use, it was most highly favored by ICU patients. The 0–10 Faces Pain Thermometer (FPT) (4.25 × 14 verti- cal format) scale, validated in 105 postoperative cardiac surgery ICU patients, revealed higher FPT scores during turning and good correlation with the VDS for pain supporting its construct validity (43). Patients evaluated the faces and numbers in the FPT favorably and nearly all rated it as easy to use and useful in iden- tifying pain intensity. When compared with the 0–10 NRS, the Wong-Baker FACES scale resulted in higher pain scores suggesting that pain scales developed for children should be evaluated cau- tiously before being used in adults (41). Finally, in another study (42), cardiovascular surgery ICU patients stated that the 0–10 NRS or Verbal Rating Scale (VRS) of six descriptors scale is better for evaluating their pain than the 0–100 VAS; they prefer to have their pain evaluated with the VRS (vs the 0–10 NRS). In summary, the 0–10 NRS in a visual format is the best self-reported pain scale to use in critically ill adults. A descriptive pain scale like the VDS should be considered for ICU patients unable to use a numerically formatted scale such as the 0–10 NRS. Behavioral Assessment Tools. Ungraded Statement: Among critically ill adults unable to self-report pain and in whom behaviors are observable, the Behavioral Pain Scale in intubated (BPS) and nonintubated (BPS-NI) patients and the Critical-Care Pain Observation Tool (CPOT) demonstrate the greatest validity and reliability for monitoring pain. Rationale: We updated this psychometric analysis of behav- ioral pain assessment tools, which was initiated in the 2013 guidelines (1) and in a systematic review (44). Fifty-three articles pertained to the development, validation, and implementation of 12 pain scales for use in critically ill adults unable to self-report pain. Four additional pain scales were included: the FACES Scale (45), the Facial Action Coding System (46), the Pain In Advanced Dementia (PAINAD) (47), and the Behavior Pain Assessment Tool (BPAT) (48). In this analysis, we considered a pain scale with a psychometric quality score of 15–20 to have very good psycho- metric properties; a score of 12–14.9 good psychometric prop- erties; 10–11.9 some acceptable psychometric properties; and 0–9.9 very few psychometric properties reported and/or unac- ceptable results (1, 49). A list of studies (by pain scale) published since 2013 are included in Supplemental Table 5 (Supplemental Digital Content 7, http://links.lww.com/CCM/D765), and the psychometric scores and the quality of evidence supporting each pain scale are described in Supplemental Table 6 (Supplemental Digital Content 8, http://links.lww.com/CCM/D766). The CPOT and the BPS remain the most robust scales for assessing pain in critically ill adults unable to self-report. Each has very good psychometric properties with scores of 16.7 and 15.1, respectively. The BPS-NI obtained a psychometric weighted score of 14.8. Although both the BPS and the CPOT have been validated across large samples of medical, surgical, and trauma ICUs (50–54), studies involving brain-injured patients using the BPS (50, 51) and CPOT (52–54) are small. In the brain-injured population, although the construct validity of both scales is supported with higher scores during painful procedures (vs rest and nonpainful procedures), patients pre- dominantly expressed pain-related behaviors that were related to level of consciousness; grimacing and muscle rigidity were less frequently observed (50, 52–54). An additional study (51), although not evaluating validity, found that BPS and BPS-NI were feasible and reliable to use in the brain-injured population. Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e830 www.ccmjournal.org September 2018 • Volume 46 • Number 9 Of note, Behavioral Pain Scales have been validated in the fol- lowing languages (other than French or English): CPOT— Mandarin (55), Korean (56), Spanish (57), and Swedish (58); BPS and BPS-NI—Mandarin (59). The BPAT, the first behavioral pain assessment tool to undergo international validation, obtained a psychometric weighted score of 10.6 when tested in its original English ver – sion and 12 other languages among 3,851 critically ill adults from 28 countries (48). This is less than reported for either the BPS or the CPOT because the feasibility and impact of its use once implemented in clinical practice remain to be inves- tigated. By the time this implementation research is complete, it may be of use in countries/languages where neither the BPS nor CPOT has been validated (48). Each of the other scales considered (i.e., the Face, Legs, Activity, Cry, Consolability; the Non-verbal Pain Assessment Tool; the PAIN; the BOT; the FACES; the Fear-Avoidance Components Scale; and the PAINAD) had low psychometric weighted scores (< 10). Proxy Reporters. Ungraded Statement: When appropriate, and when the patient is unable to self-report, family can be involved in their loved one’s pain assessment process. Rationale: The intensity and distress of 10 different patient symptoms, including pain, were independently assessed by ICU patients, nurses, physicians, and family members (60). For both pain intensity and pain distress, the reports of family proxy reporters were found to be closer to ICU patients’ self-reports than that of the patients’ nurses and physicians. However, the agreement between family and patients was only moderate. A second study compared ICU nurse and patient pain percep- tion across nine procedures using a 10-point scale. Although patient and nurse pain scores for nasogastric tube insertion and tracheal aspiration were similar, they were significantly higher among nurses (vs patients) for position change, subcutaneous injection, blood sugar testing, and blood pressure (BP) measure- ment (61). No statistical measure of agreement between nurse and ICU patient scores was reported. Finally, compared with seriously ill patients’ self-reports, surrogates correctly identified pain presence 74% of the time and pain severity 53% of the time, with a tendency to overestimate pain intensity (62). There are families who may not want to be involved in pain assess- ment or situations where family involvement in pain assess- ment is not appropriate. Family involvement in pain assessment should not substitute for an ICU team’s role and commitment to systematic pain assessment and optimal analgesia. Physiologic Measures. Ungraded Statement: Vital signs (VS) (i.e., heart rate [HR], BP, respiratory rate [RR], oxygen saturation [Sp o2], and end- tidal Co 2) are not valid indicators for pain in critically ill adults and should only be used as cues to initiate further assessment using appropriate and validated methods such as the patien s self-report of pain (whenever possible) or a behavioral scale (i.e., Bps, Bps-Ni, CpoT). Rationale: The 2013 guidelines state that VS should not be used alone to assess pain in critically ill adults (1). Fourteen studies (four new since the 2013 guidelines) (n = 30–755 patients) evaluated the validity of using VS for pain assess- ment across various ICU populations and reported inconsis- tent results (31, 34, 37, 63–73). In 11 of 14 studies, HR and/ or BP was found to increase when ICU patients were exposed to a nociceptive procedure (e.g., endotracheal/tracheal suction- ing) compared with either rest or a nonnociceptive procedure (e.g., cuff inflation, eye care) (34, 37, 63–71). However, these HR and BP increases (< 20% in all studies) were not considered to be clinically significant by the authors. In addition, VS were found to increase during both nociceptive and nonnociceptive procedures suggesting the lack of validity of these indicators (68, 70, 72–74). In some studies, RR increased and/or end-tidal CO 2 decreased during a painful procedure (64, 65, 68), whereas Sp o2 decreased (65, 69). Except for associations found among these Vss (i.e., HR, RR, and sp o2) and the pain described by cardiac surgery iCU patients themselves (64) and by critically ill adults with a traumatic brain injury (TBi) (74), an association between Vs changes and patient self-reported pain was not observed (65, 67, 68, 70). in one quality improvement project (19), changes in Vs (e.g., tachycardia, bradycardia, hyperten- sion, hypotension, desaturation, and bradypnea) during nurs- ing care (bathing, massage, sheet-change, repositioning) were considered as severe pain-related adverse events. Although Vs changes can be considered to be pain-related adverse events, they should not be used for pain assessment in critically ill adults. Evidence Gaps: When evaluating self-reported pain inten- sity scales, further research comparing FACES pain scales with other rating scales (e.g., NRS, VDS, and VAS) in heterogeneous ICU populations is required. Family members’ acting as proxy reporters using behavioral pain assessment tools (e.g., BPS/ BPS-NI and CPOT) for ICU patients unable to self-report should be explored. Behavioral scales are the alternative mea- sures to use when the patient is unable to self-report (75). Scale revisions could enhance the validity of their use in ICU patients with brain injury and other neurologically critically ill patients (such as those with neuromuscular diseases); research on the application of the BPAT in ICU practice is encour – aged. However, situations exist for which behavioral scales are impossible to use (e.g., unresponsive patients with a Richmond Agitation-Sedation Scale [RASS] ≤ −4). In such situations, no alternative methods are currently available to ICU clinicians. Other technology that may be useful in the ICU pain assess- ment process should be explored. Technology measuring HR variability (e.g., the Analgesia Nociception Index) (76, 77) or incorporating simultaneously different physiologic parameters (e.g., Nociception Level Index) (78) may be relevant. Pupillary reflex dilation using video pupillometry has shown promising results in pain assessment of critically ill adults (79–81), but future research is necessary to investigate the benefits, harms, and feasibility of implementation in the ICU. Pharmacologic Adjuvants to Opioid Therapy Opioids remain a mainstay for pain management in most ICU set- tings. However, their side effects preoccupy clinicians because of Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e831 important safety concerns, such as sedation, delirium, respiratory depression, ileus, and immunosuppression, may lengthen ICU LOS and worsen post-ICU patient outcome. A “multi-modal anal- gesia” approach has been used in the perioperative setting to reduce opioid use and to optimize postoperative analgesia and rehabili- tation (82). Nonopioid analgesics such as acetaminophen, nefo- pam, ketamine, lidocaine, neuropathic agents, and nonsteroidal anti-inflammatory drugs (NSAIDs) have each been evaluated in critically ill adults with the aim of sparing opioid use and improv- ing analgesic effectiveness. In addition to opioids, these nonopioid analgesic alternatives may be combined with regional anesthetics and nonpharmacologic interventions known to reduce pain (see below). Dose, duration, and pharmacologic effectiveness need to be evaluated when combination strategies are being evaluated. Acetaminophen. Question: Should acetaminophen be used as an adjunct to an opioid (vs an opioid alone) for pain management in criti- cally ill adults? Recommendation: We suggest using acetaminophen as an adjunct to an opioid to decrease pain intensity and opioid con- sumption for pain management in critically ill adults (condi- tional recommendation, very low quality of evidence). Rationale: Two single-centered, parallel-group randomized controlled trials (RCTs) evaluated IV acetaminophen 1 g every 6 hours (q6h) versus placebo in a double-blind fashion in 113 postcardiac surgery patients (83) and in an open design in 40 postabdominal surgical ICU patients (84). After 24 hours, pooled analysis of these two trials revealed a decrease in pain intensity at rest measured by the VAS-H (mean difference [MD], –0.5 points; 95% CI, –0.7 to –0.2; moderate quality) and in opioid consump- tion (MD, –4.5 mg [morphine equivalents]; 95% CI, –6.6 to –2.5; moderate quality) in the acetaminophen groups. In the study demonstrating the greatest reduction in opioid consumption (84), time to extubation, sedation, and nausea rate were all sig- nificantly improved in the acetaminophen group. The risk for IV acetaminophen-associated hypotension (a decrease in the mean arterial pressure > 15 mm Hg may occur in up to 50% of patients) may preclude its use in some patients (85). Given these findings, panel members suggest using acetaminophen (IV, oral, or rectal) to decrease pain intensity and opioid consumption when treat- ing pain in critically ill patients, particularly in patients at higher risk for opioid-associated safety concerns (e.g., critically ill patient recovering from abdominal surgery and at risk for ileus or nausea and vomiting). Although IV acetaminophen was the intervention evaluated in the two relevant studies, the panel felt that this con- ditional recommendation was generalizable to all acetaminophen administration routes. Although not studied in the critically ill, the absorption (i.e., bioavailability) of acetaminophen adminis- tered by the oral or rectal route may be reduced in some criti- cally ill subgroups (e.g., those requiring vasopressor support). The IV route of administration may be preferable in these situations, balanced with the hypotension risk described with IV (but not enteral) acetaminophen administration. The acquisition cost and availability of IV acetaminophen vary widely among countries and will likely influence the decision to use this specific formula- tion of acetaminophen in critically ill adults. Nefopam . Question: Should nefopam be used either as an adjunct or a replacement for an opioid (vs an opioid alone) for pain man- agement in critically ill adults? Recommendation: We suggest using nefopam (if feasible) either as an adjunct or replacement for an opioid to reduce opioid use and their safety concerns for pain management in critically ill adults (conditional recommendation, very low quality of evidence). Rationale: Nefopam is a nonopioid analgesic that exerts its effect by inhibiting dopamine, noradrenaline, and serotonin recapture in both the spinal and supraspinal spaces. A 20-mg dose has an analgesic effect comparable to 6 mg of IV morphine (86). Unlike non–cyclooxygenase (COX)-1 selective NSAIDs (e.g., ketorolac), nefopam has no detrimental effects on hemo- stasis, the gastric mucosa, or renal function; unlike acetamin- ophen, it has no detrimental effects on hepatic function, and unlike opioids, it has no detrimental effects on vigilance, venti- latory drive, and intestinal motility. However, nefopam use can be associated with tachycardia, glaucoma, seizure, and delirium. Nevertheless, nefopam may be a safe and effective alternative or adjunctive analgesic for ICU patients. Although not available in United States and Canada, nefopam is a low-cost drug that is used in nearly 30 countries. For example, after acetaminophen, it is the second most frequently used nonopioid medication in mechanically ventilated ICU patients in France (87). A three-armed, double-blind, noninferiority RCT tested the effect of nefopam, fentanyl, and combination nefopam + half-dose fentanyl, administered by a patient-controlled anal- gesia (PCA) device, in 276 elective cardiac surgery patients in one ICU (88). Patients’ self-reported pain intensity was not significantly different among the three groups despite similar PCA volumes. Nausea was significantly more frequent in the fentanyl group compared with nefopam groups. If available, nefopam could be used to reduce the opioid consumption and opioid-associated side effects, such as nausea, after an evalua- tion of the risk-to-benefit ratio of all available analgesic options and patient reassessment for potential side effects (tachycardia, glaucoma, seizure, and delirium) (89–92). Ketamine. Question: Should ketamine be used as an adjunct to an opi- oid (vs an opioid alone) for pain management in critically ill adults? Recommendation: We suggest using low-dose ketamine (0.5 mg/kg IVP x 1 followed by 1-2 μg/kg/min infusion) as an adjunct to opioid therapy when seeking to reduce opioid con- sumption in postsurgical adults admitted to the ICU (condi- tional recommendation, very low quality of evidence). Rationale: Ketamine, because of its N -methyl- d-aspartate (NmdA) receptor-blocking properties and potential to reduce the risk for opioid hyperalgesia, has been evaluated in postop- erative adults as a strategy to improve pain relief while reducing opioid requirements in two non-iCU systematic reviews (93, 94). in a single-center, double-blind RCT of 93 postabdominal sur – gery iCU patients, adjunctive ketamine (0.5 mg/kg iV push, 2 g/ kg/min infusion 24 hr followed by 1 g/kg/min 24 hr) was Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e832 www.ccmjournal.org September 2018 • Volume 46 • Number 9 associated with reduced morphine consumption (MD, –22 mg; 95% CI, –30 to –14; low quality) but no difference in patients’ self-reported pain intensity (95). The panel noted that reduced opioid consumption is only a surrogate for better patient-cen- tered outcomes. The incidence of side effects (i.e., nausea delir – ium, hallucinations, hypoventilation, pruritus, and sedation) was not different between the ketamine and opioid-alone groups. Based on this generally positive ICU RCT, the panel made a con- ditional recommendation for the use of low-dose ketamine as an adjunct to opioids to optimize acute postoperative pain manage- ment in critically ill adults once the benefits and harms of its use have been considered by clinicians. Because this single available ICU RCT had a high risk of bias and was also limited to post- operative abdominal surgery patients, the panel also considered indirect evidence from RCTs involving non-ICU patients that, overall, suggested benefit with ketamine use (93, 94). Neuropathic Pain Medications. Question: Should a neuropathic pain medication (e.g., gab- apentin, carbamazepine, and pregabalin) be used as an adjunct to an opioid (vs an opioid alone) for pain management in criti- cally ill adults? Recommendations: We recommend using a neuropathic pain medication (e.g., gabapentin, carbamazepine, and pregabalin) with opioids for neuropathic pain management in critically ill adults (strong recommendation, moderate quality of evidence). We suggest using a neuropathic pain medication (e.g., gaba- pentin, carbamazepine, and pregabalin) with opioids for pain management in ICU adults after cardiovascular surgery (con- ditional recommendation, low quality of evidence). Rationale: Two RCTs in ICU patients with Guillain-Barré syndrome (96, 97) and two RCTs in postcardiac surgery ICU patients (98, 99) were included. Each of these trials, although double-blinded, was small and single centered. The first Guillain-Barré syndrome trial compared gabapentin (15 mg/ kg/d) with placebo in 18 patients using a crossover design (96). In the second Guillain-Barré syndrome trial, gabapen- tin (300 mg/d), carbamazepine (100 mg/d), and placebo were compared in 36 patients using a parallel design (97). Pooled analysis showed that neuropathic agents reduced pain inten- sity measured by the 0–10 NRS (MD, –3.44 cm; 95% CI, –3.90 to –2.98; high quality). Patients receiving gabapentin had also significantly lower pain intensity than patients receiving car – bamazepine (97). Two postcardiac surgery trials compared pregabalin (150 mg before surgery then 150 mg daily) with placebo in 40 and 60 patients, respectively (98, 99). Pooled analysis of these four trials demonstrated a sig- nificant decrease in opioid consumption in the first 24 hours after neuropathic agent initiation (MD, –13.54 mg [morphine equivalent]; 95% CI, –14.57 to –12.5; moderate quality). However, the four RCTs included diverse opioids as baseline treatment: fentanyl (96, 97), oxycodone (98), and tramadol (99), which may limit the applicability of results. Across the two postsurgical trials, both time to extubation (MD, +0.36 hr; 95% CI, –0.7 to +1.43; low quality) and ICU LOS (MD, –0.04 d; 95% CI, –0.46 to +0.38; low quality) were similar between the neuropathic and nonneuropathic medication groups (99). The Guillain-Barré syndrome population is considered by neurologists to be one of the best populations to evaluate neu- ropathic pain medication efficacy (among the larger popula- tion of ICU patients who might have neuropathic pain). The existence of limited data and potential drawbacks to neuro- pathic pain medication use are distinct in the much larger population of cardiovascular surgical patients; our recommen- dation focuses on opiate exposure reduction in patients who, in most cases, do not have neuropathic pain. The quality of evidence for the postcardiac surgery recommendation was low due to issues related to risk of bias and imprecision (98). Panel members estimated that neuropathic agents had negligible costs and were widely available although the possible sedative and cognitive effects of these agents could preclude their use in some patients. These drugs require the ability for patients to swallow or have enteral access. Lidocaine. Question: Should IV lidocaine be used as an adjunct to an opioid (vs an opioid alone) for pain management in critically ill adults? Recommendation: We suggest not routinely using IV lido- caine as an adjunct to opioid therapy for pain management in critically ill adults (conditional recommendation, low quality of evidence). Rationale: One single-center, double-blind RCT of 100 car – diac surgery patients requiring a postoperative ICU stay found that lidocaine (1.5 mg/kg IV bolus × 1 over 10 min at the time of surgery followed by an IV infusion of 30 µg/kg /min for 48 hr) versus placebo did not affect patient’s self-reported pain intensity; postoperative fentanyl or sedative consumption, time to extubation; nor ICU and hospital LOS when compared with placebo (100). This study had a high risk of bias related to selection bias and a lack of intention-to-treat analysis. Evidence from non-ICU studies helped support this recom- mendation. A meta-analysis assessing the improvement of anal- gesia and opioid-related side effects in non-ICU postoperative patients reported only low-to-moderate quality evidence that adjunctive lidocaine, when compared with placebo, decreased postoperative pain intensity scores after abdominal surgery. It did not find an improvement with lidocaine use for objective outcomes like time to first spontaneous bowel movement after surgery. It did not evaluate the important safety concerns asso- ciated with lidocaine use (101). Although the use of IV lido- caine infusions as adjunctive medication is discouraged for the general ICU population, individual patients and certain surgi- cal ICU cohorts may benefit from this intervention. Of note, the influence of IV lidocaine infusion dose and duration and inter – patient pharmacokinetic variability on the risk that neurologic and cardiac toxicity will occur in the ICU population remains unclear. At this time, concerns about safety outweigh the theo- retical benefits of its use in the general adult ICU population. NSAIDs. Question: Should a COX-1–selective NSAID be used as an adjunct to an opioid (vs an opioid alone) for pain management in critically ill adults? Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e833 Recommendation: We suggest not routinely using a COX- 1–selective NSAID as an adjunct to opioid therapy for pain management in critically ill adults (conditional recommenda- tion, low quality of evidence). Rationale: Two single-center RCTs, one including 120 post- cardiac surgery ICU patients in four parallel groups (adjunctive 75 mg diclofenac, 100 mg ketoprofen, 100 mg indomethacin, or placebo) (102) and one including 43 postabdominal surgery ICU patients in two parallel groups (adjunctive 100 mg ketoprofen or placebo) (103), evaluated the role of COX-1–selective NSAIDs for postoperative ICU pain control. Pooled analysis demonstrated that NSAIDs nonsignificantly reduced pain intensity at rest at 24 hours as measured by the 0–10 VAS or NRS (MD, –0.35 cm; 95% CI, –0.91 to +0.21; low quality). In one trial (103), pain intensity during deep inspiration—although significantly lower at 6 hours (MD, –1.3 cm; 95% CI, –2.36 to –0.24; moderate quality)—was not different at 24 hours (MD, –0.6 cm; 95% CI, –1.44 to +0.24; low quality). Pooled analysis showed a significant reduction of morphine consumption at 24 hours (MD, –1.61 mg [morphine equivalents]; 95% CI, –2.42 to –0.8; very low quality). Neither study reported a difference in nausea/vomiting between groups. No respiratory depression events were reported (103). NSAID-related side effects including acute kidney injury and excessive bleeding were not significantly different between the three NSAIDs and the placebo group. Both studies had a high risk of bias (102, 103). Given the perceived small ben- eficial effect balanced with serious potential safety concerns (e.g., bleeding and kidney injury), particularly when NSAIDs are administered for multiple doses, the panel members rec- ommend against routine use of NSAIDs along with opioids for nonprocedural pain management in critically ill adults. As with most conditional recommendations, the panel felt that there are likely patients—and perhaps even cohorts of patients—who may benefit from NSAIDs. No RCT evaluating a COX-2–specific NSAID (e.g., celecoxib) in critically ill adults was identified; thus, the role of these agents remains unclear. Evidence Gaps: All adjunctive nonopioid analgesics (when used in the context of multimodal analgesia) require larger sized studies in critically ill adults that are designed to clearly evaluate their opioid-sparing properties and their ability to reduce opioid-related side effects (104). The outcomes asso- ciated with opioid safety concerns such as ileus, duration of mechanical ventilation, immunosuppression, healthcare- associated infections, delirium, and both ICU and hospital LOS must be evaluated carefully. The risks of using nonopi- oid-adjunctive medications for analgesia in a population at increased risk for adverse drug effects need to be better defined. This includes analysis of liver and renal toxicities secondary to acetaminophen (all routes), hemodynamic instability second- ary to IV acetaminophen (85), risk of bleeding secondary to non-COX-1–selective NSAIDs, delirium, and neurotoxicity associated with ketamine (105), and hemodynamic alterations with IV lidocaine (100). The optimal dose and route of admin- istration for these nonopioids in critically ill patients need to be investigated, and studies should be conducted in the criti- cally ill medical patients unable to self-report pain. Finally, the role for the use of different opioid-adjunctive medications in combination needs to be evaluated. Summary of Pharmacologic Adjuvants to Opioid Ther – apy . The panel generally supports the utilization of multi- modal pharmacotherapy as a component of an analgesia-first approach to spare and/or minimize both opioids and seda- tives. A multimodal analgesia strategy is likely to improve pain control, reduce opioid consumption, and improve patient- centered outcomes. In patients for whom the risk of these nonopioid-adjunctive medications favors their exclusion, the several nonpharmacologic strategies (described below) pro- vide an opportunity to minimize opioid consumption. Protocols mandating systematic assessments with validated pain and sedation scales consistently reduced the consumption of opioids and sedatives (3, 106–111). Studies aiming to evaluate an improvement in systematic pain assessment with validated scales evaluated cohorts in whom the use of nonopioid multi- modal pharmacotherapy was significantly higher (106, 110). Daily sedation interruption can also be a useful intervention at reducing opioid consumption, provided proper assessment of pain precedes it (112). Music and massage, as recommended in these guidelines, have also been shown to reduce opioids (113– 117). Selected adjunctive agents should be both patient specific (e.g., minimizing acetaminophen use with liver dysfunction or high doses of gabapentin with renal dysfunction) and symptom specific (e.g., use of ketamine in surgical ICU patients at high risk of opioid side effects) to improve pain scores, decrease opioid consumption, minimize new adverse effects, and reduce poly- pharmacy (Supplemental Fig. 2 [Supplemental Digital Content 9, http://links.lww.com/CCM/D767] summarizes a pharmaco- logic strategy to decrease opioid consumption in the ICU). Pharmacologic Interventions to Reduce Procedural Pain Bedside procedures in the ICU can include regular activities (e.g., turning) and discrete procedures (e.g., arterial catheter inser – tion). Pain should be assessed and appropriately treated before a procedure to prevent more intense pain during the procedure. The 2013 guidelines recommended that preemptive analgesia and/or nonpharmacologic interventions (e.g., relaxation) be administered to alleviate pain in adult ICU patients before CTR and suggest these interventions before other procedures (1). Opioid Use and Dose. Questions: Should an opioid (vs no opioid) be used for criti- cally ill adults undergoing a procedure? Should a high-dose opioid (vs a low-dose opioid) be used for critically ill adults undergoing a procedure? Recommendation: We suggest using an opioid, at the low- est effective dose, for procedural pain management in criti- cally ill adults (conditional recommendation, moderate level of evidence). Remarks: The same opioids (i.e., fentanyl, hydromorphone, morphine, and remifentanil) that are recommended in the 2013 guidelines to manage pain should also be considered when an opioid is deemed to be the most appropriate pharma- cologic intervention to reduce procedural pain (1). Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e834 www.ccmjournal.org September 2018 • Volume 46 • Number 9 Rationale: Three small RCTs tested the relative effectiveness of different doses of opioids administered before turning and CTR. Cardiac surgery patients in a high-dose remifentanil group versus a low-dose remifentanil group had significantly lower CTR pain (118). However, in a second study, when high-dose versus low-dose morphine was administered before turning or CTR (when steady-state morphine serum concentrations had not been reached), no significant differences in procedural pain scores were seen (119); however, procedural pain scores were low in both groups. Pooled analysis comparing high-dose versus low- dose opioids for periprocedural pain management demonstrated a small reduction in the 0–10 NRS pain score with high-dose opioid use (standard mean difference [SMD], –0.26 cm; 95% CI, –0.94 to +0.42; low quality); however, conclusions are limited given the differing results between individual studies. In a third study, medical-surgical ICU patients who received IV fentanyl versus placebo before turning had a significantly lower score on the BPS (120). The potential for harm with opioids, in a dose- dependent proportion, was demonstrated. Two of 20 patients in the high-dose remifentanil group had 1–3 minutes of apnea, requiring bag and mask ventilation for 3 minutes (118), whereas 10% of patients in another study who were administered high- dose fentanyl (at a dose of 1–1.5 µ g/kg) experienced respiratory depression (120). Given this short-term consequence of higher dose opioids in critically ill patients, as well as the effectiveness of small doses of opioids in the three studies in maintaining low pain levels, opioids at the lowest effective doses for procedural pain are favored. Timing opioid administration so that the opi- oid’s peak effect coincides with the procedure is important. Local Analgesia/Nitrous Oxide. Questions: Should local analgesia (vs an opioid) be used for critically ill adults undergoing a procedure? Should nitrous oxide (vs an opioid) be used for critically ill adults undergoing a procedure? Recommendation: We suggest not using either local anal- gesia or nitrous oxide for pain management during CTR in critically ill adults (conditional recommendation, low quality of evidence). Rationale: Only one RCT tested the effects of subcutaneous infiltration of 20 mL of 0.5% bupivacaine around a mediastinal CTR site versus inhaled 50% nitrous oxide and oxygen after car – diac surgery (121). Patients in the bupivacaine (vs 50% nitrous oxide and oxygen) group had significantly lower CTR pain scores; however, the quality of evidence was low. Despite a signal of benefit, the feasibility of subcutaneous bupivacaine use in the ICU is challenging, given that it can only be administered by a qualified clinician. A lack of data to support the use of lower risk local anesthetics like lidocaine, able to be administered by a wider range of clinicians, also influenced the panel’s recommendation. Volatile Anesthetics. Question: Should an inhaled volatile anesthetic (vs no use of this agent) be used for critically ill adults undergoing a procedure? Recommendation: We recommend not using inhaled vola- tile anesthetics for procedural pain management in critically ill adults (strong recommendation, very low quality of evidence). Rationale: Isoflurane, a volatile anesthetic, is traditionally used for general anesthesia. It has a relatively rapid onset and recovery and has demonstrated cardioprotective effects such as preserved mitochondrial oxygen consumption, troponin release, and myocardial infarction (122). Little is known of the analgesic effects of isoflurane for periprocedural pain in ICU patients. No RCTs comparing isoflurane to a control intervention (e.g., opioid alone) were found. One small double-blinded RCT tested the relative effectiveness of nitrous oxide 50% and oxygen combined with isoflurane versus inhaled nitrous oxide 50% and oxygen alone for CTR in patients after uncomplicated cardiac surgery (123). Nitrous oxide 50% and oxygen along with isoflurane inhalation were more effective for pain related to the first of two chest tubes removed. However, removal of the second chest tube was more painful, regardless of the gas inhaled. Although the study showed a potential for benefit, we do not recommend this intervention because the study failed to consider the CTR time relative to the gas administration time; the very low quality of evidence available (imprecision [a small sample size and only one study] and indirectness [only cardiac surgery patients]); the increased resources needed for use of gases in the ICU; and in some centers, safety issues related to the use of volatile anesthetics outside the operating room. NSAIDs. Question: Should an NSAID administered IV, orally, and/or rectally (vs an opioid) be used for critically ill adults undergo- ing a procedure? Recommendation: We suggest using an NSAID administered IV, orally, or rectally as an alternative to opioids for pain man- agement during discrete and infrequent procedures in criti- cally ill adults (conditional recommendation, low quality of evidence). Rationale: In a randomized double-blind study (124), the effects of two types of analgesics with different mechanisms of action were tested on CTR pain: a single 4-mg dose of IV morphine (an opioid) or a single 30-mg dose of IV ketorolac (a non-COX-1–specific NSAID). Procedural pain intensity scores did not differ significantly among the groups, although pain intensity was mild in both groups and the quality of evidence was limited by imprecision (small number of patients). Question: Should an NSAID topical gel (vs no use of NSAID gel) be used for critically ill adults undergoing a procedure? Recommendation: We suggest not using an NSAID topi- cal gel for procedural pain management in critically ill adults (conditional recommendation, low quality of evidence). Rationale: Topical valdecoxib is an NSAID gel. Use of a topical analgesic rather than an IV NSAID or opioid or local anesthetic injection could be less demanding on available nursing resources (125). One randomized double-blind study in postcardiac surgery patients tested the efficacy of topical valdecoxib 50-mg placebo gel (vs a paraffin gel) applied to the skin surrounding a chest tube before CTR (125). Patients who received the NSAID gel had less CTR pain than those who received the paraffin control gel. However, the panel made a Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e835 conditional recommendation against the use of NSAID gel for procedural pain management given concerns about the qual- ity of this study and the high acquisition cost of NSAID gel product in some countries that may make their use prohibitive. Evidence Gaps: Future studies are warranted to test the effec- tiveness of various types and doses of opioids in larger sample of patients during different procedures while attending to the patients’ preprocedural pain, particularly in a context where opioid exposure may be undesirable. Studies of procedural pain interventions should avoid risk of bias through use of control groups, allocation concealment, and blinding. Generalizability of study findings can be improved by including heterogeneous samples of ICU patients undergoing the same procedure and also patients admitted to the ICU with a known opioid use disorder. Much procedural pain research has used CTR as the paradigm procedure, most likely because the research protocol can be standardized more easily than with other procedures and because CTR represents a painful ICU procedure that fre- quently occurs after cardiac surgery. The degree to which data from CTR studies can be extrapolated to other ICU procedures likely to be associated with pain remains unclear. Nonpharmacologic Interventions to Reduce Pain Cybertherapy/Hypnosis. Questions: Should cybertherapy (virtual reality [VR]) (vs no use of cybertherapy) be used for pain management in critically ill adults? Should hypnosis (vs no use of hypnosis) be used for pain management in critically ill adults? Recommendation: We suggest not offering cybertherapy (VR) or hypnosis for pain management in critically ill adults (conditional recommendation, very low quality of evidence). Rationale: Cybertherapy is a VR distraction postulated to reduce postoperative pain and distress in the ICU. A set of five simulated environments was displayed to the patient for 30 minutes before and after surgery (126). Hypnosis was admin- istered by a trained ICU nurse in alert ICU patients and was induced using the cenesthesic approach (i.e., patient attention focused on any body sensation) or carried out on the actual symptom (pain or anxiety) (127). One study evaluated 67 postcardiac surgery ICU patients before and after the cyber – therapy intervention (126). Most (88%) reported a decreased level of postoperative pain (MD, –3.75 cm on the 0–10 VAS) that corresponded to a change from “severe to moderate” to “moderate to light” pain. Although risk of bias was minimal, imprecision (small sample size), failure to use a validated pain intensity scale, and the methodologic limitations inherent to observational studies led to an overall very low quality of evidence. Also, many factors related to resources (equipment, time, ICU environment, and training) make this intervention possibly infeasible to implement. Therefore, the panel suggests that clinicians not use cybertherapy for pain management in critically ill adults. Hypnosis was evaluated with 23 burn ICU patients com- pared with 23 matched historical controls (127). The first ICU hypnosis session occurred at a median of 9 days (0–20 d) after injury, and an adequate level of hypnosis was obtained, on average, after 15 minutes. On the day after hypnosis, repeated pain assessments (up to 12) found that hypnosis was associated with a reduction in the 0–10 VAS (MD, –0.5 cm; 95% CI, –1.37 to +0.37; very low quality). Opioid consumption was reduced compared with historical controls. Within the intervention group, opioid consumption was lower in patients who received hypnosis at admission to the ICU compared with those who did not. The risk of bias was judged to be very serious due to poorly evaluated outcomes, variability on assessment time points, cointerventions between groups, and unclear ascertain- ment of exposure. Due to high risk of bias and the imprecision associated with the observational data, the overall quality of evidence was very low. Many factors (resources, ICU environ- ment, extensive training, and patient acceptability) make this option possibly unfeasible to implement. Therefore, the panel issued a conditional recommendation against the use of hyp- nosis for pain management in critically ill adults. Massage. Question: Should massage (vs no massage) be used for pain management in critically ill adults? Recommendation: We suggest offering massage for pain management in critically ill adults (conditional recommenda- tion, low quality of evidence). Remarks: Massage interventions varied in session time (10– 30 min), frequency (once or bid), duration (for 1–7 d), and body area (back, feet and hands, or only hands). Rationale: Massage for postoperative ICU pain management in cardiac and abdominal surgery patients (n = 751 and 265, respectively) was investigated in five RCTs (65, 117, 128–130) ( Supplemental Table 7, Supplemental Digital Content 10, http://links.lww.com/CCM/D768). The comparator arms were different across studies and included standard care (117, 129, 130), attention (129, 130), or sham massage (i.e., hand hold- ing) (65). Pooled analysis showed a reduction in pain intensity scores (0–10 VAS or NRS scale) with massage use on the first day after it was provided (MD, –0.8 cm; 95% CI, –1.18 to –0.42; low quality). Repetitive administration of massage seemed to reduce pain intensity scores with MDs varying from –0.3 to –1.83 cm from day 1 to day 5 (after patients were discharged from the ICU). The overall quality of evidence was low due to risk of bias and imprecision. No adverse events were reported in relation to the administration of massage in the included stud- ies. Resources varied across studies in which nurses or massage therapists provided the intervention. Minimal training (3–6 hr) was provided to nurses. The panel felt that feasibility of using massage for ICU pain management would depend on the inter – vention duration and resources needed, which could affect cost. Music. Question: Should music therapy (vs no music therapy) be used for pain management in critically ill adults to relieve both procedural and nonprocedural pain? Recommendation: We suggest offering music therapy to relieve both nonprocedural and procedural pain in critically ill adults (conditional recommendation, low quality of evidence). Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e836 www.ccmjournal.org September 2018 • Volume 46 • Number 9 Rationale: Among the studies evaluated, music interven- tions varied in music type (participant’s choice from a prese- lection of music or harp live music), duration (10–45 min), and pain management purposes (procedural or nonprocedural) in the evaluated studies. Participants were provided with headsets to listen to music except in one study where live harp music was played in the ICU room (116). Music interventions were administered once in most studies except in two studies in which participants received the music intervention during two turning procedures (115), and once daily up to a maximum of 3 days (117) (Supplemental Table 8, Supplemental Digital Content 11, http://links.lww.com/CCM/D769). Effectiveness of music was tested for procedural pain man- agement in three RCTs during different procedures including CTR in 156 cardiac surgery ICU adults (113), C-clamp proce- dure after percutaneous coronary interventions in 66 patients (114), and during two turning procedures in postoperative ICU patients (115). The comparator arms were different across studies and included standard care and white noise (113), headsets attached to a CD player without music (115), or a rest period (114). Pooled analysis showed that music therapy reduced pain intensity (0–10 NRS) (MD, –0.52 cm; 95% CI, –1.49 to +0.45; low quality). For nonprocedural pain management, effectiveness of music was tested in four studies including three RCTs with a total of 434 medical or surgical ICU patients (12, 116, 117, 131) and a pre/posttest observational study with 87 cardiac surgery ICU patients (132). The comparator arms included standard care (117) or a rest period (116, 131). Pooled analysis showed that music reduced pain intensity (0–10 NRS) (MD, –0.66 cm; 95% CI, –0.89 to –0.43; low quality). These reductions in pain inten- sity for both procedural and nonprocedural pain management were not considered to be clinically significant. However, the potential for benefit outweighed any signal for harm or resource requirements. One large RCT that found that personal-directed music therapy reduces anxiety and sedative use in critically ill adults was not included in the evidence profile for this question because it did not report pain assessments (133). The quality of evidence of included studies was deemed to be low (nonprocedural pain management) to very low (pro- cedural pain management) due to risk of bias and the incon- sistency in the reported results between studies. There were no reported adverse events related to music therapy. However, nine participants did not complete the music intervention in two studies because they disliked music or removed their headsets (114, 131). The panel felt that music is a safe interven- tion for pain management, but the patient’s preference should be considered. Feasibility was raised as an issue by the panel depending on the resources needed for its implementation including professionals (e.g., musician and music therapist) and equipment (e.g., purchase of music and headsets). Storage room and hygiene measures must also be considered. Cold Therapy. Question: Should cold therapy (vs no use of cold therapy) be used for critically ill adults undergoing a procedure? Recommendation: We suggest offering cold therapy for pro- cedural pain management in critically ill adults (conditional recommendation, low quality of evidence). Remarks: Cold ice packs were applied for 10 minutes, and wrapped in dressing gauze, on the area around the chest tube before its removal. Rationale: Cold therapy for periprocedural pain manage- ment during CTR was investigated in two RCTs (n = 130 total) in postcardiac surgery ICU patients (134, 135). In one study, the effects of cold therapy were compared with usual care (i.e., oral acetaminophen every 6 hr) (n = 40 per group) (134), whereas in the other, a placebo tap water pack (n = 25 per group) was used as the comparator (135). Although a pooled analysis of stud- ies demonstrated a nonsignificant reduction in pain intensity (0–10 NRS) with cold therapy (MD, –1.91 cm; 95% CI, –5.34 to +1.52; low quality), the panel considered that a reduction of this magnitude on the NRS scale was clinically important and consistent with meaningful acute pain reductions (1.3–2.4 cm) as defined in one study of 700 postsurgical patients (136). Although only CTR was investigated in a homogeneous group of postcardiac surgery patients, the panel felt that this recommendation was generalizable to other procedures and for use in other critically ill populations. No mention of pos- sible undesirable effects related to the use of cold therapy appeared in the included literature; however, the panel agreed that these are likely to be trivial (unless the clinician forgets to remove the cold pack after CTR). Adequate room in the ICU freezer and a written protocol for use of this intervention will be required. Simple, inexpensive, and widely available inter – ventions like cold therapy can be used frequently in resource- poor areas where medications may not be available. Relaxation Techniques. Question: Should relaxation techniques (vs no use of relax- ation techniques) be used for critically ill adults undergoing a procedure? Recommendation: We suggest offering relaxation techniques for procedural pain management in critically ill adults (condi- tional recommendation, very low quality of evidence). Remarks: The relaxation technique used in each study differed. Rationale: Relaxation techniques related to breathing were tested for procedural pain management and timed with opioid administration during CTR in two different matched control studies evaluating a total of 88 postcardiac surgery ICU patients (137, 138). In one study (137) (in which the rapidly adminis- tered relaxation technique consisted of instructing the patient to inhale and hold their breath for a moment; to breathe out and go limp as a rag doll; and then to start yawning), the chest tube(s) were removed at the end of the yawn. In the second study (138), patients were taught breathing exercises that included inhaling slowly through the nose and exhaling slowly through pursed lips. Patients were encouraged to complete these exercises either with their eyes closed or to focus on an object in the room. Breathing exercises were initiated 5 minutes before CTR and continued during chest tube dressing, sutures, and tube removal. Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e837 Pooled analysis showed a mean reduction in pain intensity (0–10 VAS) 15–30 minutes after CTR (MD, –2.5 cm; 95% CI, –4.18 to –0.82; very low quality). A reduction of this magni- tude is clinically important (136). However, the quality of evi- dence was deemed to be very low due to the imprecision (small sample sizes) and the risk of bias. Although a breathing-focused relaxation technique was evaluated in a relatively homogeneous group of patients during only one type of painful procedure, the panel felt that this recommendation was generalizable to other painful procedures and other critically ill populations. Possible undesirable effects related to relaxation were not men- tioned in the included studies, and the panel felt that these were unlikely to occur. The panel agreed that minimal resources and training were needed to provide this intervention safely and efficiently. Therefore, relaxation using breathing techniques appears feasible to implement and acceptable to stakeholders. Written information could also be provided to patients to help familiarize them with relaxation techniques. Evidence Gaps: The effects of nonpharmacologic interven- tions in critically ill adults unable to self-report remain unknown. The role of a family member in the delivery of some interven- tions (e.g., relaxation, massage, and music) could be explored. Whether music’s coanalgesic effect depends on patient’s musi- cal preferences should be considered. Interventions to reduce procedural pain should be evaluated during procedures other than CTR. Implementation studies documenting the feasibil- ity and associated costs related to the use of these interventions are also needed. Studies to determine the effect of relaxation techniques on other outcomes such as sleep are also required. Protocol-Based Pain Assessment and Management Question: Should a protocol-based (analgesia/analgosedation) pain assessment and management program be used in the care of critically ill adults when compared with usual care? Good Practice Statement: Management of pain for adult ICU patients should be guided by routine pain assessment and pain should be treated before a sedative agent is considered. Recommendation: We suggest using an assessment-driven, protocol-based, stepwise approach for pain and sedation man- agement in critically ill adults (conditional recommendation, moderate quality of evidence). Remarks: For this recommendation, analgosedation is defined as either analgesia-first sedation (i.e., an analgesic [usually an opioid] is used before a sedative to reach the seda- tive goal) or analgesia-based sedation (i.e., an analgesic [usu- ally an opioid] is used instead of a sedative to reach the sedative goal). The implementation of this recommendation infers that institutions should have an assessment-driven protocol that mandates regular pain and sedation assessment using validated tools, provides clear guidance on medication choice and dos- ing, and makes treating pain a priority over providing sedatives. Rationale: The five outcomes deemed critical to the rec- ommendation include pain intensity, medication exposure (analgesics/sedatives), adverse events, duration of mechani- cal ventilation, and ICU LOS (5, 106–110, 127, 139–156) (Supplemental Table 9, Supplemental Digital Content 12, http://links.lww.com/CCM/D770). Pooled analysis suggests that a protocol-based (analgesia/analgosedation) pain and sedation assessment management program compared with usual care does not affect the incidence of nosocomial infec- tion, constipation, hypotension, bradycardia, or opioid expo- sure, but does reduce sedative requirements (SMD, –0.57; 95% CI, –0.84 to –0.31; low quality), duration of mechani- cal ventilation (MD, –1.26 d; 95% CI, –1.8 to –0.73; moder – ate quality), ICU LOS (MD, –2.27 d; 95% CI, –2.96 to –1.58; moderate quality), and pain intensity (0–10 VAS or NRS) (MD, –0.35 cm; 95% CI, –0.22 to –0.49; low quality). Panel members issued a conditional recommendation because the benefits of a protocol-based approach were not observed across all critical outcomes. Evidence Gaps: To be able to generate strong recommen- dations for the use of a protocol-based analgesia/analgoseda- tion program, future randomized studies must be completed that address the following questions: 1) what is the optimal opioid, or other analgesic, to use in the protocol? 2) what ICU setting or patient population is most appropriate for the use of such a protocol? 3) what are the potential ben- efits of such protocols based on their ability to reduce pain or avoid the use of potentially harmful effects of sedatives? and 4) what are the potential safety concerns associated with such protocols (e.g., opioid withdrawal, posthospital opioid use disorder)? AGITATION/SEDATION Sedatives are frequently administered to critically ill patients to relieve anxiety, reduce the stress of being mechanically ven- tilated, and prevent agitation-related harm (1). These medi- cations may predispose patients to increased morbidity (157, 158). The healthcare provider must determine the specific indication for the use of sedatives. If a sedative is needed, the patient’s current sedation status should be assessed and then frequently reassessed using valid and reliable scales (158–161). In critically ill patients, unpredictable pharmacokinetics and pharmacodynamics secondary to drug interactions, organ dys- function, inconsistent absorption and protein binding, hemo- dynamic instability, and drug accumulation can lead to adverse events (1, 162, 163). The 2013 guidelines (1) suggested targeting light levels of sedation or using daily awakening trials (112, 164–166), and minimizing benzodiazepines (167) to improve short-term out- comes (e.g., duration of mechanical ventilation and ICU LOS). In addition, sedation delivery paradigms and the specific seda- tive medication used can have an important impact on post- ICU outcomes including 90-day mortality physical functioning, neurocognitive, and psychologic outcomes. These issues have been evaluated in the present guidelines through three action- able and three descriptive questions. (A prioritized topic list is in Supplemental Table 10 [Supplemental Digital Content 13, http://links.lww.com/CCM/D771], and voting results appear in Supplemental Table 11 [Supplemental Digital Content 14, http:// links.lww.com/CCM/D772].) The evidence summaries and evidence-to-decision tables used to develop recommendations Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e838 www.ccmjournal.org September 2018 • Volume 46 • Number 9 for the agitation (sedation) group are available in Supplemental Table 12 (Supplemental Digital Content 15, http://links.lww. com/CCM/D773), and the forest plots for all completed meta- analyses are available in Supplemental Figure 3 (Supplemental Digital Content 16, http://links.lww.com/CCM/D774). Light Sedation Question: Does light sedation (vs deep sedation), regardless of the sedative agent(s) used, significantly affect outcomes in critically ill, mechanically ventilated adults? Recommendation: We suggest using light sedation (vs deep sedation) in critically ill, mechanically ventilated adults (con- ditional recommendation, low quality of evidence). Rationale: The 2013 PAD guidelines made an ungraded statement that maintaining a light level of sedation will shorten time to extubation and reduce ICU LOS (1). Although the prior guideline defined light sedation as a RASS scale score of greater than or equal to –2 and eye opening of at least 10 minutes (112), this level of sedation is probably deeper than required for management of mechanically ventilated adults in an ICU. No universally accepted definition of light sedation exists. To address this question, we evaluated studies in which light versus deep sedation were defined a priori, measured, and explicitly reported with objective scales describing whether patients met these clear light, versus deep, sedation targets systematically over the time spent in the ICU and at least q6h. Surrogate measures (e.g., sedative plasma levels) or subjective clinical assessments of wakefulness were not considered as part of the definition of level of sedation. Studies describing a daily spontaneous awak- ening trial (SAT) were not deemed indicative of a light seda- tion approach because they reported lightening of sedation at a single point in time, rather than over the entire day. For studies that used scales, such as the RASS (159), a RASS score of –2 to +1 range (or its equivalent using other scales) was considered as light sedation in the evaluated studies. Eight RCTs satisfied our research criteria (156, 168–174). We evaluated the effect of light versus deep sedation on outcomes that were considered critical by the sedation group and patient representatives: 90-day mortality, time to extubation, delir – ium, tracheostomy, cognitive and physical functional decline, depression, and posttraumatic stress disorder (PTSD). The outcomes evaluated were mostly measured after ICU discharge and are different from the short-term outcomes assessed in the 2013 guideline ungraded descriptive question. Light sedation was not associated with 90-day mortality (RR, 1.01; 95% CI, 0.80–1.27; moderate quality) (168, 169), but it was associated with a shorter time to extubation (MD, –0.77 d; 95% CI, –2.04 to –0.50; low quality) (168–170) and a reduced tracheostomy rate (RR, 0.57; 95% CI, 0.41–0.80; low quality) (170, 171). Light sedation was not associated with a reduction in the incidence of delirium (RR, 0.96; 95% CI, 0.80–1.16; low quality) (168, 172), PTSD (RR, 0.67; 95% CI, 0.12–3.79; low quality) (156, 174), depression (RR, 0.76; 95% CI, 0.10–5.58; very low qual- ity) (156, 170), or self-extubation (RR, 1.29; 95% CI, 0.58–2.88; low quality) (168–170, 173). No RCTs evaluated the impact of light versus deep sedation on cognitive or physical functioning. The overall quality of the body of evidence was low. Both the magnitude of reduction in time to extubation and tracheos- tomy rate were considered small; the magnitude of harm asso- ciated with self-extubation was uncertain. We initially evaluated the data from RCTs and then reviewed observational studies related to outcomes where the RCT data were of low quality. Observational trials suggested benefits in reduced risk of death at 90 days and time to extubation, but not in delirium outcomes (166, 175, 176). One recent cohort study not considered in the guideline evidence demonstrates that sedation intensity (sum of negative RASS measurements by number of assessments) independently, in an escalating dose-dependent relationship, predicts increased risk of death, delirium, and delayed time to extubation (177). The amount of sedation preferred by patients is likely variable; some patients or families may prefer deeper sedation, but this preference may not be considered appropri- ate by clinicians given the adverse outcomes associated with deep sedation. Uncertainty about the cost-effectiveness of light sedation was considered. Light sedation was considered likely acceptable to clinicians and patients and feasible to implement. Evidence Gaps: Despite the wide use of validated sedation scales, no consensus on the definition of light, moderate, and deep sedation is available. Further exploration of the concept of wakefulness and light sedation is required. The relationship between changing levels of sedation and their duration over the course of the ICU stay and clinical outcomes is also unknown. The effect of depth of sedation on post-ICU, patient-centered outcomes such as 90-day all-cause mortality and cognitive function, physical recovery, PTSD, anxiety, and depressive symptoms has not been well evaluated in RCTs. There is also a dearth of information regarding the interaction among seda- tive choice, sedation depth, and the patient-specific factors that affect this relationship. Finally, as outlined elsewhere in these guidelines, the relationship between level of sedation and the ability to evaluate, pain, delirium, and sleep has not been fully elucidated. Daily Sedative Interruption/Nurse-Protocolized Sedation Question: In critically ill, intubated adults, is there a differ – ence between daily sedative interruption (DSI) protocols and nursing-protocolized (NP)-targeted sedation in the ability to achieve and maintain a light level of sedation? Ungraded Statement: In critically ill, intubated adults, DSI protocols and NP-targeted sedation can achieve and maintain a light level of sedation. Remarks: A DSI or a SAT is defined as a period of time, each day, during which a patient’s sedative medication is discon- tinued and patients can wake up and achieve arousal and/or alertness, defined by objective actions such as opening eyes in response to a voice, following simple commands, and/or hav- ing a Sedation-Agitation Scale (SAS) score of 4–7 or a RASS score of –1 to +1. NP-targeted sedation is defined as an estab- lished sedation protocol implemented by nurses at the bedside to determine sedative choices and to titrate these medications to achieve prescription-targeted sedation scores. Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e839 Rationale: Five randomized, prospective, unblinded trials compared DSI protocols and NP-targeted sedation to usual care (178–182) (Supplemental Table 13, Supplemental Digital Content 17, http://links.lww.com/CCM/D775). Some studies compared DSI to “usual care,” defined as an NP protocol. Most studies did not specifically target or assess how effectively either technique achieved light level of sedation; rather, they evaluated the differences in the overall sedation scores among patients being managed with DSI or NP-targeted sedation. Across the five studies, a total of 739 patients were randomized (DSI, n = 373; NP, n = 366). Benzodiazepines were commonly prescribed for sedation in both groups, often paired with opioids for anal- gesia. Two studies reported no difference in level of sedation achieved between DSI and NP-targeted sedation (178, 179). The remaining studies appear contradictory; one noted higher RASS with DSI versus NP-targeted sedation (180), another noted lower median SAS scores with DSI versus NP-targeted sedation, but no difference in the percentage of time spent in the targeted light sedation range (181). A third study reported lighter sedation with DSI than with NP-targeted sedation (182). As outlined in these guidelines, clinicians should target a light rather than deep level of sedation in their intubated, criti- cally ill adult patients unless deeper sedation is clinically indi- cated. Our literature review suggests that both DSI protocols and NP-targeted sedation are safe and no differences exist between them in achieving and maintaining a light level of sedation. There are, however, some important caveats: first, most studies evaluat- ing DSIs and NP have done so in the context of sedation with benzodiazepines, which are no longer recommended for sedation in critically ill patients; second, DSI protocols may be associated with increasing nursing workload (179); and third, a brief DSI should not be used to justify the use of deep sedation for the rest of the day when it is not indicated. Because light levels of sedation are associated with improved outcomes and are needed to facili- tate other interventions such as spontaneous breathing trials and early mobilization, healthcare providers should strive to achieve light levels of sedation in the majority of patients the majority of the time. Light sedation, assessed using a validated sedation scale, can be achieved either using a NP or through DSI protocols (where light sedation is targeted, whereas sedatives are infusing). Evidence Gaps: Variability in nursing sedation assessment frequency and its reporting, and modality of sedative admin- istration (infusion vs bolus) differ among institutions. The most frequent sedative choice (benzodiazepines) described in the studies may not reflect current practice. Patient and fam- ily preferences and education as to depth of sedation within a “light sedation” range should also be considered. Nonetheless, future research should focus on the effect of sedation level on patient-centered outcomes. Choice of Sedative Critically ill adults may require sedation to reduce anxiety and stress and to facilitate invasive procedures and mechanical ven- tilation. Sedation indication, goal, clinical pharmacology, and acquisition cost are important determinants in choosing a sed- ative agent. The 2013 PAD guidelines suggest (in a conditional recommendation) that nonbenzodiazepine sedatives (either propofol or dexmedetomidine) are preferable to benzodiaz- epine sedatives (either midazolam or lorazepam) in critically ill, mechanically ventilated adults because of improved short- term outcomes such as ICU LOS, duration of mechanical ventilation, and delirium (1). For the current guidelines, we considered both short-term and long-term outcomes as criti- cal for evaluation. These included time to extubation, time to light sedation, and delirium, and long-term outcomes such as 90-day mortality, cognitive and physical functioning, institu- tionalization, and psychologic dysfunction. Elective cardiac surgical patients are different from critically ill medical and surgical patients whose admission profile is sel- dom elective and whose ICU stay and mechanical ventilation duration are longer. We therefore separated studies describ- ing mechanically ventilated, routine cardiac surgical patients and critically ill, mechanically ventilated medical and surgi- cal patients. Pharmacogenomic factors that may influence the response of sedatives and other medications in the critically ill were reviewed (163). Cardiac Surgery Question: Should propofol, when compared with a benzodiaz- epine, be used for sedation in mechanically ventilated adults after cardiac surgery? Recommendation: We suggest using propofol over a benzo- diazepine for sedation in mechanically ventilated adults after cardiac surgery (conditional recommendation, low quality of evidence). Rationale: We identified eight RCTs: seven of which com- pared infusions of both sedative agents (183–189) and one RCT compared propofol infusions to midazolam boluses (190). In cardiac surgical patients, we considered a shortened time to light sedation of at least 30 minutes and time to extubation of at least 1 hour to be clinically significant. Two small RCTs (n = 70) reported shorter time to light sedation with propofol when compared with benzodiazepines (MD, –52 min; 95% CI, –77 to –26; low quality) (185, 186). Seven RCTs (n = 409), including one study using only benzodiazepine boluses reported shorter time to extubation with propofol versus a benzodiazepine (MD, –1.4 hr; 95% CI, –2.2 to –0.6; low quality) (183–189). We were unable to find RCTs comparing propofol and benzodiaz- epine effects on other critical outcomes in the cardiac surgical population. Overall, the panel judged that the desirable conse- quences of using propofol probably outweigh the undesirable consequences, and thus issued a conditional recommendation favoring propofol over a benzodiazepine. Medical and Surgical Patients Not Undergoing Cardiac Surgery Questions: Should propofol, when compared with a benzodi- azepine, be used for sedation in critically ill, mechanically ven- tilated adults? Should dexmedetomidine, when compared with a benzo- diazepine, be used for sedation in critically ill, mechanically ventilated adults? Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e840 www.ccmjournal.org September 2018 • Volume 46 • Number 9 Should dexmedetomidine, when compared with propofol, be used for sedation in critically ill, mechanically ventilated adults? Recommendation: We suggest using either propofol or dex- medetomidine over benzodiazepines for sedation in critically ill, mechanically ventilated adults (conditional recommenda- tion, low quality of evidence). Rationale: We evaluated the effect of propofol versus ben- zodiazepine, dexmedetomidine versus benzodiazepine, and propofol versus dexmedetomidine in three separate analyses for the outcomes deemed critical. In most studies, benzodiaze- pines were administered as continuous infusions and not inter – mittent boluses. We combined studies using midazolam and lorazepam. In critically ill, mechanically ventilated patients, a shortened time to light sedation of at least 4 hours and time to extubation of at least 8–12 hours (one nursing shift) were deemed clinically significant. Propofol Versus Benzodiazepines. Seven trials (n = 357) (191– 197) reported shorter time to light sedation with propofol when compared with a benzodiazepine (MD, –7.2 hr; 95% CI, –8.9 to –5.5; low quality). Nine trials (n = 423) (191, 196–202) reported shorter time to extubation with propofol compared with a ben- zodiazepine (MD, –11.6 hr; 95% CI, –15.6 to –7.6; low quality). Only one RCT assessed delirium and found no difference (196). No data were available for other critical outcomes. Although pro- pofol was associated with a higher risk of self-extubation (RR, 2.2; 95% CI, 0.30–26.45; low quality), reliable conclusions for this outcome cannot be made given the wide CI. Additionally, it was not clear if the self-extubations caused any harm (e.g., need for reintubation). Although this was an important consideration for the physicians on the sedation group panel, ICU patients might feel otherwise. Overall, the panel judged that the desirable con- sequences of using propofol probably outweighs the undesirable consequences, and thus issued a conditional recommendation favoring propofol over a benzodiazepine infusion. Dexmedetomidine Versus Benzodiazepines. Five RCTs ( n = 1,052) assessed duration of mechanical ventilation (167, 172, 202–204); three studies (n = 969) evaluated ICU LOS (167, 172, 203); and four RCTs (n = 1,007) evaluated delirium prevalence (167, 172, 203, 205). The study with the lowest risk of bias (n = 366), Safety and Efficacy of Dexmedetomidine Compared With Midazolam (SEDCOM), had the greatest benefit for the time to extubation (MD, –1.90 d; 95% CI, –2.32 to –1.48) and delirium (RR, 0.71; 95% CI, 0.61–0.83) with dexmedetomidine compared with a benzodiazepine infusion, and influenced how the evidence was graded when developing this recommendation (167). Although the study by Xu et al (205) also showed reduced delirium with dexmedetomidine use, and the Dexmedetomidine Versus Midazolam for Continuous Sedation in the ICU (MIDEX) study (203) demonstrated a shorter duration of mechanical ventilation with dexmedetomidine over a benzodiazepine infusion, pooled analysis of all evalu- ated studies did not show a significant benefit of dexmedeto- midine compared with a benzodiazepine infusion for duration of mechanical ventilation extubation (MD, –0.71 d; 95% CI, –1.87 to 0.45; low quality), ICU LOS (MD, –0.23 d; 95% CI, –0.57 to 0.11; low quality), and the risk for delirium (RR, 0.81; 95% CI, 0.60–1.08; low quality). Of note, the MIDEX study (203), in which delirium was assessed only once 48 hours after sedation discontinuation, showed no improvements in delir – ium prevalence with dexmedetomidine. The SEDCOM (167) and Maximizing the Efficacy of Sedation and Reducing Neurological Dysfunction (MENDS) (172) studies both demonstrated a greater incidence of bra- dycardia in the dexmedetomidine group; neither study found intervention was required for the bradycardia. Overall, the panel judged that the desirable consequences of using dexme- detomidine probably outweigh any undesirable consequences and thus issued a conditional recommendation favoring dex- medetomidine over a benzodiazepine. Propofol Versus Dexmedetomidine. Three RCTs (n = 850) assessed time to extubation and showed no difference in this out- come (202, 203, 206). No data were available for other critical outcomes. A single RCT, the Propofol Versus Dexmedetomidine for Continuous Sedation in the ICU (PRODEX) study, showed a decreased incidence of delirium with dexmedetomidine at the single time point of 48 hours after sedation cessation (203). Patients were able to communicate more effectively if sedated with dexmedetomidine when compared with propofol (203). No differences were reported in bradycardia or hypotension between patients sedated with propofol and dexmedetomidine (203). Overall, there was low quality evidence for the outcomes assessed, with a moderate benefit noted (reduced time to light sedation and extubation) when both propofol and dexmedeto- midine were compared with benzodiazepines. No important differences in outcomes were noted between propofol and dex- medetomidine. As reported in these studies, associated harm with either propofol or dexmedetomidine was deemed to be minimal and not clinically significant. The cost-effectiveness of these sedative regimens was uncertain as both propofol and dexmedetomidine acquisition costs are now lower than when they were initially studied. Additionally, the cost of acquisition of these agents varies widely in the world, making it difficult to generalize cost-effectiveness. Nevertheless, incorporating both propofol and dexmedetomidine into practice was likely accept- able and feasible. Recognizing that dexmedetomidine should not be used when deep sedation (with or without neuromuscular blockade) is required, panel members judged that the desirable and undesirable consequences of using propofol (vs dexmedeto- midine) were balanced; therefore, they issued a conditional rec- ommendation to use either agents for sedation of critically ill adults. Implementation will likely depend on the availability of the drug and its associated cost at individual institutions. Evidence Gaps: Larger, well-conducted studies assessing the critical outcomes we defined need to be undertaken. Faster extubation and increased hospital survival, though the build- ing blocks of long-term outcomes, no longer suffice as the sole descriptors of patient-centered outcomes. Improvements in many aspects of survivorship, including return to former qual- ity of life, independent function, and employment, are mean- ingful (207). Further studies evaluating the value of patient communication with family members during and after ICU Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e841 care and the perceptions of patients while on each of these sedatives are also needed; of note, our patient panel members described very different subjective experiences when receiving sedatives that could not be translated into guideline recom- mendation content. Pharmacokinetic and pharmacodynamic considerations should be incorporated in both sedative choice and delivery methods (162, 163). For example, the risks and benefits of an intermittent benzodiazepine administration strategy after establishing analgesia need to be studied against use of continuous sedative infusions. Benzodiazepine medi- cations still form the mainstay of therapy in resource-poor areas; risks and benefits need to be studied in the context of their cost. Additionally, the role of sedative medications in the context of an analgesia-first approach or to supplement anal- gosedation needs to be better studied. The role of benzodiaz- epines versus propofol or dexmedetomidine in patients who are hemodynamically unstable, need deep sedation, are at risk for delirium, or have signs of alcohol withdrawal needs to be studied. With increased propofol use, strategies to detect propofol-related infusion syndrome earlier are required and large-scale registry studies to characterize its prevalence and risks should be undertaken. The role of nonpharmacologic strategies to reduce agitation, anxiety, and distress in terms of sedative choice and requirements is uncertain, and thus, no recommendations could be made in this regard. Objective Sedation Monitoring Question: Are objective sedation monitoring tools (electroen- cephalogram-based tools or tools such as HR variability, actig- raphy, and evoked potentials) useful in managing sedation in critically ill, intubated adults? Ungraded Statements: Bispectral index (BIS) monitoring appears best suited for sedative titration during deep sedation or neuromuscular blockade, though observational data suggest potential benefit with lighter sedation as well. Sedation that is monitored with BIS compared with subjec- tive scales may improve sedative titration when a sedative scale cannot be used. Rationale: The literature for ICU-based studies of objec- tive monitoring tools for sedation consists primarily of reports for electroencephalogram-based tools (particularly the BIS). Few ICU-based studies evaluated outcome benefits (208–210). The methods used to evaluate the accuracy of BIS in the ICU are outlined in Supplemental Table 14 (Supplemental Digital Content 18, http://links.lww.com/CCM/D776), and the characteristics of the 32 studies included are summarized in Supplemental Table 15 (Supplemental Digital Content 19, http://links.lww.com/CCM/D777) (161, 208–239). Several common challenges in research design for these studies have been identified. The relationship between elec- troencephalogram data and subjective sedation data was often assumed to be constant and linear, but this is an inaccurate perception. Because sedation gets deeper and patients become unresponsive, subjective sedation scales reach a minimum value (SAS 1 or RASS –5), whereas objective electroencepha- logram-based tools can continue to decline until an isoelectric electroencephalogram is obtained (Supplemental Fig. 4, Supplemental Digital Content 20, http://links.lww.com/CCM/ D778) (211). At the other extreme, with increasing agitation, objective tools reach a maximum (i.e., a BIS 100), whereas subjective scales continue to describe increasing levels of agita- tion (Supplemental Fig. 5, Supplemental Digital Content 21, http://links.lww.com/CCM/D779) (211). In addition, objective monitors such as BIS allow measurement without stimulating the patient, whereas subjective sedation scales require assess- ing the patient response to voice, physical, and even noxious stimuli. This stimulation changes the preexisting state of the patient and increases the BIS value; depending on the timing of the BIS measurements (i.e., before, during, or after stimula- tion), agreement between the two assessment techniques will be affected. The 32 ICU-based studies that compared BIS and subjective sedation scale assessment were scored based on their approach to timing of BIS measurement relative to the stimulation from subjective assessment (0–4 points), type of stimulation (0–2 points), adjustment for deep sedation (0–2 points), and whether electroencephalogram signal quality and software version were defined (0–2 points) (161, 208–239). Studies with less potential confounding (4 points on the timing issue) trended to better agreement between BIS and subjective scales (p = 0.09), whereas the studies that did not account for the effect of subjective stimulation (scoring 0 on timing) had the worst agreement between BIS and subjective scales (see the red ellipse in Supplemental Fig. 6, Supplemental Digital Content 22, http://links.lww.com/CCM/D780). Three studies evaluated the effect of using the BIS to assess sedation compared with using a subjective tool (209–211). These showed reductions in total sedative use and faster wak- ening times despite similar clinical sedation (Ramsay 4) (208), a reduction in procedure-related adverse events (Ramsey 2–3) (209), and reduced midazolam and fentanyl doses, less agita- tion, less need for tracheostomy, and shorter ICU LOS (210). Evidence Gaps: Research methodology to evaluate ICU sedation monitors has not been standardized, resulting in wide variability in study design as noted above. Defining best components and approaches will improve study quality. With improved research rigor, valid comparisons between the vari- ous objective sedation monitoring tools and between objec- tive and subjective sedation scales may be possible. Additional research is needed to define the best approach to dealing with issues such as depth of sedation (particularly in an era when more patients are lightly sedated), stimulation during sedation assessment, and how different patient pathology (neurologic vs nonneurologic diagnoses) may affect objective tool reliability. Finally, more outcome studies are needed to confirm whether these tools improve patient outcomes or reduce healthcare resource consumption compared with subjective scales. Physical Restraints Question: What are the prevalence rates, rationale, and out- comes (harm and benefit) associated with physical restraint use in intubated or nonintubated critically ill adults? Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e842 www.ccmjournal.org September 2018 • Volume 46 • Number 9 Ungraded Statements: Physical restraints are frequently used for critically ill adults although prevalence rates vary greatly by country. Critical care providers report using restraints to prevent self-extubation and medical device removal, avoid falls, and to protect staff from combative patients despite a lack of studies demonstrating efficacy and the safety concerns associated with physical restraints (e.g., unplanned extubations and greater agitation). Rationale: In an era focused on improving patient-centered care, the effect physical restraints have on the care and out- comes of critically ill adults remains controversial. Physical restraints are defined as “any manual method, physical, or mechanical device, material, or equipment that immobilizes or reduces the ability of a patient to move his or her arms, legs, body, or head freely” (240). This question specifically focuses on physical restraints attached to the ankle, wrist, or upper torso. Physical restraint use varies widely from 0% in some European countries to more than 75% in North America (Supplemental Table 16, Supplemental Digital Content 23, http://links.lww. com/CCM/D781) (168, 241–261). The type and location (e.g., wrist, ankle, upper torso) of physical restraints similarly vary, with resource-rich countries reporting using commercially available restraints (242, 245–247, 249, 252, 255, 260, 262–268). Healthcare providers have historically justified the use of physical restraints in the ICU for many reasons including to enhance patient safety (242, 249, 252, 262, 263); prevent self- extubation, tube dislodgement, and/or medical device removal (242, 246, 249, 255, 262, 263, 265, 266, 269); control patient behavior (249, 262, 265, 266, 269); protect staff from combat- ive patients (263); and prevent falls (242, 263, 266). Less com- monly cited reasons include the following: preserving posture/ positioning of the patient (249, 266); staffing shortages or lack of supervision during break coverage (249, 263, 265); and compliance with patient, family member, or other medical staff suggestions (265). To date, no RCT has explored the safety and efficacy of physical restraint use in critically ill adults. The few descrip- tive studies exploring physical restraint use and outcomes of the critically ill paradoxically report higher rates of the events that their use is intended to prevent. These events include more unplanned extubations and frequent reintubations (245, 247, 267, 268); greater unintentional device removal (268); longer ICU LOS (245); increased agitation; higher benzodiazepine, opioid, and antipsychotic medication use (244, 268); and increased risk for delirium or disorientation (257, 259, 268, 270, 271). Certain modifiable and nonmodifiable factors appear to increase critically ill adults’ risk for physical restraint use. These factors include the following: older age (250, 264); non-coma level of arousal; neurologic or psychiatric condi- tions including delirium (257, 258, 261, 268); sedative type/ strategy (169, 242, 261, 272); mechanical ventilation use (242, 261, 263); use of invasive devices (246, 250); nurse-to-patient ratio and perceived workload (242, 268, 271); and time of day (249). Interestingly, patients participating in an early mobility program (273) who received early pharmacologic treatment of delirium (272) and patients who had a history of alcohol use were less restrained (268). Patients’ perceptions of being physically restrained during an ICU stay vary but often provoke strong emotional responses that persist after the ICU stay (169, 269). Given the prevalence, unintended consequences, and patients’ perceptions of physi- cal restraint use, critical care providers should closely weigh the risks and benefits of this practice in the adult ICU set- ting before initiating or maintaining physical restraint use. Although certain countries report a “restraint-free” ICU envi- ronment, it may be possible that their use of bedside sitters and/or pharmacologic restraints is increased. Evidence Gaps: Whether efforts to reduce physical restraint use will have the unintended consequence of increasing patients’ exposure to potentially harmful sedative and antipsychotic med- ications remain unclear. The effect nurse staffing patterns, staff education, and patient/family advocacy have on the incidence of physical restraint use in the ICU has also yet to be determined. Particularly relevant to the ICU setting, the necessity and eth- ics of physical restraints during end-of-life care need further exploration. Finally, the true effect physical restraints play on outcomes relevant to patients should be explored in RCTs. DELIRIUM Delirium is common in critically ill adults. The delirium encountered in the ICU and other settings are assumed to be equivalent pathophysiologic states. Delirium is a clinical diag- nosis; most studies detect delirium using screening tools such as the Confusion Assessment Method for the ICU (CAM-ICU) or the Intensive Care Delirium Screening Checklist (ICDSC) (274, 275). Delirium can be disturbing for affected patients and relatives and is associated with worse outcome, and much higher ICU and hospital LOS and costs (276). Many research gaps exist in this area (277). In this guideline, we address six actionable questions and five descriptive questions (see pri- oritized topic list in Supplemental Table 17 [Supplemental Digital Content 24, http://links.lww.com/CCM/D782] and voting results in Supplemental Table 18 [Supplemental Digital Content 25, http://links.lww.com/CCM/D783]). The evidence summaries and evidence-to-decision tables used to develop recommendations for the delirium group are available in Sup – plemental Table 19 (Supplemental Digital Content 26, http:// links.lww.com/CCM/D784), and the forest plots for all meta- analyses are available in Supplemental Figure 7 (Supplemental Digital Content 27, http://links.lww.com/CCM/D785). Risk Factors Question: Which predisposing and precipitating risk factors are associated with delirium occurrence (i.e., incidence, prev- alence, or daily transition), delirium duration, or severity in critically ill adults? Ungraded Statement: For the following risk factors, strong evidence indicates that these are associated with delirium in critically ill adults: “modifiable”—benzodiazepine use and blood transfusions, and “nonmodifiable”—greater Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e843 age, dementia, prior coma, pre-ICU emergency surgery or trauma, and increasing Acute Physiology and Chronic Health Evaluation (APACHE) and ASA scores. Rationale: Sixty-eight studies published from 2000 to November 2015 that evaluated critically ill adults not under – going cardiac surgery for delirium that used either multivari- able analysis or randomization were used to evaluate variables as potential risk factors (Supplemental Table 20, Supplemental Digital Content 28, http://links.lww.com/CCM/D786). Risk of bias of the retrieved articles was scored (cohort studies using the Scottish Intercollegiate Guidelines Network quality checklist[s] and controlled trials using Cochrane methods), and studies were classified as high, acceptable, or low quality (Supplemental Table 21, Supplemental Digital Content 29, http://links.lww. com/CCM/D787). Each variable was evaluated using three cri- teria: 1) the number of studies investigating it; 2) the quality of these investigations, and 3) where consistency existed across the studies (i.e., the direction of association was consistent for ≥ 50% of studies). Strengths of association were not summa- rized because of the heterogeneity between studies. The follow- ing, nonvalidated, criteria were used to define whether there was strong, moderate, or inconclusive evidence that a risk fac- tor was associated with increased delirium: strong—more than or equal to two high-quality articles and association consistency; moderate—one high-quality article and more than or equal to one acceptable quality article with association consistency; and inconclusive—inconsistent findings and no fulfilment of criteria for strong evidence and for moderate evidence (278). The evalua- tion of predisposing and precipitating risk factors was combined because these were studied in most investigations simultaneously. Benzodiazepine use and blood transfusion administration are the only two modifiable factors with strong evidence for an asso- ciation with delirium detected by screening tools (Supplemental Table 22, Supplemental Digital Content 30, http://links.lww. com/CCM/D788). The nonmodifiable risk factors with strong evidence for an association with delirium include increasing age, dementia, prior coma, pre-ICU emergency surgery or trauma, and increasing APACHE and ASA scores. Sex, opioid use, and mechanical ventilation each have been strongly shown not to alter the risk of delirium occurrence. Moderate evidence exists showing the following increase the risk for delirium: history of hypertension; admission because of a neurologic disease; trauma; and the use of psychoactive medication (e.g., antipsychotics, anti- convulsants). A history of respiratory disease, medical admission, nicotine use, dialysis or continuous venovenous hemofiltration, and a lower Glasgow Coma Scale score have each been moder – ately shown not to increase the risk for delirium. See the “Sedation section” for a review on how sedative choice may affect delirium and the “Sleep section” regarding the relationship between sleep and delirium. For all other potential delirium-associated risk fac- tors, evidence currently remains inconclusive. Prediction Question: Can delirium be predicted in critically ill adults? Ungraded Statement: Predictive models that include delir – ium risk factors at both the time of ICU admission and in the first 24 hours of ICU admission have been validated and shown to be capable of predicting delirium in critically ill adults. Rationale: We identified four studies that used modeling to predict ICU delirium (279–282), three of which were con- sidered to be psychometrically strong (Supplemental Table 23, Supplemental Digital Content 31, http://links.lww.com/ CCM/D789) (280–282). Of these, two studies aimed to pre- dict ICU delirium within 24 hours after ICU admission using the PREdiction of DELIRium in ICu patients (PRE-DELIRIC) model (280, 281). In a multinational study, 10 predictors (age, APACHE-II score, admission group, urgent admission, infec- tion, coma, sedation, morphine use, urea level, and metabolic acidosis) permitted a model with an area under the receiver operating characteristic (AUROC) curve of 0.77 (95% CI, 0.74– 0.79) (281). In another high-quality, multinational study (282), a model was built to predict delirium with patient characteris- tics available at ICU admission. This Early (E)-PRE-DELIRIC model includes nine predictors (age, history of cognitive impairment, history of alcohol abuse, blood urea nitrogen, admission category, urgent admission, mean arterial BP, use of corticosteroids, and respiratory failure) and was found to have an AUROC of 0.76 (95% CI, 0.73–0.77). Because both the PRE-DELIRIC and the E-PRE-DELIRIC models had similar predictive value, the model of choice can be based on availabil- ity of predictors (Supplemental Table 24, Supplemental Digital Content 32, http://links.lww.com/CCM/D790). Both models were based on screening with the CAM-ICU only. Evidence Gaps: Future etiologic studies on delirium should focus on presumed risk factors for which there is currently inconclusive evidence and where modifiability is likely. The effect of a reduction in known delirium risk factors including comorbid diseases, sepsis, nicotine and alcohol abuse, and the use of opioids and systemic steroids on delirium burden and patient outcome is unknown. Confounding is a key issue in these studies. Future studies on delirium risk factors should therefore make adequate adjustments based on previously considered risk factors (278). Assessment Question: Should we assess for delirium using a valid tool (compared with not performing this assessment with a valid tool) in critically ill adults? Good Practice Statement: Critically ill adults should be regu- larly assessed for delirium using a valid tool. Remarks: The previous guidelines provided psychomet- ric appraisals of pain, sedation, and delirium screening tools (1). A reevaluation of the psychometrics for available delirium screening tools was not conducted as part of these guidelines. This question’s focus is the effect of using any delirium assess- ment tool (vs no assessment tool) in clinical practice. Rationale: Most studies evaluating delirium assessment combine the assessment intervention with one or more management strategies (8, 110, 283), precluding the ability to evaluate outcomes related to the monitoring itself. Three studies specifically evaluated delirium assessment effects (284–286) and varied significantly in design and choice of Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e844 www.ccmjournal.org September 2018 • Volume 46 • Number 9 evaluated outcomes. Two (284, 285) found no relationship between delirium assessment and ICU LOS or duration of mechanical ventilation. Three studies evaluated time to delir- ium diagnosis and treatment. One study compared screen- ing using the CAM-ICU versus clinical assessment (285) and reported no difference in time to diagnosis or treatment with antipsychotics. The CAM-ICU arm had more antipsy- chotic medication days, but the total dose of antipsychotic medication administered was similar in the two arms. The largest of the four studies (286) compared assessment tool implementation and haloperidol use, a proxy in that study for delirium incidence and duration. More patients in the postimplementation period were treated with haloperi- dol, but at lower doses and for less time than patients in the preimplementation group. In a crossover study, Reade et al (287) compared a period of CAM-ICU assessment to a period of unstructured nursing assessments using a form with a delirium definition. The CAM-ICU arm had a signifi- cantly lower proportion of nursing shifts with delirium and a shorter duration of delirium when compared with the period of unstructured assessments. Systemic delirium detection can spuriously raise reported delirium prevalence, making it challenging to capture the true impact of delirium reduc- tion intervention efforts on this outcome. Implementation strategies differed, and each study’s significant design limi- tations led to low and very low quality of evidence evalua- tions. These studies are summarized in Supplemental Table 25 (Supplemental Digital Content 33, http://links.lww.com/ CCM/D791). Although none of the studies reported patient harm, this quality level and the heterogeneity in study design and results preclude a recommendation. This evidence can- not establish whether delirium screening alone is beneficial. Instead of a graded recommendation, we issue an ungraded Good Practice Statement given that the potential benefits of delirium monitoring far outweigh any potential downsides. Summarizing the literature and evaluating the quality of evidence was not feasible due to complexity of studies. The primary potential benefit of delirium monitoring is early rec- ognition that may hasten clinical assessment and intervention. Early detection may lead to prompt identification and correc- tion (when possible) of etiology, assurance of patients expe- riencing distressing symptoms, treatment (pharmacologic or nonpharmacologic), and treatment effectiveness assessments. Multiple studies in both ICU and non-ICU settings have found that without validated screening tools, bedside nurses and phy- sicians fail to recognize delirium (285, 287–294). What are the consequences of missing delirium in addition to possible earlier detection of underlying delirium causes? Delirium is a distressing experience for ICU patients, their families, and for ICU staff (295–298). Although not proven, such distress might be mitigated by discussions between staff and patients/families about delirium. Regular delirium moni- toring may provide a foundation for those discussions (299). Qualitative studies of ICU experiences consistently highlight that delirious patients feel greater trust toward, and encourage- ment from, family members versus staff (295, 300). The early detection and identification of delirium might benefit patients by fostering reassurance when frightening symptoms occur. Delirium screening using the CAM-ICU or the ICDSC is quick (2–5 min) (284, 286). A recent systematic review has updated the psychometric properties of delirium screening tools for critically ill adults (301). The sensitivity and speci- ficity of delirium screening tools when compared with clini- cal assessment, and their reproducibility and reliability when screening tools are substituted for a clinical diagnosis vary between ICU populations (e.g., cardiac surgery ICU or neuro- logically injured patients) (51, 302, 303). A recent publication (304) describes a new validated tool (the ICU-7) to document delirium severity and suggests that severity is associated with worse outcome. Almost all the clinical trials investigating strat- egies to prevent and/or treat delirium are based on delirium assessment tools. The generalizability of any delirium-focused study relies on these instruments in clinical practice. Because the characteristics of the tools (and their confounders) are bet- ter described, the results of these investigations will help guide future clinical trials. The disadvantages of delirium screening should be consid- ered. A false-positive screening, although rare with either the CAM-ICU or the ICDSC, may result in unnecessary pharma- cologic or nonpharmacologic treatment. ICU antipsychotic use is often associated with its continuation and prolonged administration after ICU and hospital discharge (305–307). Delirium screening may be burdensome for nursing staff (287). In the context of the criteria needed to generate a best prac- tice statement, we felt that the benefits of widespread delirium assessment with the CAM-ICU or the ICDSC far outweigh any potential disadvantages. Evidence Gaps: The current body of evidence in support of pain and agitation assessments, which has been studied longer than delirium, may provide some guidance for future research in delirium monitoring (19, 106, 110, 308–310). Some stud- ies (18, 310) suggest that the ability of assessment tools to improve patient outcomes may be associated with the inten- sity of the training strategy used and the quality improvement initiatives deployed. A recent observational study (311) found an association between high delirium monitoring adherence (i.e., assessments on ≥ 50% of the ICU days) and improved patient outcomes (i.e., lower in-hospital mortality, shorter ICU LOS, and shorter time on mechanical ventilation). Future studies should include various critical care populations such as patients with primary neurologic diagnoses. The lack of high-quality trials investigating the effect of delirium assess- ment underscores the gaps in understanding the relationship among delirium assessment and patient-centered outcomes, treatment decisions, patient and family satisfaction, and staff satisfaction. Level of Arousal and Assessment Question: Does the level of arousal influence delirium assess- ments with a validated screening tool? Ungraded Statement: Level of arousal may influence delir – ium assessments with a validated screening tool. Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e845 Rationale: Four observational cohort studies have examined delirium assessments at different levels of wakefulness and sedation as assessed by the CAM-ICU, ICDSC, and RASS (312– 315). Because many patients with RASS of –3 were deemed in these studies to be “unable to assess,” data are limited to an evaluation of the influence of a RASS range from 0 to –2 on delirium positivity. These data do not allow for discrimination between delirium that is potentially sedation induced com- pared with that related to other pathologic alterations (with or without sedation). A total of 12,699 delirium assessments (97% involving the CAM-ICU) were evaluated in patients with a RASS between 0 and –2. The likelihood of a positive delirium assessment was sig- nificantly greater (77% vs 23%; p < 0.0001) when patients had a RASS –2 (vs a RASS of –1 to 0), which could suggest that level of arousal influences delirium assessments. However, because delir – ium can present with a decreased arousal level, no inferences can be made from these data (Supplemental Table 26, Supplemental Digital Content 34, http://links.lww.com/CCM/D792). Apart from the study by Patel et al (312) in which 12% of patients in whom delirium was present during sedative infusion resolved within 2 hours of stopping infusion, no other study informs the question of whether a positive delirium assessment as a result of concomitant sedation affects patient outcome or whether seda- tion merely represents a confounding issue for patient assess- ment. Given that studies to date have shown that delirium is associated with worse outcomes, even when a depressed level of arousal is present, clinicians should not currently discount the clinical significance of delirium in this setting (316–318). Evidence Gaps: The effects of level of arousal on delirium are in need of further study. This includes the impact of delir – ium at different levels of arousal on delirium assessments (with or without concomitant sedative exposure) on important out- comes such as hospital disposition and long-term cognitive impairment. Outcomes Delirium. Questions: What are the short- and long-term outcomes of delirium in critically ill adults and are these causally related? Ungraded Statements: Positive delirium screening in criti- cally ill adults is strongly associated with cognitive impairment at 3 and 12 months after ICU discharge (316–319) and may be associated with a longer hospital stay (257, 279, 316, 320–327). Delirium in critically ill adults has consistently been shown NOT to be associated with PTSD (328–333) or post-ICU dis- tress (316, 333–336). Delirium in critically ill adults has NOT been consistently shown to be associated with ICU LOS (257, 258, 272, 279, 318, 320–326, 334, 337–352), discharge disposition to a place other than home (257, 342, 344, 353, 354), depression (330, 356), functionality/dependence (330, 334, 350, 353, 354, 357–360), or mortality (316, 357). Rationale: Despite the fact that 48 studies enrolling 19,658 patients describe potential outcomes associated with ICU delirium, the complex relationship linking delirium to these outcomes has yet to be fully defined (257, 258, 279, 316–326, 330–332, 334–354, 356–358, 360–365) (Supplemental Table 27, Supplemental Digital Content 35, http://links.lww.com/CCM/ D793). We emphasize that these associations do not imply causality and that they highlight areas for future studies par – ticularly those involving cognition. Another significant gap in ICU delirium outcomes data includes the psychologic toll that delirium exerts in real time on patients, families, and caregivers. Rapidly Reversible Delirium. Question: What are the short- and long-term outcomes of rapidly reversible delirium? Ungraded Statement: Rapidly reversible delirium is asso- ciated with outcomes that are similar to patients who never experience delirium. Rationale: One prospective observational study with blinded evaluations enrolled 102 patients (312) and found that out- comes (ICU and hospital LOS, discharge disposition, and 1-yr mortality) were similar between the 12 patients who developed rapidly reversible, sedation-related delirium and the 10 patients who never experienced delirium. Most patients (n = 80) who had either delirium or not always rapidly reversible delirium had worse outcomes than the patients with rapidly reversible, sedation-related delirium, or who never developed delirium. These preliminary data suggest that for a small group of patients with rapidly reversible delirium, delirium is not associated with the specifically measured adverse clinical outcomes. Delirium assessments should be performed both before and after a DSI (SAT) to identify these subtypes of delirium. Pharmacologic Prevention and Treatment Prevention. Question: Should a pharmacologic agent (vs no use of this agent) be used to “prevent” delirium in all critically ill adults? Recommendation: We suggest not using haloperidol, an atypical antipsychotic, dexmedetomidine, a β-Hydroxy β-methylglutaryl-Coenzyme A (HMG-CoA) reductase inhibi- tor (i.e., statin), or ketamine to prevent delirium in all critically ill adults (conditional recommendation, very low to low qual- ity of evidence). Rationale: The outcomes deemed critical to this recommen- dation included delirium incidence and duration, duration of mechanical ventilation, length of ICU stay, and mortality. Single, randomized studies of adults who were admitted to the ICU for postoperative care were reviewed for haloperidol (366); the atypical antipsychotic, risperidone (367); and dex- medetomidine (368). Each study reported a significant reduc- tion in delirium incidence favoring the pharmacologic agent: scheduled IV haloperidol (n = 457) after noncardiac surgery (RR, 0.66; 95% CI, 0.45–0.97; low quality) (366); a single dose of risperidone (n = 126) following elective cardiac surgery (RR, 0.35; 95% CI, 0.16–0.77; low quality) (366); and scheduled, low-dose dexmedetomidine (n = 700) after noncardiac surgery (odds ratio [OR], 0.35; 95% CI, 0.22–0.54; low quality) (368). One recently published, double-blind, placebo-controlled RCT of 1,789 delirium-free critically ill adults, not included in the Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e846 www.ccmjournal.org September 2018 • Volume 46 • Number 9 evidence profile, found that administration of low-dose IV haloperidol in the ICU until delirium developed did not help prevent delirium or affect 90-day survival (369). Another sug- gested that nocturnal administration of low-dose dexmedeto- midine in critically ill adults with APACHE-II scores of 22 ( sd, 7.8) was associated with a signicantly greater proportion of patients who remained delirium free (80% vs 54%; p = 0.008) during their ICU stay (370). Despite the consistent reduction in delirium incidence in each study, none reported a statistically significant and/or clinically meaningful difference for any of the other outcomes that the group deemed critical. The randomized trials inform- ing this question included surgical adults having a severity of illness less than half, on average, of the (predominantly medi- cal) ICU patients represented in these trials (366–368). Given the strong association between severity of illness and delirium occurrence (365), data derived from surgical patients with a low severity of illness must be interpreted with caution. Many acute critically ill patients have delirium at ICU admission and thus delirium prevention strategies may not apply to this proportion of the ICU population. Given this evidence gap and the lack of generalizability from each study population to the broader critically ill adult population, the current recommendation reflects the panel’s concern that the potential risks and costs of exposing a large proportion of the critically ill adult population to one or more medications aimed at preventing delirium will outweigh any benefit. Three cohort studies suggest that when statin use is stopped during critical illness, delirium occurrence increases (371–373). However, one recent randomized study of delirium-free cardiac surgery patients admitted to the ICU (not included in the evi- dence profile for this question) found that the use of preopera- tive atorvastatin did not affect incident delirium (374). The role of an NMDA receptor antagonist for the primary prevention of delirium prevention in critically ill adults was being prospec- tively evaluated in a randomized trial at the time of guideline development. One recent large RCT found that a single sub- anesthetic dose of ketamine, administered perioperatively, did not decrease delirium in older adults after major surgery, some of who required admission to the ICU (375). Subsyndromal Delirium Treatment. Question: Should a pharmacologic agent (vs no use of this agent) be used to “treat subsyndromal delirium” in all critically ill adults with subsyndromal delirium? Recommendation: We suggest not using haloperidol or an atypical antipsychotic to treat subsyndromal delirium in criti- cally ill adults (conditional recommendations, very low to low quality of evidence). Rationale: Subsyndromal delirium is part of an outcome- predicting spectrum of delirium symptoms, is present when the ICDSC score is 1–3 out of 8 and occurs in about 30% of critically ill adults (342). A critically ill patient who develops subsyndromal delirium, compared with one who develops neither delirium (ICDSC, ≥ 4) nor subsyndromal delirium, is more likely to die in the ICU, spend more time hospitalized, and to be discharged to a long-term care facility rather than home (342). Duration of subsyndromal delirium when evaluated using the CAM-ICU is an independent predictor of increased odds of institutionalization (376). The outcomes deemed critical to this recommendation included delirium incidence, duration, and severity; duration of mechanical ventilation; ICU LOS; and mortality. Both RCTs used the ICDSC to iden- tify patients with subsyndromal and full-syndrome delirium (ICDSC, ≥ 4). Scheduled IV haloperidol 1 mg q6h, when com- pared with placebo in 60 mechanically ventilated adults, was not associated with a change in delirium incidence, duration, or time to first episode of delirium; days of mechanical ventila- tion; or ICU LOS in critically ill medical and surgical patients (377). Risperidone (0.5 mg every 8 hr), when compared with placebo in 101 cardiac surgery patients, was associated with a reduced likelihood for a transition from subsyndromal to full- syndrome delirium (RR, 0.41; 95% CI, 0.02–0.86) (378). Despite this reduction in delirium incidence, neither statis- tically significant and/or clinically meaningful differences were noted for any of the other outcomes deemed critical by the group. Given these evidence gaps, questionable clinical benefit, and the potential lack of applicability of data from the study by Hakim et al (378) to the entire medical and surgical critically ill popula- tion having a greater severity of illness and different risk factors for delirium, the current recommendation reflects the panel’s concern about the risks of exposing up to 35% of all critically ill adults to antipsychotic therapy (379). The role of dexmedeto- midine, a HMG-CoA reductase inhibitor (i.e., a statin), or an NMDA antagonist (e.g., ketamine) as a treatment for subsyndro- mal delirium has not been evaluated in a randomized trial. Delirium Treatment. Question: Should a pharmacologic agent (vs no use of this agent) be used to treat delirium in all critically ill adults with delirium? Antipsychotic/statin. Recommendation: We suggest not routinely using halo- peridol, an atypical antipsychotic, or a HMG-CoA reductase inhibitor (i.e., a statin) to treat delirium (conditional recom- mendation, low quality of evidence). Rationale: The outcomes deemed most critical to this ques- tion included delirium duration, duration of mechanical ventilation, ICU LOS, and mortality. A total of six RCTs were identified: haloperidol (n = 2) (380, 381), atypical antipsy- chotics (quetiapine) (n = 1) (382), ziprasidone (n = 1) (380), olanzapine (n = 1) (383), and a statin (i.e., rosuvastatin) (n = 1) (384). A recent randomized trial of critically ill adults, not included in the evidence profile, found that high-dose simv- astatin does not reduce days spent with delirium and coma (385). No evidence was found to inform a recommendation regarding the use of an NMDA antagonist (e.g., ketamine) for delirium treatment. This evidence suggests that the use of the typical antipsy- chotic, haloperidol; an atypical antipsychotic (e.g., quetiapine, ziprasidone); or a statin was not associated with a shorter dura- tion of delirium, a reduced duration of mechanical ventilation Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e847 or ICU LOS, or decreased mortality. Although the randomized trials informing this question were conducted in both medical and surgical patients who were critically ill, each used open-label antipsychotic rescue medication for agitation or hallucinations (368, 380–384, 386). Administration of such open-label medica- tion to the placebo group in these studies may bias the results of these investigations toward the null hypothesis. The undesirable effects of haloperidol and atypical antipsychotics remain uncer – tain, given the small sample sizes of the available studies. Although this recommendation discourages the “routine” use of antipsychotic agents in the treatment of delirium, patients who experience significant distress secondary to symptoms of a delirium such as anxiety, fearfulness, hallucinations, or delusions, or who are agitated and may be physically harmful to them- selves or others, may benefit from short-term use of haloperidol or an atypical antipsychotic until these distressing symptoms resolve based on the panel’s clinical experience. Patients who start with an antipsychotic for delirium in the ICU often remain on these medications unnecessarily after discharge (305–307). Continued exposure to antipsychotic medication can result in significant morbidity and financial cost. Panel members judged that the undesirable consequences of using either haloperidol or an atypical antipsychotic far outweighed the potential benefits for most critically adults with delirium and thus issued a condi- tional recommendation against their routine use. Dexmedetomidine. Recommendation: We suggest using dexmedetomidine for delirium in mechanically ventilated adults where agitation is precluding weaning/extubation (conditional recommenda- tion, low quality of evidence). Rationale: The single RCT used to evaluate the role of dex- medetomidine as a treatment for agitation precluding ventilator liberation in patients with delirium screened 21,500 intubated patients from 15 ICUs to enroll the 71 study patients and was ter – minated early because the funding amount (from the manufac- turer of dexmedetomidine) had been used up (386). Although dexmedetomidine (vs placebo) was associated with a small, but statistically significant increase in ventilator-free hours in the first 7 days after study randomization (MD, 17.3 hr; 95% CI, 4.0– 33.2; very low quality), its use did not affect either ICU or hos- pital LOS, or patient’s disposition location at hospital discharge. Patients did not commonly receive opioids; some of the agita- tion may have been pain related; and the number of patients enrolled with acute alcohol withdrawal was not reported. Panel members judged that the desirable consequences of using dexmedetomidine for mechanically ventilated ICU patients with agitation precluding weaning/extubation out- weighed the potential undesirable consequences associated with its use; therefore, they issued a conditional recommenda- tion supporting its use in the narrow population of critically ill adults. The role of dexmedetomidine in patients with delirium without agitation or who have agitation that is not preclud- ing ventilator liberation remains unclear. Recommendations regarding choice of sedation in mechanically ventilated criti- cally ill adults in the context of delirium can be found in rec- ommendations about sedative choice. Evidence Gaps: Studies evaluating pharmacologic preven- tion strategies need to evaluate patients without delirium, enroll severely ill medical patients, identify patient subgroups where the delirium prevention benefits are greatest, and evaluate clini- cally meaningful outcomes. To improve the methodology of such subsyndromal treatment trials, our understanding of the significance, characteristics, and measurement of subsyndromal delirium needs to expand. In addition, future studies should tar – get specific symptoms (e.g., anxiety) instead of subsyndromal delirium as a whole. Delirium treatment studies should focus on more homogeneous high-risk ICU populations given that the cause of delirium (and thus response to therapy) may be differ – ent. Symptomatic distress (e.g., agitation) and long-term cogni- tive and functional outcome should be evaluated. Medications shown in small studies to reduce delirium symptoms (e.g., valproic acid) should be rigorously evaluated. Finally, system innovations are needed to ensure that patients do not remain indefinitely on medications such as antipsychotics after symp- tomatic initiation during an ICU episode of delirium. Nonpharmacologic Prevention and Treatment Single Component. Question: Should a single-component, nonpharmacologic strategy not solely focused on sleep improvement or early mobilization (vs no such strategy) be used to reduce delirium in critically ill adults? Recommendation: We suggest not using bright light therapy to reduce delirium in critically ill adults (conditional recom- mendation, moderate quality of evidence). Rationale: ICU delirium studies of nonpharmacologic interventions focused on either one modifiable risk factor with a single intervention or several modifiable risk factors with multicomponent interventions (Supplemental Table 28, Supplemental Digital Content 36, http://links.lww.com/ CCM/D794). For the purposes of these guidelines, one ques- tion addressed single intervention studies and one question addressed multicomponent intervention studies. Delirium incidence, prevalence, and duration were considered the most important outcomes across both questions. ICU LOS, hospital LOS, and hospital mortality were also considered to be critical outcomes for these questions. Bright light therapy, family par – ticipation in care, and a psychoeducational program were the only single-component interventions that have been studied in the ICU. Three studies examined the effects of light therapy, which did not demonstrate beneficial effect on either delirium incidence or ICU LOS (387–389). One before-after study evaluated the effect of family participation in care (390). Panel members judged that the undesirable consequences of using bright light therapy outweighed the potential desirable effects associated with its use and thus issued a conditional recommendation against its use. Multicomponent. Question: Should a multicomponent, nonpharmacologic strategy (vs no such strategy) be used to reduce delirium in critically ill adults? Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e848 www.ccmjournal.org September 2018 • Volume 46 • Number 9 Recommendation: We suggest using a multicomponent, nonpharmacologic intervention that is focused on (but not limited to) reducing modifiable risk factors for delirium, improving cognition, and optimizing sleep, mobility, hearing, and vision in critically ill adults (conditional recommendation, low quality of evidence). Remarks: These multicomponent interventions include (but are not limited to) strategies to reduce or shorten delir – ium (e.g., reorientation, cognitive stimulation, use of clocks); improve sleep (e.g., minimizing light and noise); improve wakefulness (i.e., reduced sedation); reduce immobility (e.g., early rehabilitation/mobilization); and reduce hearing and/or visual impairment (e.g., enable use of devices such as hearing aids or eye glasses). Rationale: The multicomponent intervention studies eval- uated a bundle of interventions. Many examples of multi- component bundles (8, 283, 391–396) have shown improved outcomes in critically ill adults (Supplemental Table 29, Supplemental Digital Content 37, http://links.lww.com/CCM/ D795). Pilot studies suggested that combining cognitive and physical therapy early during critical illness is feasible and safe (391) and using nonpharmacologic multicomponent interven- tions in ICU patients is feasible (392). Studies of multicompo- nent interventions, many of which were not randomized, focus on cognitive impairment (e.g., reorientation, cognitive stimu- lation, music, use of clocks); sedation/sleep disruption (e.g., reducing sedation, minimizing light and noise); immobility (early rehabilitation/mobilization); and hearing and visual impairment (e.g., use of hearing aids and glasses). Overall, the use of such strategies reduced delirium significantly (five studies, n = 1,318; OR, 0.59; 95% CI, 0.39–0.88) (392–396). Further, ICU duration of delirium (16 vs 20 hr) (395), ICU LOS (387), and hospital mortality all decreased (393). Another multi-intervention approach, the awakening and breathing coordination, delirium monitoring/management, and early exercise/mobility (ABCDE) bundle, was significantly associated with less delirium (n = 296; 49% vs 62%; OR, 0.55; 95% CI, 0.33–0.93) (7) when evaluated in a before-after study at one hospital. When a revised and expanded ABCDEF bun- dle (which includes a focus on “F,” Family engagement) was evaluated in a larger, multicenter, before-after, cohort study, and where delirium was also assessed using the CAM-ICU, an adjusted analysis showed that improvements in bundle com- pliance were significantly associated with reduced mortality and more ICU days without coma or delirium (9). Adverse effects were not reported in these nonpharmacologic interven- tion studies. Six of the eight studies’ small interventions were heterogeneous, and the studies with positive findings were observational. Panel members judged that desirable conse- quences of using any of these multicomponent interventions to reduce delirium outweighed any potential undesirable con- sequences and thus issued a conditional recommendation sup- porting their use. Evidence Gaps: Overall, the certainty of evidence supporting single-component and multicomponent interventions is low. Because delirium almost always has a multifactorial etiology, multicomponent interventions are plausibly more promising than single interventions. However, a major gap in understand- ing the available data is uncertainty as to which interventions result in the effect. The role of families in reducing patient stress and facilitating nonpharmacologic delirium prevention and management interventions requires further research. The experience of patients with delirium has not been qualitatively evaluated. Some articles describe the same interventions differ – ently (2); consistent definitions should be established. IMMOBILITY (REHABILITATION/ MOBILIZATION) Survivors of critical illness frequently experience many long- term sequelae, including ICU-acquired muscle weakness (ICUAW). ICUAW can be present in 25–50% of critically ill patients (397) and is associated with impairments in patients’ long-term survival, physical functioning, and quality of life (398–400). One important risk factor for ICUAW is bed rest (398, 401). The safety, feasibility, and benefits of rehabilita- tion and mobilization delivered in the ICU setting have been evaluated as potential means to mitigate ICUAW and impaired physical functioning. As highlighted in the 2013 guidelines (1), rehabilitation/ mobilization may be beneficial as part of delirium management strategies. Furthermore, important associations exist between analgesic and sedation practices and pain and sedation status with patients’ participation in rehabilitation/mobilization in the ICU (402). Given the growing literature in this field and the interplay of rehabilitation/mobilization with pain, agitation, and delirium, this topic was introduced as a new part of the present guideline. One actionable question and three descriptive questions were addressed (see prioritized topic list in Supplemental Table 30 [Supplemental Digital Content 38, http://links.lww.com/CCM/ D796] and voting results in Supplemental Table 31 [Supplemental Digital Content 39, http://links.lww.com/CCM/D797]) (403). A glossary of rehabilitation /mobilization interventions and out- comes relevant to this topic can be found in Supplemental Table 32 (Supplemental Digital Content 40, http://links.lww.com/CCM/ D798). The evidence summaries and evidence-to-decision tables used to develop recommendations for the immobility (rehabilita- tion/mobilization) group are available in Supplemental Table 33 (Supplemental Digital Content 41, http://links.lww.com/CCM/ D799), and the forest plots for all meta-analyses are available in Supplemental Figure 8 (Supplemental Digital Content 42, http:// links.lww.com/CCM/D800). Efficacy and Benefit Question: For critically ill adults, is receiving rehabilitation or mobilization (performed either in-bed or out-of-bed) benefi- cial in improving patient, family, or health system outcomes compared with usual care, a different rehabilitation/mobiliza- tion intervention, placebo, or sham intervention? Recommendation: We suggest performing rehabilitation or mobilization in critically ill adults (conditional recommenda- tion, low quality evidence). Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e849 Remarks: Rehabilitation is a “set of interventions designed to optimize functioning and reduce disability in individuals with a health condition” (404). Mobilization is a type of inter – vention within rehabilitation that facilitates the movement of patients and expends energy with a goal of improving patient outcomes (405). This recommendation supports performing rehabilitation/mobilization interventions over usual care or over similar interventions with a reduced duration, reduced frequency, or later onset. The implementation of this recom- mendation will be influenced by feasibility-related issues, par – ticularly related to variability in the availability of appropriate staffing and resources to perform rehabilitation/mobilization interventions across ICUs. Rationale: A wide variety of critically ill patient populations were studied (see study eligibility criteria in Supplemental Table 34 [Supplemental Digital Content 43, http://links.lww. com/CCM/D801]). Studies evaluated different types of inter – ventions and different timings for initiating the intervention, which prevent us from making more specific recommen- dations in these areas. Comparators for the interventions included usual care rehabilitation or mobilization; rehabilita- tion or mobilization interventions with reduced duration or frequency; or a longer time to initiation compared with the intervention group. As described below, five outcomes were evaluated for this question. Three additional outcomes (cog- nitive function, mental health, and timing of return to work and related economic outcomes) could not be evaluated due to inadequate data. We identified a total of 16 RCTs (391, 406–420) (Supplemental Table 25, Supplemental Digital Content 33, http://links.lww.com/CCM/D791) that met our eligibility crite- ria and reported on five critical outcomes. The pooled estimates from six RCTs (304 patients) showed that rehabilitation/mobi- lization improved muscle strength at ICU discharge (MD in Medical Research Council sum score [range, 0–60]: 6.24 points [95% CI, 1.67–10.82; low quality evidence]) (408–410, 414, 415, 420). Duration of mechanical ventilation (11 RCTs, 1,128 patients) was reduced by 1.31 days (95% CI, –2.44 to –0.19; low quality evidence) (406–409, 411, 413–416). For health-related quality of life measured using the 36-Item Short Form Health Survey instrument within 2 months of discharge in four RCTs (303 patients), a moderate-sized improvement (SMD, 0.64 [95% CI, –0.05 to 1.34]) not reaching statistical significance was observed, with an overall rating of low quality of evidence (412, 416–418). For the remaining two critical outcomes, across 13 RCTs (1,421 patients), there was no effect on hospital mortality (moderate quality of evidence) (391, 407, 408, 410–418, 420). Physical function was evaluated via the “Timed Up and Go” test in three RCTs (209 patients) and the Physical Function in ICU Test in three RCTs (209 patients), with no significant effect of rehabilitation/mobilization (moderate quality of evidence) (391, 411, 414, 416, 420). The incidence of adverse events for patients was very low based on five trials and eight observa- tional studies (moderate quality of evidence). Rehabilitation/mobilization was assessed as feasible, accept- able to key stakeholders, and likely to be cost-effective based on preliminary data. In addition, indirect evidence (421), along with a discussion with panel members (including an ICU patient representative), suggests that patients will prob- ably value the benefits of rehabilitation/mobilization. Given a small benefit of rehabilitation/mobilization interventions (performed either in-bed or out-of-bed) and the low overall quality of evidence, panel members agreed that the desirable consequences for patients probably outweigh the undesir – able consequences, and issued a conditional recommendation favoring rehabilitation/mobilization interventions. Safety and Risk Question: For critically ill adults, is receiving rehabilitation/ mobilization (performed either in-bed or out-of-bed) com- monly associated with patient-related safety events or harm? Ungraded Statement: Serious safety events or harms do not occur commonly during physical rehabilitation or mobilization. Rationale: Data from 10 observational and nine RCTs (Supplemental Table 35, Supplemental Digital Content 44, http://links.lww.com/CCM/D802) were reviewed to answer this question. Serious safety events or harms were defined as a change in physiologic status or an injury that required an intervention. These events were rare, with only 15 reported during greater than 12,200 sessions across 13 studies (283, 391, 416–418, 422–429). An incidence rate for these events could not be calculated because information about the number of patients at risk and/or the number of rehabilitation/mobi- lization sessions per patient was not consistently or clearly reported in many studies. The majority of safety events or harms was respiratory related, with four desaturations that required an increase in F io2 (423, 429) and three unplanned extubations (285). Three mus- culoskeletal-related events occurred: one fall (427), one Achilles tendon rupture (418), and one polyarthralgia exacerbation (416). Two cardiovascular-related events occurred: one hyper – tensive urgency (391) and one syncopal episode (416). overall, patient harm related to rehabilitation/mobilization is rare; this conclusion is supported by a recent meta-analysis (430). Indicators for Initiation Question: For critically ill adults, what aspects of patient clini- cal status are indicators for the safe initiation of rehabilitation/ mobilization (performed either in-bed or out-of-bed)? Ungraded Statements: Major indicators for safely initiating rehabilitation/mobilization include stability in cardiovascular, respiratory, and neurologic status. Vasoactive infusions or mechanical ventilation are not barriers to initiating rehabilitation/mobilization, assuming patients are otherwise stable with the use of these therapies. Rationale: Safe initiation of physical rehabilitation or mobi- lization was evaluated in 17 (283, 391, 407, 408, 413, 416–418, 424–426, 429, 431–435) studies that enrolled 2,774 patients and reported cardiovascular, respiratory, or neurologic cri- teria (Supplemental Table 36, Supplemental Digital Content 45, http://links.lww.com/CCM/D803). Data from these studies Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e850 www.ccmjournal.org September 2018 • Volume 46 • Number 9 were summarized, and expert opinion was used to determine suggested ranges for cardiovascular, respiratory, neurologic, and other relevant criteria within which rehabilitation/mobili- zation can be safely initiated (Table 1). Although these param- eters were based on clinical research with clinical application interpreted via expert opinion, they should not be a substitute for clinical judgment. All thresholds should be interpreted or modified, as needed, in the context of individual patients’ clinical symptoms, expected values, recent trends, and any cli- nician-prescribed goals or targets. Indicators for Stopping Question: For adult critically ill patients, what aspects of patient clinical status are indicators that rehabilitation/mobilization (performed either in-bed or out-of-bed) should be stopped? Ungraded Statements: Major indicators for stopping reha- bilitation/mobilization include development of new cardiovas- cular, respiratory, or neurologic instability. Other events, such as a fall or medical device removal/mal- function, and patient distress are also indications for stopping. Rationale: Indicators for stopping rehabilitation/mobi- lization were reported in 14 studies (283, 391, 407, 408, 413, 416, 418, 424, 425, 429, 431–434) that enrolled 2,617 patients (Supplemental Table 37, Supplemental Digital Content 46, http://links.lww.com/CCM/D804). Specific stopping crite- ria for cardiovascular, respiratory, or neurologic instability were identified. Data from these studies were summarized, and expert opinion was used to determine suggested cardio- vascular, respiratory, neurologic, and other relevant criteria for stopping rehabilitation/mobilization (Table 1). Although these parameters were based on clinical research with clinical application interpreted via expert opinion, they should not be a substitute for clinical judgment. Evidence Gaps: The field of ICU-based rehabilitation/ mobilization is at an early stage with a rapidly evolving body of evidence. Many research questions remain outstanding. Important directions for future research include understand- ing differences in patient outcomes according to the type of intervention and the timing, frequency, duration, and intensity of interventions. The mode of intervention delivery, including the expertise/training of personnel delivering interventions, needs additional investigation. The influence of patient condi- tions (e.g., pre-ICU functional status, delirium and sedation status, muscle wasting, and nerve and muscle dysfunction) on patient outcomes after rehabilitation/mobilization interven- tions should be examined. These factors may help to identify potential subgroups of critically ill patients who may gain the greatest benefit from rehabilitation/mobilization interven- tions. As well, methods to assess the patient experience during rehabilitation/mobilization, particularly in nonverbal critically ill patients, are warranted. Standardized reporting of interven- tion details (e.g., timing, frequency, duration, and intensity), potential safety events, and both short-term and long-term outcomes will facilitate comparisons between studies and settings. Finally, future research should continue to evalu- ate the measurement properties of short-term and long-term outcome measures to determine the most effective and effi- cient approaches to evaluating the effects of rehabilitation/ mobilization. SLEEP DISRUPTION Poor sleep is a common complaint and a source of distress for many critically ill patients (436, 437). Sleep disruption in the critically ill can be severe and is characterized by sleep fragmen- tation, abnormal circadian rhythms, increased light sleep (stage N1 + N2), and decreased slow-wave (stage N3) and rapid eye movement (REM) sleep (438–440). The interplay of medica- tions, critical illness, delirium, cerebral perfusion, and sleep is complex, but is important, and is an increasing focus of research. A glossary of the sleep-related terms used in this section can be found in Supplemental Table 38 (Supplemental Digital Content 47, http://links.lww.com/CCM/D805), and an overview of nor – mal sleep and its architecture as characterized by polysomnog- raphy can be found in Supplemental Table 39 (Supplemental Digital Content 48, http://links.lww.com/CCM/D806). In addition to emotional distress, sleep disruption has also been hypothesized to contribute to ICU delirium (441–443), prolonged duration of mechanical ventilation (444), deranged immune function (445, 446), and neurocognitive dysfunc- tion. Given that sleep is a potentially modifiable risk factor influencing recovery in critically ill adults, this topic has been introduced in the present guideline and is addressed in four actionable and six descriptive questions (see prioritized topic list in Supplemental Table 40 [Supplemental Digital Content 49, http://links.lww.com/CCM/D807] and voting results in Supplemental Table 41 [Supplemental Digital Content 50, http://links.lww.com/CCM/D808]). The evidence summa- ries and evidence-to-decision tables used to develop recom- mendations for the disrupted sleep group are available in Supplemental Table 42 (Supplemental Digital Content 51, http://links.lww.com/CCM/D809), and the forest plots for all meta-analyses completed are available in Supplemental Figure 9 (Supplemental Digital Content 52, http://links.lww. com/CCM/D810). Characterization Critically Ill Versus Healthy. Question: How does sleep in critically ill adults differ from normal sleep in healthy adults? Ungraded Statements: Total sleep time (TST) and sleep effi- ciency are often normal. Sleep fragmentation, the proportion of time spent in light sleep (stages N1 + N2), and time spent sleeping during the day (vs night) are higher. The proportion of time spent in deep sleep (stage N3 sleep and REM) is lower. Subjective sleep quality is reduced. Rationale: Small studies suggest that TST and sleep effi- ciency are normal during critical illness although considerable interpatient variability exists (443, 447). During critical illness, the proportion of time spent in light sleep (stages N1 + N2) is increased and the time spent in deep sleep (stages N3 + REM Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e851 sleep) is decreased (438, 440, 448–450). Sleep fragmentation (i.e., number of arousals and awakenings per hour) is higher in critically ill adults than healthy subjects (449, 451, 452). Among healthy adults exposed to the ICU environment, daytime sleep was found to increase each day spent in the ICU setting and represent one third of total sleep (453). In critically ill adults, the proportion of total sleep during the daytime sleep has been shown to be as high as 57% (444, 454). Subjective sleep quality is severely altered during critical illness; patients assess their sleep quality in the ICU as being considerably worse than their sleep at home (449, 455, 456). Delirium Versus No Delirium. Question: Is sleep different in critically ill adults if delirium (vs no delirium) is present? Ungraded Statements: The presence of delirium may not affect TST, sleep efficiency, or sleep fragmentation. The influence of delirium on the proportion of time spent in light (N1 + N2) versus deeper (N3) sleep is unknown. REM sleep is lower if delirium is present. Delirium is associated with greater circadian sleep-cycle disruption and increased daytime sleep. Whether delirium affects reported subjective sleep quality remains unclear. Rationale: Delirium has not been evaluated in most ICU polysomnography sleep studies. Four studies have evalu- ated sleep with polysomnography in critically ill adults with delirium that was evaluated with a validated screening tool (443, 447, 457). Two of the studies excluded patients receiv- ing sedation (443, 447). TST and sleep efficiency are similar between delirious and nondelirious patients (443, 447). One small study of noninvasive ventilation (NIV) patients found that sleep fragmentation is similar regardless of delirium status (443). The influence of delirium on the proportion TABLE 1. Summary of Safety Criteria for Starting and Stopping Physical Rehabilit ation or Mobilization Performed Either In-Bed or Out-of-Bed System Starting a Rehabilitation/Mobility Session a Stopping a Rehabilitation/Mobility Session a SystemRehabilitation or mobility could be “started” when ALL of the following parameters are present: Rehabilitation or mobility should be “stopped” when ANY of the following parameters are present: Cardiovascular • Heart rate is between 60 and 130 beats/min, • Systolic blood pressure is between 90 and 180 mm Hg, or • Mean arterial pressure is between 60 and 100 mm Hg• Heart rate decreases below 60 or increases above 130 beats/min, • Systolic blood pressure decreases below 90 or increases above 180 mm Hg, or • Mean arterial pressure decreases below 60 or increases above 100 mm Hg Respiratory • Respiratory rate is between 5 and 40 breaths/min • Sp o2 ≥ 88% • F io2 < 0.6 and positive end-expiratory pressure < 10 • Airway (endotracheal tube or tracheostomy) is adequately secured • Respiratory rate decreases below 5 or increases above 40 breaths per minute • Sp o2 decreases below 88% • Concerns regarding adequate securement of airway (endotracheal tube or tracheostomy) Neurologic • Able to open eyes to voice • Changes in consciousness, such as not follow- ing directions, lightheadedness, combative, or agitated Further, the following clinical signs and symptoms should be “absent”: Further, if the following clinical signs, symptoms or events develop and appear clinically relevant: • New or symptomatic arrhythmia • Chest pain with concern for myocardial ischemia • Unstable spinal injury or lesion • Unstable fracture • Active or uncontrolled gastrointestinal bleed • New/symptomatic arrhythmia • Chest pain with concern for myocardial ischemia • Ventilator asynchrony • Fall • Bleeding • Medical device removal or malfunction • Distress reported by patient or observed by clini- cian Other Mobility sessions may be performed with the following: • Femoral vascular access devices, with exception of femoral sheaths in which hip mobilization is generally avoided • During continuous renal replacement therapy • Infusion of vasoactive medications Spo2 = oxygen saturation. aBased on published clinical studies and expert opinion, but should not be a substitute for clinical judgment. All thresholds should be interpreted or modied, as needed, in the context of individual patient clinical symptoms, norma values, and recent trends while in the hospital, and any clinician-prescribed goals or targets. Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e852 www.ccmjournal.org September 2018 • Volume 46 • Number 9 of time spent in light sleep (N1 + N2) (vs deeper N3 sleep) was not reported in any of the studies. The amount of REM sleep was significantly lower in patients with delirium (443). Days with delirium were greater in those patients having a very low amount of REM sleep suggesting that an association between REM sleep quantity and delirium exists (442). One study found that delirium is associated with a greater circadian sleep-cycle disruption as evidenced by daytime sleep becoming a greater proportion of TST (443). Higher reported subjective sleep quality was associated with lower delirium incidence in one observational study (312), and in one RCT, earplug use reduced delirium and improved subjective sleep quality (458). In a pre-post sleep quality improvement study, patients rated their sleep before and during the multicomponent sleep pro- tocol similarly although significantly fewer patients had coma/ delirium during the intervention (459). Subjective sleep qual- ity reporting by delirious patients might be unreliable. Mechanical Ventilation Versus No Mechanical Ventilation. Question: Is sleep different in critically ill adults who are mechanically ventilated (vs not mechanically ventilated)? Ungraded Statements: The use of mechanical ventilation in critically ill adults may worsen sleep fragmentation, archi- tecture, and circadian rhythm (daytime sleep) compared with normal sleep, but these effects are often variable and have not yet been fully investigated. The use of mechanical ventilation (vs periods without mechanical ventilation) in patients with respiratory failure may improve sleep efficiency and reduce fragmentation, but data are limited. Rationale: Ventilation and sleep share complex and recip- rocal relationships. During sleep, oxygen consumption and CO 2 production decrease, leading to a physiologic reduction of ventilation compared with wakefulness. Excessive pressure support, ventilator asynchronies, or ventilator alarms might trigger arousals and sleep interruptions. For the purpose of this question, “ventilated” referred to patients mechanically ventilated (both invasively and noninvasively) and “nonventi- lated” as patients who were breathing without any respiratory assistance (i.e., no pressure support, patients may be receiving continuous positive airway pressure). Only studies that incor – porated polysomnography assessment were evaluated. Although three polysomnography studies compared dis- tinct ventilated and nonventilated groups (451, 454, 461), two studies evaluated the same patients before and after ventila- tory assistance (451, 454). During ventilation, sleep duration has been reported to be lower than normal (241, 443, 448, 453, 454, 462–464), normal (438, 465), or higher than normal (466, 467). Arousal indices are lower during ventilation (460), and sleep fragmentation is lower with NIV than without ventila- tion (243, 443, 448, 453, 454, 462–464). Sleep fragmentation is higher during mechanical ven- tilation (vs no ventilation) (449) and NIV (vs no ventila- tion) (454). The proportion of time spent in stage N3 sleep is decreased in ventilated critically ill adults (0–27%) (438, 439, 448, 449, 453, 462, 464, 467–473), as is the proportion of time spent in REM stage sleep reduced (0–14%) (241, 438, 440, 443, 448, 450, 451, 453, 454, 462, 464–473). Sleep fragmentation index during mechanical ventilation ranges from 18 to 35 arousals and awakenings per hour of sleep (241, 438, 440, 443, 448, 450, 451, 453, 454, 462, 464–474). Respiratory-related arousals have been suspected to be a major factor involved in sleep fragmentation in critically ill adults, reported in one study as causing 19% (11–30) of arousal and awakenings from sleep (241, 438, 440, 448, 450, 451, 453, 454, 460, 462, 464–474). Among ventilated criti- cally ill adults, studies consistently show that among venti- lated patients, the proportion of time spent in daytime sleep ranges from 36% to 57% and is greater than it is for nonven- tilated patients (438, 440, 443, 450, 453, 454, 470). Comparing mechanical ventilation (vs no mechanical ven- tilation) in critically ill adults, three studies have shown greater TST during mechanical ventilation (241, 436, 438), whereas one study showed no difference (461). In patients with a tracheos- tomy, median (interquartile range) sleep efficiency is higher during ventilation (61% [38–74]) than without ventilatory sup- port (44% [9–63]) (451). Two studies have shown that sleep fragmentation is significantly lower during mechanical ventila- tion (vs no ventilation) (472, 473), whereas one study showed no difference (451). Two studies showed no significant difference in sleep stages, whereas one study showed improved sleep architec- ture with less light, sleep (stage N1), and more deep sleep (stages 3 and REM sleep) during periods with NIV than without (454). Evidence Gaps: Large, additional studies are required to define the influence of critical illness, delirium, and mechani- cal ventilation on sleep quality. A systematic assessment of delirium should be done in parallel with polysomnography recording (472). Among studies, considerable variability has been reported regarding all sleep parameters. These discor – dances might be due to several factors such as total record- ing time, quality of the recordings, experience of the scorer (awareness of atypical sleep), the criteria used to analyze sleep (i.e., Rechtschaffen et Kales vs Drouot-Watson rules) (457, 475, 476), disease severity, LOS on the day of polysomnogra- phy evaluation, both sedative type and depth of sedation, and whether delirium is present. Harmonization in scoring rules and recording practices (e.g., systematic recording of noise levels and mental status) and studying homogeneous groups of patients might help to assess the prevalence of sleep altera- tions in critically ill patients. Detailed data on potential sleep disrupters are important when evaluating sleep fragmentation. The effect of sleep disruption on clinically relevant short- and long-term outcomes in large homogeneous patient groups remains uncertain. Finally, reliable tools to assess circadian rhythm disruption have yet to be identified. Prevalence of Unusual/Dissociated Sleep Question: What is the prevalence of unusual or dissociative sleep patterns in critically ill adults? Ungraded Statement: The prevalence of unusual or dissoci- ated sleep patterns is highly variable and depends on patient characteristics. Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e853 Rationale: Atypical sleep, characterized by δ waves without any cyclic organization and by the absence of K complexes and sleep spindles that are considered the defining electroencepha- logram features of stage N2 sleep, was first reported in sedated patients (438). Pathologic wakefulness is often associated with atypical sleep and is characterized by a nonreactive slowed electroencephalogram and by dissociation between electro- encephalogram rhythms and behavioral wakefulness. During atypical sleep, not included in conventional Rechtschaffen and Kales electroencephalogram scoring rules, the electroencepha- logram can display δ or θ waves (evocative of sleep) in behav- iorally awake patients or α-β waves (evocative of wakefulness) in a comatose patient (457, 476). Eleven studies have reported the prevalence of the abnor – mal sleep electroencephalogram patterns that meet the crite- ria for atypical sleep (438, 440, 443, 450, 457, 464, 476–481). In conscious nonsedated or lightly sedated ICU patients, the abnormal sleep electroencephalogram pattern prevalence ranges from 23% to 31% (440, 443, 450, 457, 480). When criteria are used to exclude patients with known factors for these abnormal electroencephalogram patterns (e.g., receiv- ing sedative/opioids, having delirium coma or sepsis, or with a history of epilepsy), the prevalence of atypical sleep becomes nonexistent (0%) (464). In sedated patients, the prevalence of at least one dissociated electroencephalogram pattern (dis- sociated wake or sleep) ranges from 60% to 97% (438, 476, 481), and the prevalence of isolated unusual sleep electroen- cephalogram patterns ranges from 50% to 70% (475, 481). Variability in the presence to those factors (i.e., sedation, sep- sis, and delirium) known to influence abnormal sleep electro- encephalogram patterns likely accounts for the variability in prevalence among studies (438, 440, 457, 476). Evidence Gaps: Sleep recordings in critically ill adults should be carefully examined to identify new unusual or dissociative sleep patterns using published approaches and specific criteria (457, 476). The clinical characteristics of patients with these unusual patterns, and their associated mechanisms and outcomes both during and long after the ICU stay, should be investigated. Risk Factors Before ICU Admission. Question: What risk factors that exist before the onset of critical illness affect sleep quality in critically ill adults in the ICU? Ungraded Statement: Patients who report poor-quality sleep and/or use of a pharmacologic sleep aid at home are more likely to report poor-quality sleep in the ICU. Rationale: The following factors existing before the onset of critical illness have been examined to determine if they affect sleep quality in ICU: female gender, older age, reported poor quality of sleep at home, regular use of sleep aid medication at home, and specific premorbid medical conditions (e.g., hyper – tension, diabetes, cancer, and thyroid disease) (Supplemental Table 43, Supplemental Digital Content 53, http://links.lww. com/CCM/D811). Of these, only “reported poor quality sleep at home” (459, 482, 483) and “regular use of a pharmacologic sleep aid at home” (450, 482) have been consistently reported in more than one study as being associated with perceived lower quality of sleep in the ICU. During ICU Admission. Question: Which ICU-acquired risk factors affect sleep quality in critically ill adults? Ungraded Statement: Pain, environmental stimuli, health- care-related interruptions, psychologic factors, respiratory fac- tors, and medications each affect sleep quality in the ICU. Rationale: Patient-perceived factors that contribute to patient-perceived poor sleep among critically ill adults have been reported according to either their severity (degree to which they disrupted sleep) or incidence (frequency with which they were reported) in 12 observational studies (455, 456, 460, 482, 484– 492) (Supplemental Table 44, Supplemental Digital Content 54, http://links.lww.com/CCM/D812). The factors most frequently cited by patients as disruptive to sleep were noise, pain and dis- comfort, immobility/restricted movement, nursing care inter – ventions, and worry/anxiety/fear (449, 455, 456, 482, 484–490, 492, 493). Four studies (449, 456, 482, 492) used the “Sleep in the Intensive Care Unit (ICU) Questionnaire” (455) to assess the severity of disruption caused by seven extrinsic (environmental) factors (ranked on a scale of 1–10 with 1 being no disruption and 10 significant disruption). The top three reported extrinsic factors disrupting sleep were noise, lighting, and nursing inter – ventions (e.g., baths). All seven factors, including the top three, ranked 5 or less on the 10-point sleep disruptiveness scale (455, 482, 484). When ICU patients were asked to rank 35 intrinsic and extrinsic factors on a 0–4 scale (based on how disruptive each factor was to sleep), the top intrinsic factors were pain, inability to get comfortable, the bed, and procedures being per – formed on the patient (456, 485–490, 492, 493). A complete list of patient-identified factors is summarized in Table 2. In addition to asking patients to identify factors they perceive as disruptive, other studies have measured sleep objectively using polysomnography or actigraphy and attempted to correlate risk factors with various measures of sleep. Factors that have been shown to correlate with sleep disruption in univariate analyses include illness severity (494), delirium (442, 443), hypoxemia and alkalosis (494), receiving a benzodiazepine (442) or propo- fol (464), patient-ventilator asynchrony (454), spontaneous (vs mechanically supported) breathing (452), and a spontaneous mode of ventilation (vs a controlled mode) (472, 495). Noise has been found to correlate temporally with arousals but appears to be responsible for only 10–17% of all arousals (449, 455, 482, 484). Only one study included multivariable analysis and found that presence of an endotracheal tube (i.e., receiving mechani- cal ventilation) seemed to confer improved sleep quality (460). The sleep of individual patients may be affected differently by various risk factors (e.g., some patients may be more bothered by noise than other patients) and the meaning or relevance to patients (e.g., some patients are comforted by hearing the nurse nearby, whereas others are bothered by it), and the patient’s intrinsic disposition (e.g., susceptibility to feel worried, afraid, or uncomfortable under similar circumstances). Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e854 www.ccmjournal.org September 2018 • Volume 46 • Number 9 Evidence Gaps: Studies using questionnaires and interviews, while patient-centered, are subject to recall bias and exclude patients who are not able to self-report due to sedation, delir – ium, dementia, or acute brain injury. Furthermore, patients may have sleep that is severely fragmented with microarous- als, but the patients may not be able to identify the disrup- tive factors because they were not fully awakened from sleep. Studies using polysomnography are limited to those that can be analyzed by standard criteria and exclude highly abnormal electroencephalograms or those with poor-quality electroen- cephalogram signals. Studies correlating various factors with impaired sleep on polysomnography do not prove causation, only association, and were largely weak associations in univari- ate analysis. Outcomes Question: Do sleep and circadian rhythm alterations “during” an ICU admission affect outcomes during and/or after the ICU stay in critically ill adults? Ungraded Statements: Although an association between sleep quality and delirium occurrence exists in critically ill adults, a cause-effect relationship has not been established. An association between sleep quality and duration of mechanical ventilation, length of ICU stay, and ICU mortality in critically ill adults remains unclear. The effects of sleep quality and circadian rhythm alterations on outcomes in critically ill patients after ICU discharge are unknown. Rationale: A handful of studies help answer these ques- tions (Supplemental Table 45, Supplemental Digital Content 55, http://links.lww.com/CCM/D813). Poor sleep quality is often assumed to be a potentially modifiable risk factor for ICU delirium; several studies have evaluated this relationship. Critically ill adults who are severely sleep deprived are 30% more likely to have mental status changes (441). Subsequent polysomnography studies further supported this association (442, 451). Critically ill adults with severe REM deprivation (442, 451) and circadian sleep-cycle disruption (as evidenced by a greater proportion of daytime sleep) are more likely to experience delirium (451). Poor sleep quality has also been found to be an independent risk factor (496) for postcardiac surgery ICU delirium. Additionally, before-and-after observa- tional studies of multidisciplinary bundles that include sleep enhancement protocols have been shown to decrease delirium prevalence (312, 454), although in only one study did sleep efficiency improve with the intervention (312). Although an association between sleep quality and delirium occurrence exists, it remains unknown if poor sleep is a cause for delirium. Use of a multicomponent delirium prevention protocol that incorporated a nonpharmacologic sleep enhancement protocol TABLE 2. List of Factors That Patients Report as Disruptive to Sleep Environmental Physiologic and Pathophysiologic Noise (447, 453, 454, 480, 483–488, 490, 491)Pain (454, 483–486, 488, 490, 491) Light (241, 453, 454, 480, 482–484, 486–488) Discomfort (454, 483, 486, 488, 490) Comfort of bed (483, 486–488) Feeling too hot or too cold (484, 486, 488) Activities at other bedsides (483, 486, 487) Breathing difficulty (484, 491) Visitors (clinician or family) (483) Coughing (484, 491) Room ventilation system (483) Thirst (484, 486) and hunger (486, 488) Hand washing by clinicians (483) Nausea (484, 488) Bad odor (486, 488) Needing to use bedpan/urinal (486, 488) Care Related Psychologic Nursing care (447, 453, 480, 482–484, 486, 488, 491)Anxiety/worry/stress (483, 484, 486, 489–491) Patient procedures (447, 453, 480, 482, 483, 487, 488) Fear (485, 486, 489) Vital sign measurement (442, 448, 475, 477, 481, 483) Unfamiliar environment (485, 488, 491) Diagnostic tests (447, 453, 480, 483) Disorientation to time (454, 486) Medication administration (447, 453, 480, 482) Loneliness (488, 491) Restricted mobility from lines/catheters (454, 486, 488) Lack of privacy (485, 488) Monitoring equipment (454, 486, 488) Hospital attire (486, 488) Oxygen mask (486, 488) Missing bedtime routine (483) Endotracheal tube (491) Not knowing nurses’ names (486) Urinary catheters (486) Not understanding medical terms (486) Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e855 was associated with shorter delirium duration and greater venti- lator-free days (497). The relationship of sleep to these outcomes remains unclear as sleep was not measured in the study. Patients with abnormal sleep (increased daytime sleep; reduced REM) were more likely to fail NIV and require intubation and mechani- cal ventilation (443). In a small study of patients with moderate/ severe TBI, better or improving rest-activity cycle consolidation ( ≥ 80% daytime activity) was associated with shorter ICU and hospital stays (498). Among patients where abnormal sleep was felt to be a cause of late NIV failure, ICU stays were longer and both ICU and hospital mortality rates were greater (443). One quality improvement study showed no difference in mortality with its use despite delirium’s being reduced (459). The presence of organized sleep patterns in patients with a recent TBI is pre- dictive of improved survival (479). Although a number of stud- ies have found that sleep remains disturbed after ICU discharge, no studies were found in the literature evaluating the effect of sleep in the ICU on outcomes after ICU discharge. Evidence Gaps: Available studies cannot fully elucidate the relationship between sleep alterations in the critically ill and important outcomes such as delirium occurrence, duration of mechanical ventilation, ICU LOS, and mortality are inadequate to confirm whether an association exists between the sleep altera- tions seen in the critically ill adults and important outcomes such as delirium occurrence, duration of mechanical ventilation, ICU LOS, and mortality. Poor sleep may adversely affect the immune system, glycemic control, and the psychologic well-being of oth- erwise healthy individuals, so understanding if there are clinical effects on these and other outcomes in critically ill adults is of great importance. Studies that pair these outcomes with reliable measurement of sleep at the ICU bedside, while controlling for the multiple other factors that are associated with these out- comes, are needed. Additionally, studies are needed to determine the effects of ICU sleep quality on post-ICU outcomes. Monitoring Question: Should physiologic monitoring be routinely used clinically to evaluate sleep in critically ill adults? Recommendation: We suggest not routinely using physi- ologic sleep monitoring clinically in critically ill adults (condi- tional recommendation, very low quality of evidence). Remarks: Physiologic monitoring refers to the use of actig- raphy, bispectral analysis (BIS), electroencephalography, and polysomnography to determine if a patient is asleep or awake. It specifically does “not” include monitoring of patients’ perceived sleep by either validated assessment (e.g., the Richards Campbell Sleep Questionnaire) or informal subjective bedside assessment. Rationale: None of the five critical outcomes chosen for this question (i.e., delirium occurrence, duration of mechani- cal ventilation, ICU LOS, ICU mortality, and patient satisfac- tion) have been studied. Observational studies have evaluated the role of physiologic sleep monitoring on other outcomes ( Supplemental Table 46, Supplemental Digital Content 56, http://links.lww.com/CCM/D814). Physiologic monitor – ing identified sleep-disordered breathing in patients with acute coronary syndromes (499, 500), but the impact of this evaluation was not determined. When motor activity (as mea- sured by actigraphy) was compared with nurses’ sleep and seda- tion assessments in a small series of mechanically ventilated adults (501), limb movements were found to correlate with the measured neurologic indices. The use of polysomnogra- phy-derived electroencephalogram recordings of patients with nontraumatic (479) and traumatic (480) encephalopathy con- cluded that the presence of recognized elements of sleep was associated with a favorable prognosis. Finally, three small stud- ies found that polysomnography can be used to optimize the method of mechanical ventilatory support in ICU patients in acute respiratory failure (443, 502, 503). Despite these potential roles for polysomnography, its routine use in the ICU is not feasible. The panel arrived at this recommendation based on the lack of high-quality evidence combined with the high cost of the resources necessary to implement most of the relevant technologies. Physiologic monitoring and interpretation have significant limitations as described above. Further, no studies investigated sleep monitoring in an unselected ICU popula- tion, thus calling into question the generalizability of the avail- able data. Although routine physiologic sleep monitoring is not rec- ommended, we emphasize that clinicians “should” routinely inquire about patients’ sleep or try to monitor it either by using one of the validated assessment tools such as the Richards Campbell Sleep Questionnaire or by informal bedside assess- ment. The Richard-Campbell Sleep Questionnaire has been shown to be a valid and reliable tool in critically ill adults to evaluate a patient’s perception of their own sleep if they are both alert and oriented (504). Poor sleep is considered to be one of the most common stresses experienced by critically ill patients (435, 437). Asking about patients’ sleep may serve to validate patients’ and their families’ concerns and is a necessary first step to approaching an intervention. Nurse-observed sleep (439, 448, 505, 506) overestimated TST when compared with polysomnography evaluation. When nurse and patient perceptions of sleep are compared, the nurse may sometimes overestimate patients’ perception of sleep quality (485, 492, 505, 507). Evidence Gaps: How best to measure sleep in critically ill patients continues to be debated (476, 508). Routine moni- toring of any brain activity in the ICU remains challenging. The problem of monitoring sleep is further complicated by the fact that the electrical activity of the brain alone (i.e., electro- encephalogram) is insufficient to determine sleep stages, cir – cadian activity, and sleep-disordered breathing. A simplified, generalizable system for monitoring sleep in the ICU that is resistant to the changing physiology of the critically ill patient and will stand up to regular use in the ICU setting would enhance our understanding of the relationship between sleep and ICU outcomes. In contrast to healthy individuals, critically ill patients have variation in vigilance states and electroenceph- alogram patterns not only due to natural sleep/wake states but also from sedating medications and delirium. Whether sed- ative-induced sleep provides the same restorative benefits as Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e856 www.ccmjournal.org September 2018 • Volume 46 • Number 9 natural sleep is unknown. Large studies are needed to deter- mine the best method of sleep measurement and classification and to measure how the individual factors (sleep, sedation, ill- ness-induced encephalopathy) or a combination thereof affect patient outcomes, including patient satisfaction. The expense and time-consuming nature of polysomnography have made research of sleep measurement and sleep outcomes difficult. Other measurement techniques such as limited electroenceph- alogram and processed electroencephalogram devices may provide valuable data, but studies comparing them to poly- somnography are needed to validate these methods. Nonpharmacologic Interventions to Improve Sleep A description of the ventilation modes evaluated in this section question and the methods used to identify studies and sum- marize data can be found in Supplemental Table 47 (Supple- mental Digital Content 57, http://links.lww.com/CCM/D815). Ventilator Mode. Question: Should assist-control ventilation be used at night (vs pressure support ventilation) to improve sleep in critically ill adults? Recommendation: We suggest using assist-control ventila- tion at night (vs pressure support ventilation) for improving sleep in critically ill adults (conditional recommendation, low quality of evidence). Rationale: Many of the outcomes deemed critical or impor – tant by the panel for this question were not evaluated or reported. Pooled estimates of three studies (n = 61) (469, 472, 473) found that assist-control ventilation (vs pressure support ventilation) was associated with an increase in sleep efficiency (MD, 18.33%; 95% CI, 7.89–28.76; moderate quality). Although pooled estimates of two studies (472, 473) (n = 41) found that assist-control ventilation (vs pressure support ventilation) was not associated with a difference in the percentage of TST spent in stage 1 (MD, 0.31%; 95% CI, –5.17 to 5.79; low qual- ity) or stage 2 (MD, 5.29%; 95% CI, –4.38 to 14.97; very low quality) sleep, it was associated with more time spent in REM sleep (MD, 2.79%; 95% CI, 0.53–5.05; low quality). Although the quality was deemed to be low, given the potential benefits of this intervention, its low risk and the fact that all ventilators have assist-control mode capability, a conditional recommendation for using assist-control mode ventilation at night to improve sleep was made. For those patients who remain dyssynchronous despite all efforts to optimize ventilator settings on assist-control mode, however, clinicians will have to make a case-by-case deci- sion whether to return the patient to pressure support ventila- tion or consider sedation, considering the deleterious effects of propofol and benzodiazepines on sleep quality and synchrony. Question: Should an adaptive mode of ventilation be used at night (vs pressure support ventilation) to improve sleep in critically ill adults? Recommendation: We make no recommendation regarding the use of an adaptive mode of ventilation at night (vs pressure support ventilation) for improving sleep in critically ill adults (no recommendation, very low quality of evidence). Rationale: Five small randomized controlled crossover trials compared an adaptive mode of ventilation versus a pressure support mode in primarily medical critically ill adults, evalu- ating outcomes the panel deemed important but none were deemed critical. The adaptive modes studied were as follows: automatically adjusted pressure support (473), proportional assist ventilation (462), proportional assist ventilation with load-adjustable gain factors (468, 471), and neutrally adjusted ventilator assist (465). Feasibility may also be a concern because some ICUs might not have ventilators or staff trained to deliver an adaptive ventilation mode. Based on these issues, and the reluctance to issue a recommendation based on this small, sin- gle-center study due to feasibility/availability concerns in other centers, we were not able to make a recommendation regarding the use of adaptive ventilation at night. NIV-Dedicated Ventilator. Question: Among critically ill adults requiring NIV, should an NIV-dedicated ventilator (vs a standard ICU ventilator with NIV capacity) be used to improve sleep? Recommendation: We suggest using either an NIV-dedicated ventilator or a standard ICU ventilator for critically ill adults requiring NIV to improve sleep (conditional recommendation, very low quality of evidence). Rationale: Only one small randomized trial was available to answer this question, and it did not evaluate most of the defined outcomes (454). No significant differences appeared between use of an NIV-dedicated ventilator and a standard ICU ventilator with respect to sleep efficiency; percent of time spent in stage 1, stage 2, stage 3/4, or REM sleep; or sleep fragmenta- tion index. Compared with periods off NIV, sleep during NIV resulted in increased REM and stage 3/4 sleep with a reduc- tion in sleep fragmentation index. Based on the above, patients with acute hypercapnic respiratory failure have improved sleep quality during NIV compared with without NIV, but we rec- ommend that either type of ventilator, dependent on feasibility and convenience, is acceptable to use for ICU patients requir – ing NIV. Evidence Gaps: Studies comparing sleep between assisted breathing and controlled breathing in the assist-control and adaptive modes and the adaptive mode and assist-control ventilation modes have not been published. Studies used poly- somnography to measure sleep on various modes, but none of these studies evaluated patients’ perception of their sleep. Aromatherapy/Acupressure/Music Question: Should aromatherapy, acupressure, or music be used at night (vs not using it) to improve sleep in critically ill adults? Recommendation: We suggest not using aromatherapy, acu- pressure, or music at night to improve sleep in critically ill adults (conditional recommendation, low quality of evidence [aroma- therapy and acupressure]; very low quality of evidence [music]). Rationale: Two small, unblinded RCTs (509, 510) evaluated the use of aromatherapy for improving sleep in conscious and communicative ICU patients. No adverse effects were reported, but a pooled analysis demonstrated no effect with its use (vs no Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e857 use) in patient-reported sleep quality (MD, 0.02 points; 95% CI, –0.36 to 0.41; low quality) and the overall quality of evi- dence was low. Although a low-cost intervention that is gen- erally considered safe, the lack of proven benefit for sleep in addition to some concern about using potential respiratory irritants in an ICU population led the panel to make a condi- tional recommendation against aromatherapy in the ICU. One small RCT (n = 85) (511) evaluated the use of acupres- sure in ICU patients having a low severity of illness. Researchers who attended an acupressure training course applied pressure for 3 minutes to each of six acupoints between 7:00 pm and 10:00 pm and found that acupressure (vs no use of acupressure) was associated with an increased duration of sleep when evalu- ated by actigraphy (md, 0.5 hr; 95% Ci, 0.0 0.91; low quality) or the nurse (md, 1.1 hr; 95% Ci, 0.3 1.81; low quality) and less daytime sleepiness on the stanford sleepiness scale (md, 0.4 points; 95% Ci, 0.6 0.14; low quality). Given the high risk of bias for the single included study, the small number of patients enrolled, the cost of having a trained clinician pro- vide acupressure, and the lack of availability of this modality at many centers, we decided to suggest against the use of acupres- sure to improve sleep in critically ill adults. For those institu- tions with trained personnel and expertise, however, it may be a reasonable intervention, especially if requested by patients. one small RCT (n = 28) (512) evaluated the effect of play- ing music on the piano (four sedating pieces lasting 45 min) on sleep outcomes (during first 2 hr of night) in critically ill adults. The music had a small effect on improving sleep quality (as evaluated by the Verran and Snyder-Halpern Sleep Scale) (MD, 48 points; 95% CI, 34.5–130.5; very low quality) and sleep efficiency (as evaluated by polysomnography) (MD, 2.3%; 95% CI, 27.3–32.0; very low quality). Given the low quality of evidence (no blinding, ambient noise not controlled) and the resources needed to institute this intervention, the panel made a conditional recommendation against the use of music to improve sleep in critically ill adults. Music may play a role in reducing pain (see pain section) and anxiety in the ICU (133). If patients (or their families) request it, it should be considered. Noise and Light Reduction Question: Should noise and light reduction strategies (vs not using these strategies) be used at night to improve sleep in critically ill adults? Recommendation: We suggest using noise and light reduc- tion strategies to improve sleep in critically ill adults (condi- tional recommendation, low quality of evidence). Rationale: Two RCTs (458, 513) and two observational studies (514, 515) evaluated strategies to reduce ICU noise and light at night through the use of earplugs with or without the use of eyeshades. Use of earplugs and eyeshades (vs control) on the first postoperative ICU night after cardiac surgery main- tained sleep quality at the preoperative level (513). Application of earplugs (vs no earplugs) to nonsedated, critically ill adults improved patient-reported sleep quality and reduced delirium (458). Pooled analysis from the two ICU observational studies (n = 164) found that application of ear plugs (vs no ear plugs) was associated with a greater proportion of achieving greater than 4 hours of sleep (RR, 1.2; 95% CI, 0.64–2.24; low qual- ity) (513, 515). The overall quality of evidence was low due to a lack of blinding, a population of patients not severely ill, and the refusal of some patients to keep the earplugs inserted. Earplugs, with or without eyeshades, represent a low-cost intervention that can be applied in all ICUs to improve sleep quality and reduce delirium. In general patients, particularly those who cannot initiate sleep, should be asked if they want this intervention and earplugs should always be removed in the morning. Evidence Gaps: Nonpharmacologic strategies focused on improving sleep in the ICU need to be evaluated in large ran- domized trials, include ICU patients with higher severity of ill- ness, and rigorously evaluate the effect of these interventions on sleep quality. The group of patients in the ICU who may gain the most benefit from these interventions needs to be elucidated. Pharmacologic Interventions to Improve Sleep Given the challenges of promoting naturally occurring sleep in the ICU, patients and their family members may ask for sleep- enhancing medication. Although their request should always be considered, this pressure and our efforts to provide com- passionate care sometimes lead to the administration of med- ications that are poorly tested for safety and efficacy in ICU patients and that may increase the risk for polypharmacy and delirium rather than actually promote sleep. Pharmacologic interventions were considered by drug type/class and were reviewed by the panel solely for their effect on sleep promotion. Question: Should a sleep-promoting medication (i.e., mela- tonin, dexmedetomidine, or propofol) (vs no use of a medica- tion) be used to improve sleep in critically ill adults? Melatonin. Recommendation: We make no recommendation regarding the use of melatonin to improve sleep in critically ill adults (no recommendation, very low quality of evidence). Rationale: Three small, placebo-controlled, randomized trials (n = 60) evaluating the night-time administration of melatonin were reviewed. The first found that the administra- tion of 10 mg of melatonin at night (vs placebo) to 12 patients in the ICU having chronic respiratory failure was associated with nonsignificant improvements in both sleep quality and quantity (as evaluated by BIS) (516). A second RCT that eval- uated night-time melatonin 3 mg (or placebo) in 16 patients in a similar population and evaluated sleep using actigra- phy arrived at a similar conclusion (517). A third RCT that compared melatonin 3 mg (or placebo) to 32 patients who also were admitted to the ICU with chronic respiratory fail- ure as the first two studies found no discernible difference in the duration of “observed nocturnal sleep” by bedside nurse assessment (518). The limitations of evaluating sleep in the ICU using BIS, actigraphy, or subjective nursing scales rather than polysomnography are highlighted previously in the guidelines. Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e858 www.ccmjournal.org September 2018 • Volume 46 • Number 9 The manufacture of melatonin in the United States is not Food and Drug Administration regulated; concerns as to the quality and consistency of the product (519) have prevented many hospitals from adding it to their formulary. Melatonin is, however, associated with relatively few adverse effects (e.g., mild sedation and headache) and inexpensive. The panel decided on no recommendation due to the perceived balance between desirable and undesirable outcomes and the lack of high-quality evidence. Ramelteon, an FDA-approved melatonin receptor agonist, was evaluated in a single study (not included in this analysis) to prevent delirium in the elderly (520). A small number of patients in that study were critically ill; however, there was no demonstrable improvement in subjective sleep quality. Similar to melatonin, few adverse events are reported with the medica- tion, but sleep promotion was not proven and the cost is higher than that of melatonin. One recent single-center, double-blind, placebo-controlled RCT, also not included in this analysis, found that the administration of 8 mg of ramelteon at 20:00 hours each day to critically ill adults without delirium was asso- ciated with significant reduction in delirium occurrence (521). Dexmedetomidine. Recommendation: We make no recommendation regarding the use of dexmedetomidine at night to improve sleep (no rec- ommendation, low quality of evidence). Rationale: Two randomized trials (n = 74) evaluated the effects of dexmedetomidine in critically ill, mechanically ven- tilated adults requiring sedation (470) and in critically ill, non- mechanically ventilated patients not requiring a continuous infusion of a sedative medication (521). Both studies demon- strated that dexmedetomidine increased stage 2 sleep (MD, 47.85% min; 95% CI, 24.05–71.64; moderate quality) and decreased in stage 1 sleep (MD, –30.37%; 95% CI, –50.01 to –10.73; moderate quality), each of which the panel considered favorable outcomes (470, 521). Neither study, however, demon- strated a decrease in sleep fragmentation or an increase in deep sleep or REM sleep that are thought to be the most restorative sleep stages and thus potentially most important to recovery. A third, observational trial, not included in this analysis, cor – roborated these findings with regard to sleep architecture and noted preserved day-night cycling when dexmedetomidine was administered overnight in mechanically ventilated ICU patients (522). One recently published double-blind, placebo- controlled RCT of 100 delirium-free critically ill adults receiv- ing sedatives, and not included in the evidence profile, found that the administration of low-dose dexmedetomidine did not change Leeds Sleep Evaluation Questionnaire scores between the dexmedetomidine and placebo groups (370). Consideration was given to a conditional recommendation in favor of using dexmedetomidine at night for the sole pur – pose of sleep promotion; however, clinical concerns include its high cost, hemodynamic side effects, and generalizability of the existing studies. If a sedative infusion is indicated for a hemody- namically stable, critically ill adult overnight, dexmedetomidine may be a reasonable option because of its potential to improve sleep architecture (523). See the sedation section for a more in- depth evaluation of sedative choice in critically ill adults. Propofol . Recommendation: We suggest not using propofol to improve sleep in critically ill adults (conditional recommendation, low quality of evidence). Rationale: Two RCTs compared propofol with benzodiaz- epines (454, 524), and one compared propofol with placebo (525). No demonstrable improvement in sleep occurred with propofol compared with placebo. Further, propofol was asso- ciated with REM suppression, hemodynamic side effects, and respiratory depression sometimes necessitating mechanical ventilation. Although we recommend against using propofol for the sole purpose of improving sleep in the critically ill, this recommendation does not intend to address its use in patients requiring procedural or continuous sedation. Other medications administered with the intent to improve sleep in the critically ill include tricyclic antidepressants, atypi- cal antipsychotics, and hypnotics such as benzodiazepines and benzodiazepine-receptor agonists. Currently, there is insuf- ficient information to consider a recommendation for any of medications to help promote sleep in the critically ill. Although their adverse effects are well described, their benefits in terms of sleep promotion are unknown. Evidence Gaps: Large, well-controlled trials of medications administered at night for the sole purpose of sleep promo- tion in critically ill patients are lacking. This is especially true for medications such as tricyclic antidepressants and atypical antipsychotics that are frequently used for this pur – pose because they are less likely to precipitate an episode of delirium, have fewer hemodynamic and respiratory depres- sant effects, and because their sedating side effects suggest the possibility of sleep promotion. These medications, however, should be rigorously studied to assess their efficacy in this population to determine if the benefits justify their potential harms. Sleep-Promoting Protocol Question: Should a sleep-promoting protocol be used to improve sleep in critically ill adults? Recommendation: We suggest using a sleep-promoting, multicomponent protocol in critically ill adults (conditional recommendation, very low quality of evidence.) Rationale: Protocols are a common way to incorporate multiple interventions at once into a clinical practice guide- line (526), including those described below for sleep quality improvement in critically ill patients. The sleep-promoting protocols eligible for inclusion varied in their components, as described below (459, 527–529). All included offering earplugs and eyeshades to patients who could choose to use them or to discontinue their use if they wished and two also included use of relaxing music (459, 526). Among the two composed of a more complex combination of interventions, one specified a pharmacologic guideline that discouraged the use of sedating medications known to alter sleep and/or precipitate delirium Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Online Special Article Critical Care Medicine www.ccmjournal.org e859 and introduced interventions in stages over a 5-month period (459). In all studies, protocols were applied to all ICU patients and did not target a subset of patients known to have poor sleep quality. The critical outcomes examined were sleep stages, sleep duration, sleep fragmentation, circadian rhythm, delirium, duration of mechanical ventilation, mortality, LOS (ICU and hospital), and patient experience. Current published data contain four studies reporting outcomes relevant to this question, one RCT (527), and three observational stud- ies (459, 528, 529) (Supplemental Table 48 Supplemental Digital Content 58, http://links.lww.com/CCM/D816). One small RCT in open-heart surgery patients demonstrated that earplugs, eyeshades, and relaxing music improved self- reported sleep quality (528). Among the three observational before-and-after studies, one found an improvement in sleep in a mixed ICU population (529), whereas the other two did not (459, 528). Pooled analysis of the three studies demon- strated an overall reduction in the prevalence of delirium with a sleep-promoting protocol (RR, 0.62; 95% CI, 0.42– 0.91; very low quality). One of the observational studies used a similar intervention to Hu et al (527), earplugs, eye shades, and music, whereas the other two tested more com- plex interventions including these interventions plus envi- ronmental changes, namely clustering of care to minimize interruptions overnight and early mobilization (459, 529). One study also specifically included pharmacologic guide- lines, administering zolpidem to patients without delirium and haloperidol or an atypical antipsychotic for patients with delirium (459). In an effort to minimize the influ- ence of medications on outcomes, Patel et al (529) excluded patients who had received sedatives in the 24 hours before enrollment. Which of the interventions, or which combina- tions of the interventions, are effective in improving sleep and reducing delirium cannot be discerned from the above studies. Overall evidence was low or very low quality due to risk of confounding, imprecision, and the potential for risk of bias in the included studies. The panel made a conditional recommendation based on the potential for benefit (e.g., delirium reduction) and minimal anticipated harm. The panel recognized, however, that implementing and sustain- ing multifaceted clinical practice protocols can be resource intensive (530). Evidence Gaps: Future research should investigate which of the interventions, or which combinations of the interventions, are effective in improving sleep and reducing delirium. The effect on reduction in delirium in the reviewed studies but less demonstrable on sleep quality is notable, reinforcing that more work on the assessment of sleep in critically ill adults is needed, as recommended above. Although many thousands of publica- tions on the science of implementing evidenced-based clinical practice guidelines exist, relatively few address improving sleep in critically ill adult patients; this specific topic would benefit from further investigation. Mortality, ICU LOS, and dura- tion of mechanical ventilation were reported in the reviewed studies, but numbers were too small to draw any conclusions. These, as well as patient experience and patient-centered mid- to long-term outcomes such as sleep quality, psychologic health, and quality of life determinants such as autonomous living remain unexplored. Concluding Comments on Sleep: Studies to date are consis- tent in demonstrating that critically ill patients sleep poorly as a result of both patient and ICU factors. The importance of improving sleep in this population may be unproven by RCT but is intuitive and, at least, could be considered an important comfort measure that would improve patients’ ICU quality of life if not other outcomes. Although only a select few interven- tion studies have been published, available data suggest that a multicomponent protocolized approach to improving sleep that favors nonpharmacologic measures may offer our patients their best chance for a better night’s sleep. Future research needs to focus on improved methods for measuring sleep and on implementing interventions targeting patient-centered outcomes. Sleep habits are highly variable among healthy indi- viduals; therefore, a more individualized approach should be considered. SUMMARY Thousands of hours were invested by these guidelines’ authors, who were in turn supported by formal and informal collab- orators, over the 3.5 years it took to produce this effort. As experts mandated by the Society of Critical Care Medicine, we aimed to provide the recent information clinicians need to better care for critically ill adults (531, 532) using the most rigorous and transparent processes at our disposition. Because such process does not necessarily ensure acceptability among knowledge providers and users (533), we established ways in which to address relevant and patient-centered pain, sedation, delirium, immobility, and sleep practice-related questions. The diversity of our experts (534), representing many professions on three continents, generated vigorous discussions as to clini- cal approaches and care aspects that differed by geographical availability (of medication interventions, for instance) and by institutional culture. Because we did not limit our reviews to English language publications, the evidence gathered to sup- port our recommendations represents literature from around the world. The recommendation rationales, fueled by debate and dis- cussion, circled back to the bedside experience—and the per – spective of what was best for patients—held by all panelists and methodology experts. In sections added to these guidelines since their last 2013 version (1) (rehabilitation/mobility and sleep), we sought to clarify conceptual definitions within these relatively new critical care research domains. We wanted to make them accessible to facilitate incorporating them into the complex patient management reasoning any critical care clini- cian might consider. We challenged common practices such as administering antipsychotics to delirious patients. We invited clinicians to expand the proposed interventions in comparison to the 2013 guidelines (1); one example is the consideration of multiple pharmacologic and nonpharmacologic coanalgesic approaches to the ICU patient. When the published evidence Copyright © 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Devlin et al e860 www.ccmjournal.org September 2018 • Volume 46 • Number 9 was insufficient, limited to a narrow population or specific intervention (e.g., for procedural analgesia), or outright absent to answer the questions we posed, we structured evidence gap descriptors to inform clinicians where the uncertainty lay, and intended to provide sufficient information to apprise and invite researchers to address these gaps. We are mindful of the limitations inherent to our work. “Good evidence” requirements for randomized trials involv- ing many patients have its caveats; practice misalignment (535) and diagnostic confounders (312) were, to the extent it was possible, considered, but “unknown” factors with the potential to influence evidence likely exist. One example is the recent introduction of stratification by frailty (536) in trials involving the critically ill, which could not be con- sidered because this comorbidity had not been taken into account in much of the literature justifying our recom- mendations. Another is the fact that although all patients were admitted to an ICU, both the reasons leading to their ICU admission and severity of illness varied considerably, warranting individual tailoring of our recommendations to individual patient considerations. A degree of uncertainty is as inherent to clinical practice as it is to the research process and its resulting conclusions (537). The quest to make our decision making and iterative innovations transparent and accessible motivated the methods article that was prepared separately from this guideline initiative (13). Finally, the development of guidelines like these does not ensure their use (538). Some educational programs and the provision of feedback in relationship to attaining analgesia and sedation-targeted performance goals have been disap- pointingly ineffective when studied prospectively (3, 4). We consider the effectiveness and limitations of different dissem- ination methods and approaches germane to this guideline’s topics in a separate publication as a tool to inform educa- tional programming and quality improvement initiatives that will evolve from this guideline (2). In addition to bridging the gap between the knowledge we gathered and its applica- tion, we believe that this will provide tangible support to cli- nicians, stakeholders, and decision makers in implementing quality in pain, agitation, delirium, early mobility, and sleep and further foster the application of what we understand to be useful in the provision and delivery of excellent care. ACKNOWLEDGMENTS We acknowledge the many direct and indirect contributors to this effort: Margaret McIvor, an ICU survivor whose contri- bution was limited by subsequent illness; students, trainees, and colleagues (Julie C. Reid, PT, MSc; Anastasia Newman, PT, MSc; David J. Gagnon, PharmD; Lauren E. Payne, PharmD; Nicole Kovacic, PharmD; Kimia Honarmand, MD, MSc; Jamie Le, MD; Sindu Mohan, MD; Peter J. Hurh, MD; Justin D. Dumont, DO, MS; M. Farhan Nasser, MD; Venkat R. Venna, MD; Aparna Nallagangula, MBBS; Kimberly J. Terry, PharmD; and Jeremy R. DeGrado, PharmD) helped with abstract and full-text screening, supervised by several of the authors; Grading of Recommendations Assessment, Development and Evaluation group members (Fayez Alshamsi, MD) who pro- vided help with data analyses; Charlie Kishman, MSL, who initiated the literature searches as a continuation of his con- tribution to the 2013 PAD guidelines; Matt Duprey, PharmD, for his valuable support at the 2017 Hawaii meeting; Lori Harmon and Sylvia Quintanilla who provided direction and organizational infrastructure; and Deb McBride copywrote and edited the final article. The panel coauthors’ effort would not have been possible without the explicit and implicit sup- port of colleagues, families, and friends. The time committed to the Pain, Agitation/sedation, Delirium, Immobility (reha- bilitation/ mobilization), and Sleep (disruption) initiative had to be weighed against availability to attend personal and professional challenges. We wish to acknowledge all those who shouldered other responsibilities, indirectly facilitating the creation and writing of these guidelines. Finally, we wish to thank the patients, teachers, and colleagues who inspired this effort and who challenged us to honor, and rise to the challenge of, this academic effort. The Society of Critical Care Medicine’s ICU Liberation ini- tiative is dedicated to providing resources and implementation tools related to the prevention and management of pain, agi- tation, delirium, and immobility. Please visit the ICU Libera- tion Campaign website (http://www.iculiberation.org/About/ Pages/default.aspx) for additional information. REFERENCES 1. Barr J, Fraser GL, Puntillo K, et al; American College of Critical Care Medicine: Clinical practice guidelines for the management of pain, agitation, and delirium in adult patients in the intensive care unit. Crit Care Med 2013; 41:263–306 2. 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Directions: please follow explicitly *** primarily this assignment is filling in the tables- have attached all articles to use **** Use the attached “Literature Evaluation Table to complete this a
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All Rights Reserved. Feature Articles Critical Care Medicine www.ccmjournal.org 885 Objectives: To measure the impact of staged implementation of full versus partial ABCDE bundle on mechanical ventilation dura- tion, ICU and hospital lengths of stay, and cost. Design: Prospective cohort study. Setting: Two medical ICUs within Montefiore Healthcare Center (Bronx, NY). Patients: One thousand eight hundred fifty-five mechanically ventilated patients admitted to ICUs between July 2011 and July 2014. Interventions: At baseline, spontaneous (B)reathing trials (B) were ongoing in both ICUs; in period 1, (A)wakening and (D)elir- ium (AD) were implemented in both full and partial bundle ICUs; in period 2, (E)arly mobilization and structured bundle (C)oordina- tion (EC) were implemented in the full bundle (B-AD-EC) but not the partial bundle ICU (B-AD). Measurements and Main Results: In the full bundle ICU, 95% patient days were spent in bed before EC (period 1). After EC was implemented (period 2), 65% of patients stood, 54% walked at least once during their ICU stay, and ICU-acquired pressure ulcers and physical restraint use decreased (period 1 vs 2: 39% vs 23% of patients; 30% vs 26% patient days, respectively; p < 0.001 for both). After adjustment for patient-level covariates, im- plementation of the full (B-AD-EC) versus partial (B-AD) bundle was associated with reduced mechanical ventilation duration (–22.3%; 95% CI, –22.5% to –22.0%; p < 0.001), ICU length of *See also p. 997.1Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY. 2Division of Pulmonary Diseases, Critical Care, and Environmental Medi-cine, Department of Medicine, Tulane University School of Medicine, New Orleans, LA. 3Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Depart- ment of Medicine, University of Miami, Miller School of Medicine, Miami, FL. 4Division of Critical Care Medicine, Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY. 5Division of Pulmonary Diseases and Critical Care, Department of Med-icine, University of Texas Health Sciences Center at San Antonio, San Antonio, TX. 6Department of Nursing, Montefiore Healthcare Center, Bronx, NY.7Department of Physical Medicine and Rehabilitation, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY. 8Occupational Therapy Assistant Program, Health Sciences Depart-ment, LaGuardia Community College, Long Island City, NY. 9Division of Pulmonary Medicine, Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY. 10Network Performance Group, Montefiore Medical Center, Yonkers, NY.11Department of Epidemiology and Population Health, Albert Einstein Col- lege of Medicine, Bronx, NY. Drs. Hsieh and Gong conceptualized and designed the study. Drs. Hsieh, Otusanya, Gershengorn, Hope, Dayton, Prince, Mills, Fein, Colman, and Gong acquired, analyzed, and interpreted the data. Drs. Hsieh, Otusanya, Gershengorn, Hope, and Gong drafted the article for important intellec- tual content. Supplemental digital content is available for this article. Direct URL cita- tions appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals.l ww.com/ ccmjournal). Supported, in part, by 8KL2TR0000088-05 from the Albert Einstein Col- lege of Medicine – Montefiore Medical Center Institute for Clinical an d Translational Research (to Dr. Hsieh), R03AG050927 (to Dr. Hope), Na- tional Heart, Lung, and Blood Institute HL084060 and HL086667 (to Dr. Gong); 1 UL1 TR001073-01, 1 TL1 TR001072-01, 1 KL2 TR001071-01 (Einstein-Montefiore Clinical and Translational Science Awards). Drs. Hsieh, Hope, and Gong received support for article research from the National Institutes of Health (NIH). Dr. Hsieh’s institution received funding from Einstein-Montefiore Institute for Clinical and Translational Research DOI: 10.1097/CCM.0000000000003765 Staged Implementation of Awakening and Breathing, Coordination, Delirium Monitoring and Management, and Early Mobilization Bundle Improves Patient Outcomes and Reduces Hospital Costs* S. Jean Hsieh, MD, MS 1; Olufisayo Otusanya, MD 2; Hayley B. Gershengorn, MD 3; Aluko A. Hope, MD, MScE 4; Christopher Dayton, MD 5; Daniela Levi, MD 4; Melba Garcia, BSN 6; David Prince, MD 7; Michele Mills, MA, OTR 8; Dan Fein, MD 9; Silvie Colman, PhD 10; Michelle Ng Gong, MD, MS 4,11 and La Jolla Pharmaceutical. Dr. Gong’s institution received funding from NIH grants and Philips Healthcare. The remaining authors have disclosed that they do not have any potential conflicts of interest. This work was performed at Montefiore Healthcare Center. Address requests for reprints to: Michelle Ng Gong, MD, MS, Division of Critical Care Medicine, Department of Medicine, Montefiore Medical Center, 111 East 210th Street, Bronx, NY 10467. E-mail: [email protected] tefiore.org Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Hsieh et al 886 www.ccmjournal.org July 2019 • Volume 47 • Number 7 stay (–10.3%; 95% CI, –15.6% to –4.7%; p = 0.028), and hos- pital length of stay (–7.8%; 95% CI, –8.7% to –6.9%; p = 0.006). Total ICU and hospital cost were also reduced by 24.2% (95% CI, –41.4% to –2.0%; p = 0.03) and 30.2% (95% CI, –46.1% to –9.5%; p = 0.007), respectively. Conclusions: In a clinical practice setting, the addition of (E)arly mobilization and structured (C)oordination of ABCDE bundle components to a spontaneous (B)reathing, (A)wakening, and (D) elirium management background led to substantial reductions in the duration of mechanical ventilation, length of stay, and cost. (Crit Care Med 2019; 47:885–893) Key Words: critical care; delirium; early mobilization; implementation; mechanical ventilation I CU-acquired delirium and weakness can lead to dev- astating cognitive and physical impairments and psy- chiatric symptoms in ICU survivors, also known as “post-intensive care syndrome” (1–6). The (A)wakening and (B)reathing, (C)oordination, (D)elirium monitoring and management, and (E)arly mobilization (ABCDE) bundle (7, 8) is an interdisciplinary patient-centered evidence-based strategy endorsed by critical care societies and national quality improvement agencies to prevent and reduce ICU delirium and weakness, and operationalize the Society of Critical Care Medicine’s Pain, Agitation, and Delirium clin- ical practice guidelines (9–13). Individual components of the ABCDE bundle are asso- ciated with substantial benefits in research settings (14–20). Although studies in clinical practice settings suggest that im- plementation of the full ABCDE bundle is associated with clinical benefits, its uptake has been limited and implemen- tation often-incomplete (21–28). Sequential implementa- tion of bundle components may improve overall execution by allowing providers to: 1) maximize efficacy of imple- mentation by focusing on individual components, 2) assess process improvement by performing stepwise evaluation of components, and 3) make practice adjustments before mov- ing to the next component. In addition, studies suggest that the efficacy of early mobilization can be maximized if pro- grams to reduce unnecessary sedation and delirium are al- ready in place (25, 29). Accordingly, we sought to determine the impact of add- ing EC to B-AD in the context of staged implementation of the ABCDE bundle in mechanically ventilated (MV) patients. We hypothesized that implementation of early mobilization on a foundation of targeted sedation practices and routine de- lirium monitoring would improve clinical outcomes and re- duce hospital cost. Preliminary results have been presented in abstract form (30, 31). MATERIALS AND METHODS See Supplemental Appendix (Supplemental Digital Content 1, http://links.lww.com/CCM/E506) for a more detailed descrip- tion of study procedures. Study Design and Setting This prospective study took place in two academic medical ICUs at Montefiore Medical Center (Bronx, NY). ICUs had the same size (14 beds) and staffing (two patients per nurse, 24 hr onsite intensivist coverage), except the full bundle ICU was staffed by medical residents and the partial bundle ICU by physician assistants. The Institutional Review Board (IRB) approved a waiver of informed consent (IRB number 2014–3466). Cohort Our primary cohort consisted of all MV adults (≥ 18 yr) admit- ted to the ICUs for greater than or equal to 24 hours between July 1, 2011, and June 30, 2014 (Fig. 1). This cohort was used for analyses of clinical outcomes; alternative cohorts were used for process of care and cost outcomes (Fig. S1 and text in Sup- plemental Appendix, Supplemental Digital Content 1, http:// links.lww.com/CCM/E506). Implementation Stages Interdisciplinary teams of critical care nursing, physician, phar – macy, respiratory therapy, and rehabilitation leadership and champions developed and implemented bundle components. (A)wakening and (D)elirium Monitoring/Management (AD) (Both ICUs). At baseline, both ICUs used MV order sets that included daily sedation vacations and spontaneous (B) reathing trials (B) (Fig. 1); however, no guidance was given on performance or coordination of these bundles. Beginning in January 2012, the (A)wakening from sedation and (D)elirium monitoring/management (AD) bundles were implemented in both ICUs; this included physician-directed targeted sedation using the Richmond Agitation and Sedation Scale (32, 33), twice daily delirium assessments using the Confusion Assess- ment Method-ICU by nurses (32, 34), and suggestions for nonpharmacologic delirium reduction methods. To account for time to adopt these changes, AD bundles were considered fully implemented by July 1, 2012. (E)arly Mobilization and (C)oordination of Components (EC): (Full Bundle ICU Only). (E)arly mobilization (E) con- sisted of evaluation by physical therapy (PT) and occupational therapy (OT) at ICU admission, and daily rehabilitation by PT and/or OT according to a staged protocol in which patients ad- vanced from passive range of motion to independent ambula- tion with respiratory therapy and nursing assistance as needed (17, 35) (Fig. S3, Supplemental Digital Content 1, http://links. lww.com/CCM/E506). As part of this bundle, daily structured interdisciplinary rounds were established for ICU nurses, res- piratory therapists, and rehabilitation staff to (C)oordinate bundle components (C), diagnostic tests and procedures. On July 1, 2013, EC were implemented in the full bundle ICU only because of resource and staffing limitations. Data Collection Clinical data were extracted from electronic medical records using healthcare surveillance software (Clinical Looking Glass; Emerging Health Information Technology, Yonkers, Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Feature Articles Critical Care Medicine www.ccmjournal.org 8 87 NY ). To determine if practices changed after ICU-wide implementation of bundle components, we also examined process of care data (Fig. 1; and Fig. S1 and text in Supple- mental Appendix, Supplemental Digital Content 1, http:// links.lww.com/CCM/E506). Outcomes Clinical Outcomes. The primary outcome of interest was the hospital length of stay (LOS) after the index ICU admission (i.e., ICU LOS + post-ICU LOS). Secondary outcomes included ICU LOS, duration of MV, hospital mortality, and discharge location. Cost Outcomes. Total hospital and ICU cost and average daily ICU cost (i.e., total cost divided by ICU LOS) were de- termined using cost-to-charge ratios at Montefiore Medical Center. Because cost-to-charge ratios differ by calendar year, the cohort in the cost analyses was limited to patients with hospitalizations that ended between January 1, 2012, and De- cember 31, 2013. Costs were calculated as the sum of daily direct variable costs from cost centers related to inpatient, nonoperative care (e.g., respiratory support, room and board, laboratory, medications) as previously described (37). Clinical Quality Outcomes. Clinical quality metrics that may be affected by implementation of the ABCDE bundle (e.g., ICU restraint use, prevalence of ICU-acquired pressure ulcers) were obtained from aggregate hospital-reported data for Cen- ters for Medicare and Medicaid Services quality indicators in both full and partial bundle ICUs. Data were only available for periods 1 and 2. Statistical Analysis Patient characteristics and unadjusted clinical outcomes were compared across ICUs and time periods using standard de- scriptive statistics. Nonparametric tests were used for skewed continuous measures. To evaluate the impact of EC on clinical and cost out- comes, we compared trends in these outcomes in the full versus partial bundle ICUs before and after EC implemen- tation using a multivariable difference-in-differences (DiD) approach (38, 39). This methodology uses a multivariable regression model that includes an interaction term for “time period” (e.g., period 1 vs 2) and “ICU” (full vs par – tial bundle) that measures the magnitude of the effect of EC Figure 1. Timeline of staged implementation of ABCDE in partial (B-AD only) versus full (B-AD-EC) bundle ICUs and data measurement periods. A, Periods of component implementation in the full and partial bundle ICUs. At baseline, spontaneous (B)reathing trials were ongoing in both full and partial bundle ICUs; on July 1, 2012, (A)wakening and (D)elirium monitoring/managemen t were implemented in both ICUs; on July 1, 2013, (E)arly mo- bilization and structured bundle (C)oordination were implemented in only the full bundle ICU. B, Periods in which process of care, clinical outcomes, and cost data were collected relative to bundle implementation. aProcess of care measurements (sedative use, delirium prevalence, maximum level of mobility) were compared across time in the full bundle ICU (B-AD-EC) only. bICU quality indicators, clinical outcomes, and cost were compared across t ime in both the full (B-AD-EC) and partial (B-AD) bundle ICUs. cCost periods were truncated because cost data are calculated based on a cost-to-charge ratio which varies between calendar years. The following periods were compared for the cost analysis: 1) baseline v ersus period 1 (i vs ii) and 2) period 1 versus pe – riod 2 (iii vs iv). A = awakening from sedation, B = spontaneous breat hing trial, C = structured coordination of bundle components, D = deliri um monitor – ing and management, E = early mobilization. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Hsieh et al 888 www.ccmjournal.org July 2019 • Volume 47 • Number 7 (Fig. 1). In contrast to standard before-after studies, DiD controls for temporal trends in patient characteristics (e.g., increasing severity of illness) that might impact outcomes. DiD analyses are based on four assumptions to ensure va- lidity of the model, the most important of which is the parallel trend assumption (i.e., prior to interventions, tem- poral changes in outcomes for both ICUs are similar) (38). To test this assumption, separate regression models were constructed for each outcome in the baseline period (for B vs B-AD analysis) and period 1 (for B-AD vs B-AD-EC analysis); models included interaction terms for ICU admis- sion date and ICU. We also performed sensitivity analyses to determine if including patients with hospital LOS greater than 90 would alter our estimates. Although AD was imple- mented in both units, we used DiD (baseline vs period 1) to evaluate for differential impact of AD implementation on clinical outcomes between ICUs. All models were adjusted for patient-level characteristics that differed between ICUs (univariable p ≤ 0.2). Because Acute Physiology and Chronic Health Evaluation (APACHE) IV scores were missing in 10% of patients, we used dummy variable adjustment (40). All tests were two-tailed and p value of less than 0.05 de- fined statistical significance. Analyses were performed with STATA/MP 13 (Statacorp, College Station, TX). TABLE 1. Patient Characteristics in Partial (B-AD) Versus Full Bundle (B-AD-EC) ICUs Across Implementation Periods Patient Characteristic Baseline Period 1 Period 2 B Ongoing in Both ICUs B-AD in Both ICUs B-AD in Partial Bundle ICU; B-AD-EC in Full Bundle ICU Partial Bundle ICU, n = 267 Full Bundle ICU, n = 356 Partial Bundle ICU, n = 271 Full Bundle ICU, n = 314 Partial Bundle ICU, n = 281 Full Bundle ICU, n = 366 Age a, mean ( sd) 64 (5 74) 64 (5 75)66 (5 77) 64 (5 75)67 (5 78) c 61 (5 73) c Male, % 49464846 4551 Race, % c cc c White 221833213317 Black 3735273330 35 Multiracial 303230 342837 Other 111510111011 Hispanic ethnicity, % 33 c 42 c 373929 c 42 c Resided at home, % 79 c 70c 82 c 74c 8076 Admit from Ed, % a 66 6779 c 68 c 78c 69 c Charlson Comorbidity Index, median (IQR) 0 ( 1) 0 ( 2) 0 ( 2)0 ( 2)0 ( 1) c 0 ( 2) c Acute Physiology and Chronic Health Evalu- ation IV, median (IQR) b,d 59 (4 76) 59 (4 77) 61 (4 77)62 (4 77)66 (5 86) 72 (5 90) Primary admitting diagnosis, % sepsis 5248 5449 5549 Respiratory 181917221517 Cardiovascular 444345 Gastrointestinal 355877 Endocrine/renal 341344 Other 211918161518 A = awakening from sedation, B = spontaneous breathing trial, C = coordination of bundle components, D = delir ium monitoring and management, E = early mobilization, IQR = interquartile range. a Partial bundle ICU between three periods, p ≤ 0.04.b Full bundle ICU between three periods, p < 0.001.c Partial vs full bundle ICU within period, p < 0.01.d Test for trend across three periods within partial and full bundle ICU, p ≤ 0.001. Multiple comparisons are being made in this table. Interpretive example: 1) patients were younger in full bundle ICU vs partial bundle ICU and 2) severity of illness increased over time in both partial and full bundle ICUs. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Feature Articles Critical Care Medicine www.ccmjournal.org 889 RESULTS Patient Characteristics Between July 1, 2011, and June 30, 2014, 1,855 MV patients were admitted to the full (1,036, 56%) and partial bundle (819, 44%) ICUs. The full bundle ICU had younger patients and more minorities (Table 1). Patients in the full bundle ICU also had more comorbidities, higher severity of illness, and fewer lived at home prior to hospitalization. Severity of illness (APACHE IV) increased across periods in both ICUs (p ≤ 0.001). Process of Care Evaluation (Full Bundle ICU Only) Sedative Use and Delirium Prevalence (Fig. S2, Supple- mental Digital Content 1, http:// links.lww.com/CCM/E506). In the rull bundle ICU, the pro- portion of patients receiving continuous sedation decreased across all three periods (p < 0.001 for midazolam and fen- tanyl; p = 0.06 for propofol) (Fig. S3A , Supplemental Digital Con- tent 1, http://links.lww.com/ CCM/E506). The proportion of patients with ICU delirium and/ or coma also decreased across all three periods (p ≤ 0.02) and similar to sedative use, the larg- est decrease occurred after AD was implemented (Fig. S3B , Supplemental Digital Content 1, http://links.lww.com/CCM/ E506). ICU Mobility. After EC was implemented in the full bundle ICU (period 1 vs 2), the pro- portion of patients evaluated by the rehabilitation team (i.e., either PT and/or OT) increased from 19% to 90% and the pro- portion of patient days spent passively lying or sitting in bed decreased from 95% to 37%. Patients received rehabilitation therapy within 1 day of ICU ad- mission (median ICU day 1; in- terquartile range [IQR], 0–1) for a median of 60% of all ICU days (IQR, 50–80%); 77% of patients dangled at the bed’s edge, 65% stood, and 54% walked at least once during their ICU stay. No serious complications occurred during the 1,345 rehabilitation treatments. The main reasons why patients did not receive reha- bilitation therapy were lack of staff and clinical instability (61% and 29% of patient days with no rehabilitation, respectively). Outcomes Clinical Quality Outcomes. The proportion of patients with ICU-acquired pressure ulcers decreased (39% to 23%; p < 0.001) and the proportion of ICU patient days in restraints Figure 2. Clinical quality outcomes in full and partial bundle ICUs (periods 1 vs 2). Quality metrics from ag- gregate hospital-reported data Centers for Medicare and Medicaid Service s quality indicators were compared between periods 1 versus 2 in both full and partial bundle ICUs. A, In the full bundle ICU (B-AD vs B-AD-EC), pressure ulcer incidence and physical restraint use decreased (p < 0.001 for both). B, In the partial bundle ICU (B-AD vs B-AD), pressure ulcer incidence and physical restraint use in creased ( p = 0.04; p = 0.001, respec- tively). A = awakening from sedation, B = spontaneous breathing trial, C = structured coordination of bundle components, D = delirium monitoring and management, E = early mobilizati on. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Hsieh et al 890 www.ccmjournal.org July 2019 • Volume 47 • Number 7 decreased (30% to 26%; < 0.001) after implementation of EC in the full bundle ICU (period 1 vs 2; Fig. 2A). In contrast, the prevalence of ICU-acquired pressure ulcers increased (18% to 23% of patients; p = 0.04) and proportion of ICU days in restraints increased (50% to 54%; p = 0.001) in the partial bundle ICU during the same periods of time (Fig. 2B). Clinical Outcomes. Duration of MV and ICU LOS signifi- cantly changed in the full bundle ICU but not in the partial bundle ICU across three periods (Table 2). The duration of MV was sig- nificantly shorter in period 2 in the full versus partial bundle ICU, and ICU LOS was significantly shorter across all three periods in the full versus partial bundle ICU (p < 0.001). Hospital LOS and hospital mortality did not differ across all periods in both ICUs. In our DiD analyses, implementation of AD in both full bundle and partial bundle ICUs was associated with no signifi- cant changes in clinical outcomes, except for increased hospital LOS in the full versus partial bundle ICU (5.9%; 95% CI, 4.6– 7.2%; p = 0.011) (Table 3). Implementation of EC in the full bundle ICU after AD was associated with a 22.3% decrease in duration of MV (95% CI, –22.5% to –22.0%; p < 0.001), a 10.3% decrease in ICU LOS (95% CI, –15.6% to –4.7%; p = 0.028), and a 7.8% decrease in hospital LOS (95% CI, –8.7% to –6.9%; p = 0.006) compared with the partial bundle ICU (Table 3). The parallel trend assumption was met for all outcomes except for hospital LOS in period 1, where hospital LOS increased more in the full versus partial bundle ICU (0.17% change per calendar day; 95% CI, 0.10–0.24%; p = 0.022) (Table S2, Supplemental Digital Content 1, http://links.lww.com/CCM/E506). Sensitivity analyses including patients with hospital LOS greater than or equal to 90 days (n = 28, who had been excluded from our pri- mary cohort) revealed similar results (Table S3, Supplemental Digital Content 1, http://links.lww.com/CCM/E506). Cost Outcomes. In DiD analyses, implementation of AD in both full and partial bundle ICUs was associated with no sig- nificant changes in cost between the two units (Table 3). Im- plementation of EC in only the full bundle ICU was associated with a 24.2% reduction in total ICU cost (95% CI, –41.4% to –2.0%; p = 0.034; Table 3) and a 30.2% reduction in total hos- pital cost (95% CI, –46.1% to –9.5%; p = 0.007) in the full versus partial bundle ICU; there was no reduction in average daily ICU cost (4.4%; 95% CI, –4.5% to 14.1%; p = 0.342). The parallel trend assumption was met for all cost outcomes (Table S2, Supplemental Digital Content 1, http://links.lww. com/CCM/E506). TABLE 2. Clinical Outcomes in Partial (B-AD) Versus Full Bundle (B-AD-EC) ICUs Across Implementation Periods Clinical Outcome Baseline Period 1 Period 2 B Ongoing in Both ICUs B-AD in Both ICUs B-AD in Partial Bundle ICU; B-AD-EC in Full Bundle ICU Partial Bundle ICU, n = 267 Full Bundle ICU, n = 356 Partial Bundle ICU, n = 271 Full Bundle ICU, n = 314 Partial Bundle ICU, n = 281 Full Bundle ICU, n = 366 Duration of mechanical ventilation (d), median (IQR) a 5 (3–11) 4 (3–9)5 (3–10) 5 (3–10)6 (3–11) b 4 (2–7) b ICU LOS (d), median (IQR) a 6.9 (3.4–12.7) b 5.0 (3.0–10.3) b 7.6 (4.7–13.0) b 6.2 (3.9–11.7) b 6.9 (3.8–13.3) b 5.0 (3.0–9.3) b Hospital LOS (d), median (IQR) c 13.2 (6.6–22.9) 12.2 (7.0–21.5)13.4 (8.9–21.9) 13.9 (8.0–24.4)14.0 (7.7–24.2)13.3 (7.1–23.3) Hospital mortality, % 222530 262830 Discharge location, % b b Home 464546 484348 Rehabilitation 634 253 Skilled nursing facility 4246 41 464441 Acute care hospital 134 044 Hospice 114 021 Left against medical advice 3 22 313 A = awakening from sedation, B = spontaneous breathing trial, C = coordination of bundle components, D = delir ium monitoring and management, E = early mobilization, IQR = interquartile range, LOS = length of stay. a Full bundle ICU across three periods, p < 0.001; partial bundle ICU did not significantly differ across three periods.b Partial vs full bundle ICU within period, p ≤ 0.01.c Hospital LOS defined as index ICU LOS + post-ICU LOS. Multiple comparisons are being made in this table. Interpretive example: 1) duration of mechanical ventilation in period 2 was shorter in the full vs partial bundl e ICU and 2) duration of mechanical ventilation significantly differed across three periods in the full bundle ICU. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Feature Articles Critical Care Medicine www.ccmjournal.org 891 DISCUSSION This is the first large-scale prospective quality improvement study demonstrating the value of staged implementation of a bundle of evidence-based interventions aimed at reducing ICU associated weakness and delirium. We showed that the addition of (E)arly mobilization and structured interdiscipli- nary (C)oordination of bundle components to a spontaneous (B)reathing trial, (A)wakening from sedation, and (D)elirium monitoring/management program (B-AD + EC), is feasible, associated with improvements in quality of care, and is inde- pendently associated with substantial reductions in MV dura- tion, ICU LOS, hospital LOS, and cost savings after adjusting for secular trends and patient-level confounders. Our findings complement the growing literature demonstrat- ing the clinical benefit of ABCDE bundle (25, 41). Simultaneous implementation of ABCDE/F bundle components has been associated with increased hospital survival and delirium and coma-free days, and reduced duration of MV (21–23). Studies suggest that ABCDE, and early mobilization in par – ticular, can be challenging to implement in routine practice (24–26, 42). Over 100 unique barriers have been identified in recent literature reviews (43). Dubb et al (44) classified these barriers into four categories: patient-related (e.g., deep seda- tion, delirium, new immobility/weakness), structural (e.g., lack of mobility protocol, limited staff and equipment, inadequate training), process related (e.g., lack of coordination), and cul- tural (e.g., lack of ICU mobility culture, staff buy-in, expertise). The positive outcomes in our study may be explained by our use of strategies specifically targeting these barriers, including: 1) reducing sedative use and delirium (B-AD, period 1) “be- fore” implementation of EC (period 2) so patients were more awake and could actively engage in mobilization; 2) mobiliza- tion of patients within 1 day of ICU admission to prevent the development of new immobility/weakness; 3) developing an interdisciplinary mobility protocol with prespecified roles and responsibilities before EC implementation; 4) obtaining admin- istrative buy-in to finance dedicated rehabilitation staff and re- habilitation equipment; 5) interdisciplinary simulation training of mobilization scenarios to enhance skills, improve interdisci- plinary communication, and increase buy-in; 6) daily interdis- ciplinary coordination of staff and bundle components; and 7) including local nursing, respiratory, rehabilitation champions in protocol development, training, and dissemination. Our large effect size may also be explained by our use of DiD analysis which mitigates against secular trends that can con- found pre-post study designs (21, 23). In addition, prior studies implemented bundle components all at once, which may reduce overall bundle compliance and offset clinical benefit if com- ponents are not fully adopted (25, 45). Barnes-Daly et al (22) showed that for every 10% increase in ABCDEF bundle com- pliance, odds for hospital survival increased by 7%. Finally, our study excluded non-MV patients from analysis since only a frac- tion of the bundle (i.e., D, E) applies to them. Their inclusion in prior studies may have diminished any effect seen (21, 23). TABLE 3. Difference-in-Differences Estimates of Change in Clinical and Cost Outc omes After AD Implementation (Baseline vs Period 1) and EC Implementation (Period 1 vs Period 2) in Mechanically Ventilated Patients a Outcome Measure Full Bundle ICU Minus Partial Bundle ICU Baseline vs Period 1 % Change (95% CI) (B minus B-AD) pPeriod 1 vs Period 2 % Change (95% CI) (B-AD minus B-AD-EC) p Clinical outcomes Duration of mechanical ventilation 7.2 (–3.3 to 18.9) 0.07–22.3 (–22.5 to –22.0) < 0.001 ICU LOS 3.0 (–6.5 to 13.5)0.16–10.3 (–15.6 to –4.7) 0.03 Hospital LOS b 5.9 (4.6–7.2) 0.01–7.8 (–8.7 to –6.9) 0.006 Cost outcomes Average daily ICU cost 2.69 (–4.9 to 10.9)0.504.4 (–4.5 to 14.1) 0.34 Total ICU cost –0.47 (–22.3 to 27.4)0.97–24.2 (–41.4 to –2.0) 0.03 Total hospital cost –0.06 (–21.4 to 27.0)0.10–30.2 (–46.1 to –9.5) 0.007 A = awakening from sedation, B = spontaneous breathing trial, C = coordination of bundle components, D = delir ium monitoring and management, E = early mobilization, LOS = length of stay. a Both models are adjusted for age, race, ethnicity, prehospital residence, admission location, Charlson Comorbidity Index, primary ad mitting diagnosis, and Acute Physiology and Chronic Health Evaluation IV. b Hospital LOS defined as index ICU LOS + post-ICU LOS. Baseline vs period 1 compares clinical and cost outcomes after AD was imp lemented in both full and partial bundle ICUs. Period 1 vs period 2 compares clinical and cost outcomes in full bundle vs partial bundle ICUs after EC was implemented in full bundle ICU only. Interpretive example: 1) implementation of AD in both ICUs was associated with no differential change in total hospital cost and 2) implementation of EC in full bundle ICU only was associated with a 7.8% reduction in hospital LOS. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Hsieh et al 892 www.ccmjournal.org July 2019 • Volume 47 • Number 7 This is the first report on the financial impact of the en- tire ABCDE bundle. Prior analyses on the awakening/de- lirium bundle components suggested cost savings, but studies on early mobilization have reported conflicting results (35, 46, 47). Using patient-level data, we found that adding EC to B-AD led to substantial cost savings which appear to be prima- rily explained by reductions in LOS (as indicated by decreased overall costs but unchanged average daily ICU cost before and after EC implementation). Our finding that EC implementation was associated with shorter ICU and hospital LOS is consistent with prior random- ized controlled trials (RCTs) and quality improvement studies (17, 35, 48). However, two recent RCTs on early mobilization found no effect on hospital LOS. In Morris et al (49), a seda- tion protocol was not used, which may have limited the effi- cacy of spontaneous breathing trials and early mobilization. In Moss et al (50), mobilization was initiated 8 days after ICU admission (vs 1 d in this study). Given the rapid degradation of muscle of critically ill patients, mobilization may be less effec- tive if initiated after muscle loss has occurred (4). Our study highlights several areas for future research. These include assessment of patient-centered outcomes such as short and long-term disability and readmission rate, determination of return on investment, cost analyses accounting for payer status, and evaluation of bundle dissemination and sustaina- bility. The ABCDE bundle has been reframed since our 2014 study to include assessment, management and prevention of pain, and (F)amily empowerment and engagement (“F” in ABCDEF) (28). Future studies will need to reconcile our find- ings with the updated components. This study has several strengths. Our DiD approach allowed us to adjust for secular trends which could have confounded prior historically-controlled studies. We also fulfilled a ma- jority of the rigorous assumptions required for internal va- lidity of the DiD estimates. Our cost data were generated from costs attributed to individual patients rather than assumptions based on average published costs. Finally, our study evaluated one of the largest cohorts to date. This study has some limitations. Despite adjusting for patient characteristics, unmeasured differences and/or changes in cohort composition could have impacted our results. We also did not in- clude discharge location in our model. Our study was conducted in a single medical center, which may limit generalizability. For example, the bundle’s impact on quality metrics (e.g., pressure ulcers) may be greater in ICUs with higher rates at baseline than sites that have already achieved low rates. There was potential for cross-contamination of practices between the two ICUs. However, cross-contamination would have biased the estimates toward the null. Because cost-to-charge ratios change across cal- endar years, we were unable to compare costs between the same seasonal periods and needed to use a smaller cohort for the cost analyses. Although changes in processes of care were demon- strated in the full bundle ICU, data were not collected in the par – tial bundle ICU for comparison. Finally, we were unable to fulfill the parallel trend assumption for hospital LOS as it increased in the full bundle ICU relative to the partial bundle ICU in period 1. However, this would bias our findings “toward the null” making it more difficult to demonstrate subsequent decreased hospital LOS after EC implementation in period 2. Because hospital LOS decreased despite this bias, our results may underestimate the full impact of ABCDE bundle implementation. CONCLUSIONS This study demonstrates that the complex ABCDE bundle can be successfully implemented into routine care. We showed that the addition of early mobilization and bundle coordination to an established targeted sedation and de- lirium management program led to substantial reductions in MV duration, LOS, and hospital cost, liberated patients from restraints, and reduced iatrogenic complications. 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