A common data model for the standardization of intensive care unit medication features

Objective

Common data models provide a standard means of describing data for artificial intelligence (AI) applications, but this process has never been undertaken for medications used in the intensive care unit (ICU). We sought to develop a common data model (CDM) for ICU medications to standardize the medication features needed to support future ICU AI efforts.

Materials and Methods

A 9-member, multi-professional team of ICU clinicians and AI experts conducted a 5-round modified Delphi process employing conference calls, web-based communication, and electronic surveys to define the most important medication features for AI efforts. Candidate ICU medication features were generated through group discussion and then independently scored by each team member based on relevance to ICU clinical decision-making and feasibility for collection and coding. A key consideration was to ensure the final ontology both distinguished unique medications and met Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles.

Results

Using a list of 889 ICU medications, the team initially generated 106 different medication features, and 71 were ranked as being core features for the CDM. Through this process, 106 medication features were assigned to 2 key feature domains: drug product-related (n = 43) and clinical practice-related (n = 63). Each feature included a standardized definition and suggested response values housed in the electronic data library. This CDM for ICU medications is available online.

Conclusion

The CDM for ICU medications represents an important first step for the research community focused on exploring how AI can improve patient outcomes and will require ongoing engagement and refinement.

Clinical Impact of the Implementation Strategies Used to Apply the 2013 Pain, Agitation/Sedation, Delirium or 2018 Pain, Agitation/Sedation, Delirium, Immobility, Sleep Disruption Guideline Recommendations: A Systematic Review and Meta-Analysis

OBJECTIVES

To summarize the effectiveness of implementation strategies for ICU execution of recommendations from the 2013 Pain, Agitation/Sedation, Delirium (PAD) or 2018 PAD, Immobility, Sleep Disruption (PADIS) guidelines.

DATA SOURCES

PubMed, CINAHL, Scopus, and Web of Science were searched from January 2012 to August 2023. The protocol was registered with PROSPERO (CRD42020175268).

STUDY SELECTION

Articles were included if: 1) design was randomized or cohort, 2) adult population evaluated, 3) employed recommendations from greater than or equal to two PAD/PADIS domains, and 4) evaluated greater than or equal to 1 of the following outcome(s): short-term mortality, delirium occurrence, mechanical ventilation (MV) duration, or ICU length of stay (LOS).

DATA EXTRACTION

Two authors independently reviewed articles for eligibility, number of PAD/PADIS domains, quality according to National Heart, Lung, and Blood Institute assessment tools, implementation strategy use (including Assess, prevent, and manage pain; Both SAT and SBT; Choice of analgesia and sedation; Delirium: assess, prevent, and manage; Early mobility and exercise; Family engagement and empowerment [ABCDEF] bundle) by Cochrane Effective Practice and Organization of Care (EPOC) category, and clinical outcomes. Certainty of evidence was assessed using Grading of Recommendations Assessment, Development, and Evaluation.

DATA SYNTHESIS

Among the 25 of 243 (10.3%) full-text articles included ( n = 23,215 patients), risk of bias was high in 13 (52%). Most studies were cohort ( n = 22, 88%). A median of 5 (interquartile range [IQR] 4-7) EPOC strategies were used to implement recommendations from two (IQR 2-3) PAD/PADIS domains. Cohort and randomized studies were pooled separately. In the cohort studies, use of EPOC strategies was not associated with a change in mortality (risk ratio [RR] 1.01; 95% CI, 0.9-1.12), or delirium (RR 0.92; 95% CI, 0.82-1.03), but was associated with a reduction in MV duration (weighted mean difference [WMD] -0.84 d; 95% CI, -1.25 to -0.43) and ICU LOS (WMD -0.77 d; 95% CI, -1.51 to 0.04). For randomized studies, EPOC strategy use was associated with reduced mortality and MV duration but not delirium or ICU LOS.

CONCLUSIONS

Using multiple implementation strategies to adopt PAD/PADIS guideline recommendations may reduce mortality, duration of MV, and ICU LOS. Further prospective, controlled studies are needed to identify the most effective strategies to implement PAD/PADIS recommendations.

Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction

INTRODUCTION

Intravenous (IV) medications are a fundamental cause of fluid overload (FO) in the intensive care unit (ICU); however, the association between IV medication use (including volume), administration timing, and FO occurrence remains unclear.

METHODS

This retrospective cohort study included consecutive adults admitted to an ICU ≥72 hours with available fluid balance data. FO was defined as a positive fluid balance ≥7% of admission body weight within 72 hours of ICU admission. After reviewing medication administration record (MAR) data in three-hour periods, IV medication exposure was categorized into clusters using principal component analysis (PCA) and Restricted Boltzmann Machine (RBM). Medication regimens of patients with and without FO were compared within clusters to assess for temporal clusters associated with FO using the Wilcoxon rank sum test. Exploratory analyses of the medication cluster most associated with FO for medications frequently appearing and used in the first 24 hours was conducted.

RESULTS

FO occurred in 127/927 (13.7%) of the patients enrolled. Patients received a median (IQR) of 31 (13-65) discrete IV medication administrations over the 72-hour period. Across all 47,803 IV medication administrations, ten unique IV medication clusters were identified with 121-130 medications in each cluster. Among the ten clusters, cluster 7 had the greatest association with FO; the mean number of cluster 7 medications received was significantly greater in patients in the FO cohort compared to patients who did not experience FO (25.6 vs.10.9. p<0.0001). 51 of the 127 medications in cluster 7 (40.2%) appeared in > 5 separate 3-hour periods during the 72-hour study window. The most common cluster 7 medications included continuous infusions, antibiotics, and sedatives/analgesics. Addition of cluster 7 medications to a prediction model with APACHE II score and receipt of diuretics improved the ability for the model to predict fluid overload (AUROC 5.65, p =0.0004).

CONCLUSIONS

Using ML approaches, a unique IV medication cluster was strongly associated with FO. Incorporation of this cluster improved the ability to predict development of fluid overload in ICU patients compared with traditional prediction models. This method may be further developed into real-time clinical applications to improve early detection of adverse outcomes.

The Delphi Delirium Management Algorithms. A practical tool for clinicians, the result of a modified Delphi expert consensus approach

Delirium is common in hospitalised patients, and there is currently no specific treatment. Identifying and treating underlying somatic causes of delirium is the first priority once delirium is diagnosed. Several international guidelines provide clinicians with an evidence-based approach to screening, diagnosis and symptomatic treatment. However, current guidelines do not offer a structured approach to identification of underlying causes. A panel of 37 internationally recognised delirium experts from diverse medical backgrounds worked together in a modified Delphi approach via an online platform. Consensus was reached after five voting rounds. The final product of this project is a set of three delirium management algorithms (the Delirium Delphi Algorithms), one for ward patients, one for patients after cardiac surgery and one for patients in the intensive care unit.

A Rapid Systematic Review of Pharmacologic Sleep Promotion Modalities in the Intensive Care Unit

Background: The Society of Critical Care Medicine Clinical Practice Guidelines for Management of Pain, Agitation, Delirium, Immobility, and Sleep recommend protocolized non-pharmacologic sleep improvement. Pharmacologic interventions are frequently initiated to promote sleep but the evidence supporting these strategies remains controversial. Purpose: To systematically search and synthesize evidence evaluating pharmacologic sleep promotion modalities in critically ill adults. Methods: A rapid systematic review protocol was used to search Medline, Cochrane Library, and Embase for reports published through October 2022. We included randomized controlled trials (RCTs) and before-and-after cohort studies evaluating pharmacologic modalities intended to improve sleep in adult intensive care unit (ICU) patients. Sleep-related endpoints were the primary outcome of interest. Study and patient characteristics and relevant safety and non-sleep outcome data were also collected. The Cochrane Collaboration Risk of Bias or Risk of Bias in Non-Randomized Studies of Interventions were used to assess the risk of bias for all included studies. Results: Sixteen studies (75% RCTs) enrolling 2573 patients were included; 1207 patients were allocated to the pharmacologic sleep intervention. Most studies utilized dexmedetomidine (7/16; total n = 505 patients) or a melatonin agonist (6/16; total n = 592 patients). Only half of the studies incorporated a sleep promotion protocol as standard of care. Most (11/16, 68.8%) studies demonstrated a significant improvement in ≥1 sleep endpoint (n = 5 dexmedetomidine, n = 3 melatonin agonists, n = 2 propofol/benzodiazepines). Risk of bias was generally low for RCTs and moderate-severe for cohort studies. Conclusions: Dexmedetomidine and melatonin agonists are the most studied pharmacologic sleep promotion modalities, but current evidence does not support their routine administration in the ICU to improve sleep. Future RCTs evaluating pharmacologic modalities for ICU sleep should consider patients' baseline and ICU risks for disrupted sleep, incorporate a non-pharmacologic sleep improvement protocol, and evaluate the effect of these medication interventions on circadian rhythm, physiologic sleep, patient-perceived sleep quality, and delirium.

Relationship Between Pain and Delirium in Critically Ill Adults

OBJECTIVES

Although opioids are frequently used to treat pain, and are an important risk for ICU delirium, the association between ICU pain itself and delirium remains unclear. We sought to evaluate the relationship between ICU pain and delirium.

DESIGN

Prospective cohort study.

SETTING

A 32-bed academic medical-surgical ICU.

PATIENTS

Critically ill adults (n = 4,064) admitted greater than or equal to 24 hours without a condition hampering delirium assessment.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Daily mental status was classified as arousable without delirium, delirium, or unarousable. Pain was assessed six times daily in arousable patients using a 0-10 Numeric Rating Scale (NRS) or the Critical Care Pain Observation Tool (CPOT); daily peak pain score was categorized as no (NRS = 0/CPOT = 0), mild (NRS = 1-3/CPOT = 1-2), moderate (NRS = 4-6/CPOT = 3-4), or severe (NRS = 7-10/CPOT = 5-8) pain. To address missingness, a Multiple Imputation by Chained Equations approach that used available daily pain severity and 19 pain predictors was used to generate 25 complete datasets. Using a first-order Markov model with a multinomial logistic regression analysis, that controlled for 11 baseline/daily delirium risk factors and considered the competing risks of unarousability and ICU discharge/death, the association between peak daily pain and next-day delirium in each complete dataset was evaluated.

RESULTS

Among 14,013 ICU days (contributed by 4,064 adults), delirium occurred on 2,749 (19.6%). After pain severity imputation on 1,818 ICU days, mild, moderate, and severe pain were detected on 2,712 (34.1%), 1,682 (21.1%), and 894 (11.2%) of the no-delirium days, respectively, and 992 (36.1%), 513 (18.6%), and 27 (10.1%) of delirium days (p = 0.01). The presence of any pain (mild, moderate, or severe) was not associated with a transition from awake without delirium to delirium (aOR 0.96; 95% CI, 0.76-1.21). This association was similar when days with only mild, moderate, or severe pain were considered. All results were stable after controlling for daily opioid dose.

CONCLUSIONS

After controlling for multiple delirium risk factors, including daily opioid use, pain may not be a risk factor for delirium in the ICU. Future prospective research is required.

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU

Fluid overload, while common in the ICU and associated with serious sequelae, is hard to predict and may be influenced by ICU medication use. Machine learning (ML) approaches may offer advantages over traditional regression techniques to predict it. We compared the ability of traditional regression techniques and different ML-based modeling approaches to identify clinically meaningful fluid overload predictors. This was a retrospective, observational cohort study of adult patients admitted to an ICU ≥ 72 h between 10/1/2015 and 10/31/2020 with available fluid balance data. Models to predict fluid overload (a positive fluid balance ≥ 10% of the admission body weight) in the 48-72 h after ICU admission were created. Potential patient and medication fluid overload predictor variables (n = 28) were collected at either baseline or 24 h after ICU admission. The optimal traditional logistic regression model was created using backward selection. Supervised, classification-based ML models were trained and optimized, including a meta-modeling approach. Area under the receiver operating characteristic (AUROC), positive predictive value (PPV), and negative predictive value (NPV) were compared between the traditional and ML fluid prediction models. A total of 49 of the 391 (12.5%) patients developed fluid overload. Among the ML models, the XGBoost model had the highest performance (AUROC 0.78, PPV 0.27, NPV 0.94) for fluid overload prediction. The XGBoost model performed similarly to the final traditional logistic regression model (AUROC 0.70; PPV 0.20, NPV 0.94). Feature importance analysis revealed severity of illness scores and medication-related data were the most important predictors of fluid overload. In the context of our study, ML and traditional models appear to perform similarly to predict fluid overload in the ICU. Baseline severity of illness and ICU medication regimen complexity are important predictors of fluid overload.

Critical Care Pharmacist Attitudes and Perceptions of Neuromuscular Blocker Infusions in ARDS

BACKGROUND

Current critical care pharmacist (CCP) practices and perceptions related to neuromuscular infusion (NMBI) use for acute respiratory distress syndrome (ARDS) maybe different with the COVID-19 pandemic and the publication of 2020 NMBI practice guidelines.

OBJECTIVE

To evaluate CCP practices and perceptions regarding NMBI use for patients with moderate-severe ARDS.

METHODS

We developed, tested, and electronically administered a questionnaire (7 parent-, 42 sub-questions) to 409 American College of Clinical Pharmacy (ACCP) Critical Care Practice and Research Network members in 12 geographically diverse states. The questionnaire focused on adults with moderate-severe ARDS (PaO2:FiO2<150) whose causes of dyssynchrony were addressed. Two reminders were sent at 10-day intervals.

RESULTS

Respondents [131/409 (32%)] primarily worked in a medical intensive care unit (ICU) 102 (78%). Compared to COVID-negative(-) ARDS patients, COVID positive(+) ARDS patients were twice as likely to receive a NMBI (34 ± 18 vs.16 ± 17%; P < 0.01). Respondents somewhat/strongly agreed a NMBI should be reserved until after trials of deep sedation (112, 86%) or proning (92, 81%) and that NMBI reduced barotrauma (88, 67%), dyssynchrony (87, 66%), and plateau pressure (79, 60%). Few respondents somewhat/strongly agreed that a NMBI should be initiated at ARDS onset (23, 18%) or that NMBI reduced 90-day mortality (12, 10%). Only 2/14 potential NMBI risks [paralysis awareness (101, 82%) and prolonged muscle weakness (84, 68%)] were frequently reported to be of high/very high concern. Multiple NMBI titration targets were assessed as very/extremely important including arterial pH (109, 88%), dyssynchrony (107, 86%), and PaO2: FiO2 ratio (82, 66%). Train-of-four (55, 44%) and BIS monitoring (36, 29%) were deemed less important. Preferred NMBI discontinuation criteria included absence of dysschrony (84, 69%) and use ≥48 hour (72, 59%).

CONCLUSIONS AND RELEVANCE

Current critical care pharmacists believe NMBI for ARDS patients are best reserved until after trials of deep sedation or proning; unique considerations exist in COVID+ patients. Our results should be considered when ICU NMBI protocols are being developed and bedside decisions regarding NMBI use in ARDS are being formulated.

A pharmacogenetic precision medicine approach to analgesia and sedation optimization in critically ill adults

Precision medicine is a growing field in critical care. Research increasingly demonstrated pharmacogenomic variability to be an important determinant of analgesic and sedative drug response in the intensive care unit (ICU). Genome-wide association and candidate gene finding studies suggest analgesic and sedatives tailored to an individual's genetic makeup, environmental adaptations, in addition to several other patient- and drug-related factors, will maximize effectiveness and help mitigate harm. However, the number of pharmacogenetic studies in ICU patients remains small and no prospective studies have been published using pharmacogenomic data to optimize analgesic or sedative therapy in critically ill patients. Current recommendations for treating ICU pain and agitation are based on controlled studies having low external validity, including the failure to consider pharmacogenomic factors affecting response. Use of a precision medicine approach to individualize pharmacotherapy focused on optimizing ICU patient comfort and safety may improve the outcomes of critically ill adults. Additionally, benefits and risks of analgesic and/or sedative therapy in an individual may be informed with large, standardized datasets. The purpose of this review was to describe a precision medicine approach focused on optimizing analgesic and sedative therapy in individual ICU patients to optimize clinical outcomes and reduce safety concerns.

Data Missingness Reporting and Use of Methods to Address It in Critical Care Cohort Studies

IMPORTANCE

Failure to recognize and address data missingness in cohort studies may lead to biased results. Although Strengthening the Reporting of Observational Studies in Epidemiology reporting guidelines advocate data missingness reporting, the degree to which missingness is reported and addressed in the critical care literature remains unclear.

OBJECTIVES

To review published ICU cohort studies to characterize data missingness reporting and the use of methods to address it.

DESIGN SETTING AND PARTICIPANTS

We searched the 2022 table of contents of 29 critical care/critical care subspecialty journals having a 2021 impact factor greater than or equal to 3 to identify published prospective clinical or retrospective database cohort studies enrolling greater than or equal to 100 patients.

MAIN OUTCOMES AND MEASURES

In duplicate, two trained researchers conducted a manuscript/supplemental material PDF word search for "missing*" and extracted study type, patient age, ICU type, sample size, missingness reporting, and the use of methods to address it.

RESULTS

A total of 656 studies were reviewed. Of the 334 of 656 (50.9%) studies mentioning missingness, missingness was reported for greater than or equal to 1 variable in 234 (70.1%) and it exceeded 5% for at least one variable in 160 (47.9%). Among the 334 studies mentioning missingness, 88 (26.3%) used exclusion criteria, 36 (10.8%) used complete-case analysis, and 164 (49.1%) used a formal method to avoid missingness. In these 164 studies, imputation only was used in 100 (61.0%), an analytic strategy only in 24 (14.6%), and both in 40 (24.4%). Only missingness greater than 5% (in ≥ 1 variable) was independently associated with greater use of a missingness method (adjusted odds ratio 2.91; 95% CI, 1.85-4.60). Among 140 studies using imputation, multiple imputation was used in 87 studies (62.1%) and simple imputation in 49 studies (35.0%). For the 64 studies using an analytic method, 12 studies (18.8%) assigned missingness as an unknown category, whereas sensitivity analysis was used in 47 studies (73.4%).

CONCLUSIONS AND RELEVANCE

Among published critical care cohort studies, only half mentioned result missingness, one-third reported actual missingness and only one-quarter used a method to manage missingness. Educational strategies to promote missingness reporting and resolution methods are required.

Efficacy of haloperidol to decrease the burden of delirium in adult critically ill patients: the EuRIDICE randomized clinical trial

BACKGROUND

The role of haloperidol as treatment for ICU delirium and related symptoms remains controversial despite two recent large controlled trials evaluating its efficacy and safety. We sought to determine whether haloperidol when compared to placebo in critically ill adults with delirium reduces days with delirium and coma and improves delirium-related sequelae.

METHODS

This multi-center double-blind, placebo-controlled randomized trial at eight mixed medical-surgical Dutch ICUs included critically ill adults with delirium (Intensive Care Delirium Screening Checklist ≥ 4 or a positive Confusion Assessment Method for the ICU) admitted between February 2018 and January 2020. Patients were randomized to intravenous haloperidol 2.5 mg or placebo every 8 h, titrated up to 5 mg every 8 h if delirium persisted until ICU discharge or up to 14 days. The primary outcome was ICU delirium- and coma-free days (DCFDs) within 14 days after randomization. Predefined secondary outcomes included the protocolized use of sedatives for agitation and related behaviors, patient-initiated extubation and invasive device removal, adverse drug associated events, mechanical ventilation, ICU length of stay, 28-day mortality, and long-term outcomes up to 1-year after randomization.

RESULTS

The trial was terminated prematurely for primary endpoint futility on DSMB advice after enrolment of 132 (65 haloperidol; 67 placebo) patients [mean age 64 (15) years, APACHE IV score 73.1 (33.9), male 68%]. Haloperidol did not increase DCFDs (adjusted RR 0.98 [95% CI 0.73-1.31], p = 0.87). Patients treated with haloperidol (vs. placebo) were less likely to receive benzodiazepines (adjusted OR 0.41 [95% CI 0.18-0.89], p = 0.02). Effect measures of other secondary outcomes related to agitation (use of open label haloperidol [OR 0.43 (95% CI 0.12-1.56)] and other antipsychotics [OR 0.63 (95% CI 0.29-1.32)], self-extubation or invasive device removal [OR 0.70 (95% CI 0.22-2.18)]) appeared consistently more favorable with haloperidol, but the confidence interval also included harm. Adverse drug events were not different. Long-term secondary outcomes (e.g., ICU recall and quality of life) warrant further study.

CONCLUSIONS

Haloperidol does not reduce delirium in critically ill delirious adults. However, it may reduce rescue medication requirements and agitation-related events in delirious ICU patients warranting further evaluation.

TRIAL REGISTRATION

ClinicalTrials.gov (#NCT03628391), October 9, 2017.

Frequency of screening and SBT Technique Trial-North American Weaning Collaboration (FAST-NAWC): an update to the protocol and statistical analysis plan

BACKGROUND

This update summarizes key changes made to the protocol for the Frequency of Screening and Spontaneous Breathing Trial (SBT) Technique Trial-North American Weaning Collaborative (FAST-NAWC) trial since the publication of the original protocol. This multicenter, factorial design randomized controlled trial with concealed allocation, will compare the effect of both screening frequency (once vs. at least twice daily) to identify candidates to undergo a SBT and SBT technique [pressure support + positive end-expiratory pressure vs. T-piece] on the time to successful extubation (primary outcome) in 760 critically ill adults who are invasively ventilated for at least 24 h in 20 North American intensive care units.

METHODS/DESIGN

Protocols for the pilot, factorial design trial and the full trial were previously published in J Clin Trials ( https://doi.org/10.4172/2167-0870.1000284 ) and Trials (https://doi: 10.1186/s13063-019-3641-8). As planned, participants enrolled in the FAST pilot trial will be included in the report of the full FAST-NAWC trial. In response to the onset of the coronavirus disease of 2019 (COVID-19) pandemic when approximately two thirds of enrollment was complete, we revised the protocol and consent form to include critically ill invasively ventilated patients with COVID-19. We also refined the statistical analysis plan (SAP) to reflect inclusion and reporting of participants with and without COVID-19. This update summarizes the changes made and their rationale and provides a refined SAP for the FAST-NAWC trial. These changes have been finalized before completion of trial follow-up and the commencement of data analysis.

TRIAL REGISTRATION

Clinical Trials.gov NCT02399267.

Evaluation of medication regimen complexity as a predictor for mortality

While medication regimen complexity, as measured by a novel medication regimen complexity-intensive care unit (MRC-ICU) score, correlates with baseline severity of illness and mortality, whether the MRC-ICU improves hospital mortality prediction is not known. After characterizing the association between MRC-ICU, severity of illness and hospital mortality we sought to evaluate the incremental benefit of adding MRC-ICU to illness severity-based hospital mortality prediction models. This was a single-center, observational cohort study of adult intensive care units (ICUs). A random sample of 991 adults admitted ≥ 24 h to the ICU from 10/2015 to 10/2020 were included. The logistic regression models for the primary outcome of mortality were assessed via area under the receiver operating characteristic (AUROC). Medication regimen complexity was evaluated daily using the MRC-ICU. This previously validated index is a weighted summation of medications prescribed in the first 24 h of ICU stay [e.g., a patient prescribed insulin (1 point) and vancomycin (3 points) has a MRC-ICU = 4 points]. Baseline demographic features (e.g., age, sex, ICU type) were collected and severity of illness (based on worst values within the first 24 h of ICU admission) was characterized using both the Acute Physiology and Chronic Health Evaluation (APACHE II) and the Sequential Organ Failure Assessment (SOFA) score. Univariate analysis of 991 patients revealed every one-point increase in the average 24-h MRC-ICU score was associated with a 5% increase in hospital mortality [Odds Ratio (OR) 1.05, 95% confidence interval 1.02-1.08, p = 0.002]. The model including MRC-ICU, APACHE II and SOFA had a AUROC for mortality of 0.81 whereas the model including only APACHE-II and SOFA had a AUROC for mortality of 0.76. Medication regimen complexity is associated with increased hospital mortality. A prediction model including medication regimen complexity only modestly improves hospital mortality prediction.

Pharmacophenotype identification of intensive care unit medications using unsupervised cluster analysis of the ICURx common data model

BACKGROUND

Identifying patterns within ICU medication regimens may help artificial intelligence algorithms to better predict patient outcomes; however, machine learning methods incorporating medications require further development, including standardized terminology. The Common Data Model for Intensive Care Unit (ICU) Medications (CDM-ICURx) may provide important infrastructure to clinicians and researchers to support artificial intelligence analysis of medication-related outcomes and healthcare costs. Using an unsupervised cluster analysis approach in combination with this common data model, the objective of this evaluation was to identify novel patterns of medication clusters (termed 'pharmacophenotypes') correlated with ICU adverse events (e.g., fluid overload) and patient-centered outcomes (e.g., mortality).

METHODS

This was a retrospective, observational cohort study of 991 critically ill adults. To identify pharmacophenotypes, unsupervised machine learning analysis with automated feature learning using restricted Boltzmann machine and hierarchical clustering was performed on the medication administration records of each patient during the first 24 h of their ICU stay. Hierarchical agglomerative clustering was applied to identify unique patient clusters. Distributions of medications across pharmacophenotypes were described, and differences among patient clusters were compared using signed rank tests and Fisher's exact tests, as appropriate.

RESULTS

A total of 30,550 medication orders for the 991 patients were analyzed; five unique patient clusters and six unique pharmacophenotypes were identified. For patient outcomes, compared to patients in Clusters 1 and 3, patients in Cluster 5 had a significantly shorter duration of mechanical ventilation and ICU length of stay (p < 0.05); for medications, Cluster 5 had a higher distribution of Pharmacophenotype 1 and a smaller distribution of Pharmacophenotype 2, compared to Clusters 1 and 3. For outcomes, patients in Cluster 2, despite having the highest severity of illness and greatest medication regimen complexity, had the lowest overall mortality; for medications, Cluster 2 also had a comparably higher distribution of Pharmacophenotype 6.

CONCLUSION

The results of this evaluation suggest that patterns among patient clusters and medication regimens may be observed using empiric methods of unsupervised machine learning in combination with a common data model. These results have potential because while phenotyping approaches have been used to classify heterogenous syndromes in critical illness to better define treatment response, the entire medication administration record has not been incorporated in those analyses. Applying knowledge of these patterns at the bedside requires further algorithm development and clinical application but may have the future potential to be leveraged in guiding medication-related decision making to improve treatment outcomes.

Causes, Consequences, and Treatments of Sleep and Circadian Disruption in the ICU: An Official American Thoracic Society Research Statement

Background: Sleep and circadian disruption (SCD) is common and severe in the ICU. On the basis of rigorous evidence in non-ICU populations and emerging evidence in ICU populations, SCD is likely to have a profound negative impact on patient outcomes. Thus, it is urgent that we establish research priorities to advance understanding of ICU SCD. Methods: We convened a multidisciplinary group with relevant expertise to participate in an American Thoracic Society Workshop. Workshop objectives included identifying ICU SCD subtopics of interest, key knowledge gaps, and research priorities. Members attended remote sessions from March to November 2021. Recorded presentations were prepared and viewed by members before Workshop sessions. Workshop discussion focused on key gaps and related research priorities. The priorities listed herein were selected on the basis of rank as established by a series of anonymous surveys. Results: We identified the following research priorities: establish an ICU SCD definition, further develop rigorous and feasible ICU SCD measures, test associations between ICU SCD domains and outcomes, promote the inclusion of mechanistic and patient-centered outcomes within large clinical studies, leverage implementation science strategies to maximize intervention fidelity and sustainability, and collaborate among investigators to harmonize methods and promote multisite investigation. Conclusions: ICU SCD is a complex and compelling potential target for improving ICU outcomes. Given the influence on all other research priorities, further development of rigorous, feasible ICU SCD measurement is a key next step in advancing the field.

Physicians' attitudes and perceptions of neuromuscular blocker infusions in ARDS

PURPOSE

The perceptions and practices of ICU physicians regarding initiating neuromuscular blocker infusions (NMBI) in acute respiratory distress syndrome (ARDS) may not be evidence-based amidst the surge of severe ARDS during the SARS-CoV-2 pandemic and new practice guidelines. We identified ICU physicians' perspectives and practices regarding NMBI use in adults with moderate-severe ARDS.

MATERIALS AND METHODS

After extensive development and testing, an electronic survey was distributed to 342 ICU physicians from three geographically-diverse U.S. health systems(n = 12 hospitals).

RESULTS

The 173/342 (50.5%) respondents (75% medical) somewhat/strongly agreed a NMBI should be reserved until: after a trial of deep sedation (142, 82%) or proning (59, 34%) and be dose-titrated based on train-of-four monitoring (107, 62%). Of 14 potential NMBI risks, 2 were frequently reported to be of high/very high concern: prolonged muscle weakness with steroid use (135, 79%) and paralysis awareness due to inadequate sedation (114, 67%). Absence of dyssychrony (93, 56%) and use ≥48 h (87, 53%) were preferred NMBI stopping criteria. COVID-19 + ARDS patients were twice as likely to receive a NMBI (56 ± 37 vs. 28 ± 19%, p < 0.01).

CONCLUSIONS

Most intensivists agreed NMBI in ARDS should be reserved until after a deep sedation trial. Stopping criteria remain poorly defined. Unique considerations exist regarding the role of paralysis in COVID-19+ ARDS.

Dexmedetomidine vs other sedatives in critically ill mechanically ventilated adults: a systematic review and meta-analysis of randomized trials

Conventional gabaminergic sedatives such as benzodiazepines and propofol are commonly used in mechanically ventilated patients in the intensive care unit (ICU). Dexmedetomidine is an alternative sedative that may achieve lighter sedation, reduce delirium, and provide analgesia. Our objective was to perform a comprehensive systematic review summarizing the large body of evidence, determining if dexmedetomidine reduces delirium compared to conventional sedatives. We searched MEDLINE, EMBASE, CENTRAL, ClinicalTrials.gov and the WHO ICTRP from inception to October 2021. Independent pairs of reviewers identified randomized clinical trials comparing dexmedetomidine to other sedatives for mechanically ventilated adults in the ICU. We conducted meta-analyses using random-effects models. The results were reported as relative risks (RRs) for binary outcomes and mean differences (MDs) for continuous outcomes, with corresponding 95% confidence intervals (CIs). In total, 77 randomized trials (n = 11,997) were included. Compared to other sedatives, dexmedetomidine reduced the risk of delirium (RR 0.67, 95% CI 0.55 to 0.81; moderate certainty), the duration of mechanical ventilation (MD - 1.8 h, 95% CI  - 2.89 to  - 0.71; low certainty), and ICU length of stay (MD  - 0.32 days, 95% CI  - 0.42 to  - 0.22; low certainty). Dexmedetomidine use increased the risk of bradycardia (RR 2.39, 95% CI 1.82 to 3.13; moderate certainty) and hypotension (RR 1.32, 95% CI 1.07 to 1.63; low certainty). In mechanically ventilated adults, the use of dexmedetomidine compared to other sedatives, resulted in a lower risk of delirium, and a modest reduction in duration of mechanical ventilation and ICU stay, but increased the risks of bradycardia and hypotension.

Association Between Perioperative Medication Use and Postoperative Delirium and Cognition in Older Adults Undergoing Elective Noncardiac Surgery

BACKGROUND

Postoperative delirium is frequent in older adults and is associated with postoperative neurocognitive disorder (PND). Studies evaluating perioperative medication use and delirium have generally evaluated medications in aggregate and been poorly controlled; the association between perioperative medication use and PND remains unclear. We sought to evaluate the association between medication use and postoperative delirium and PND in older adults undergoing major elective surgery.

METHODS

This is a secondary analysis of a prospective cohort study of adults ≥70 years without dementia undergoing major elective surgery. Patients were interviewed preoperatively to determine home medication use. Postoperatively, daily hospital use of 7 different medication classes listed in guidelines as risk factors for delirium was collected; administration before delirium was verified. While hospitalized, patients were assessed daily for delirium using the Confusion Assessment Method and a validated chart review method. Cognition was evaluated preoperatively and 1 month after surgery using a neurocognitive battery. The association between prehospital medication use and postoperative delirium was assessed using a generalized linear model with a log link function, controlling for age, sex, type of surgery, Charlson comorbidity index, and baseline cognition. The association between daily postoperative medication use (when class exposure ≥5%) and time to delirium was assessed using time-varying Cox models adjusted for age, sex, surgery type, Charlson comorbidity index, Acute Physiology and Chronic Health Evaluation (APACHE)-II score, and baseline cognition. Mediation analysis was utilized to evaluate the association between medication use, delirium, and cognitive change from baseline to 1 month.

RESULTS

Among 560 patients enrolled, 134 (24%) developed delirium during hospitalization. The multivariable analyses revealed no significant association between prehospital benzodiazepine (relative risk [RR], 1.44; 95% confidence interval [CI], 0.85-2.44), beta-blocker (RR, 1.38; 95% CI, 0.94-2.05), NSAID (RR, 1.12; 95% CI, 0.77-1.62), opioid (RR, 1.22; 95% CI, 0.82-1.82), or statin (RR, 1.34; 95% CI, 0.92-1.95) exposure and delirium. Postoperative hospital benzodiazepine use (adjusted hazard ratio [aHR], 3.23; 95% CI, 2.10-4.99) was associated with greater delirium. Neither postoperative hospital antipsychotic (aHR, 1.48; 95% CI, 0.74-2.94) nor opioid (aHR, 0.82; 95% CI, 0.62-1.11) use before delirium was associated with delirium. Antipsychotic use (either presurgery or postsurgery) was associated with a 0.34 point (standard error, 0.16) decrease in general cognitive performance at 1 month through its effect on delirium (P = .03), despite no total effect being observed.

CONCLUSIONS

Administration of benzodiazepines to older adults hospitalized after major surgery is associated with increased postoperative delirium. Association between inhospital, postoperative medication use and cognition at 1 month, independent of delirium, was not detected.

Diarrhea during critical illness: a multicenter cohort study

PURPOSE

To study the incidence, predictors, and outcomes of diarrhea during the stay in the intensive care unit (ICU).

METHODS

Prospective cohort of consecutive adults in the ICU for > 24 h during a 10-week period across 12 intensive care units (ICUs) internationally. The explored outcomes were: (1) incidence of diarrhea, (2) Clostridioides difficile-associated diarrhea (CDAD); (3) ICU and hospital length of stay (LOS) and mortality in patients with diarrhea. We fit generalized linear models to evaluate the predictors, management, morbidity and mortality associated with diarrhea.

RESULTS

Among 1109 patients aged 61.4 (17.5) [mean (standard deviation)] years, 981(88.5%) were medical and 645 (58.2%) were mechanically ventilated. The incidence was 73.8% (818 patients, 73.8%, 95% confidence interval [CI] 71.1-76.6) using the definition of the World Health Organisation (WHO). Incidence varied across definitions (Bristol 53.5%, 95% CI 50.4-56.7; Bliss 37.7%, 95% CI 34.9-40.4). Of 99 patients with diarrhea undergoing CDAD testing, 23 tested positive (2.2% incidence, 95% CI 1.5-3.4). Independent predictors included enteral nutrition (RR 1.23, 95% CI 1.16-1.31, p < 0.001), antibiotic days (RR 1.02, 95% CI 1.02-1.03, p < 0.001), and suppositories (RR 1.14 95% CI 1.06-1.22, p < 0.001). Opiates decreased diarrhea risk (RR 0.76, 95% CI 0.68-0.86, p < 0.001). Diarrhea prompted management modifications (altered enteral nutrition or medications: RR 10.25, 95% CI 5.14-20.45, p < 0.001) or other consequences (fecal management device or CDAD testing: RR 6.16, 95% CI 3.4-11.17, p < 0.001). Diarrhea was associated with a longer time to discharge for ICU or hospital stay, but was not associated with hospital mortality.

CONCLUSION

Diarrhea is common, has several predictors, and prompts changes in patient care, is associated with longer time to discharge but not mortality.

Psychoactive medication therapy and delirium screening in skilled nursing facilities

BACKGROUND

A positive delirium screen at skilled-nursing facility (SNF) admission can trigger a simultaneous diagnosis of Alzheimer's Disease or related dementia (AD/ADRD) and lead to psychoactive medication treatment despite a lack of evidence supporting use.

METHODS

This was a nationwide historical cohort study of 849,086 Medicare enrollees from 2011-2013 who were admitted to the SNF from a hospital without a history of dementia. Delirium was determined through positive Confusion Assessment Method screen and incident AD/ADRD through active diagnosis or claims. Cox proportional hazard models predicted the risk of receiving one of three psychoactive medications (i.e., antipsychotics, benzodiazepines, antiepileptics) within 7 days of SNF admission and within the entire SNF stay.

RESULTS

Of 849,086 newly-admitted SNF patients (62.6% female, mean age 78), 6.1% had delirium (of which 35.4% received an incident diagnosis of AD/ADRD); 12.6% received antipsychotics, 30.4% benzodiazepines, and 5.8% antiepileptics. Within 7 days of admission, patients with delirium and incident dementia were more likely to receive an antipsychotic (relative risk [RR] 3.09; 95% confidence interval [CI] 2.99 to 3.20), or a benzodiazepine (RR 1.23; 95% CI 1.19 to 1.27) than patients without either condition. By the end of the SNF stay, patients with both delirium and incident dementia were more likely to receive an antipsychotic (RR 3.04; 95% CI 2.95 to 3.14) and benzodiazepine (RR 1.32; 95% CI 1.29 to 1.36) than patients without either condition.

CONCLUSION

In this historical cohort, a positive delirium screen was associated with a higher risk of receiving psychoactive medication within 7 days of SNF admission, particularly in patients with an incident AD/ADRD diagnosis. Future research should examine strategies to reduce inappropriate psychoactive medication prescribing in older adults admitted with delirium to SNFs.

Impact of the 2018 Society of Critical Care Medicine Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Guidelines on Nonopioid Analgesic Use and Related Outcomes in Critically Ill Adults After Major Surgery

We compared ICU nonopioid analgesic use, opioid use, and pain before and after Pain, Agitation/Sedation, Delirium, Immobility, and Sleep guideline publication at one academic center among critically ill adults receiving an opioid infusion and greater than or equal to 24 hours of mechanical ventilation after major surgery. The 2017 (n = 77) and 2019 (n = 57) groups were similar at baseline. The 2019 (vs 2017) patients were more likely to receive scheduled IV/oral acetaminophen (84% vs 69%; p = 0.05), less likely to receive a lidocaine patch (33% vs 50%; p = 0.05), and just as likely to receive ketamine (4% vs 3%; p = 1.0), an nonsteroidal anti-inflammatory drug (7% vs 3%; p = 0.26), or gabapentin/pregabalin (16% vs 9%; p = 0.23). Daily average opioid exposure (in IV morphine milligram equivalent) was not different (70 [42–99] [2017] vs 78 mg [49–109 mg]; p = 0.94). The 2019 (vs 2017) group spent more ICU days with severe pain (p = 0.04). At our center, Pain, Agitation/Sedation, Delirium, Immobility, and Sleep guideline publication had little effect on nonopioid analgesic or opioid prescribing practices in critically ill surgical adults.

Sleep-Promotion Bundle Development, Implementation, and Evaluation in Critically Ill Adults: Roles for Pharmacists

OBJECTIVE

To review evidence for intensive care unit (ICU) sleep improvement bundle use, identify preferred sleep bundle components and implementation strategies, and highlight the role for pharmacists in developing and evaluating bundle efforts.

DATA SOURCES

Multiple databases were searched from January 1, 1990, to September 1, 2021, using the MeSH terms sleep, intensive care or critical care, protocol or bundle to identify comparative studies evaluating ICU sleep bundle implementation.

STUDY SELECTION AND DATA EXTRACTION

Study screening, data extraction, and risk-of-bias evaluation were conducted in tandem. The ICU quality improvement literature and Institute for Healthcare Improvement bundle improvement guidance were also reviewed to identify recommended strategies for successful sleep bundle use.

DATA SYNTHESIS

Nine studies (3 randomized, 1 quasi-experimental, 5 before-and-after) were identified. Bundle elements varied and were primarily focused on nonpharmacological interventions designed to be performed during either the day or night; only 2 studies included a medication-based strategy. Five studies were associated with reduced delirium; 2 studies were associated with improved total sleep time and 2 with improved patient-perceived sleep. Pharmacists were involved directly in 4 studies.

RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE

Sleep improvement bundles are recommended for use in all critically ill adults; specific bundle elements and ICU team member roles should be individualized at the institution/ICU level. Pharmacists can help lead bundle development efforts and routinely deliver key elements.

CONCLUSIONS

Pharmacists can play an important role in the development and implementation of ICU sleep bundles. Further research regarding the relative benefit of individual bundle elements on relevant patient outcomes is needed.

Design of Clinical Trials Evaluating Sedation in Critically Ill Adults Undergoing Mechanical Ventilation: Recommendations From Sedation Consortium on Endpoints and Procedures for Treatment, Education, and Research (SCEPTER) Recommendation III

OBJECTIVES

Clinical trials evaluating the safety and effectiveness of sedative medication use in critically ill adults undergoing mechanical ventilation differ considerably in their methodological approach. This heterogeneity impedes the ability to compare results across studies. The Sedation Consortium on Endpoints and Procedures for Treatment, Education, and Research Recommendations convened a meeting of multidisciplinary experts to develop recommendations for key methodologic elements of sedation trials in the ICU to help guide academic and industry clinical investigators.

DESIGN

A 2-day in-person meeting was held in Washington, DC, on March 28-29, 2019, followed by a three-round, online modified Delphi consensus process.

PARTICIPANTS

Thirty-six participants from academia, industry, and the Food and Drug Administration with expertise in relevant content areas, including two former ICU patients attended the in-person meeting, and the majority completed an online follow-up survey and participated in the modified Delphi process.

MEASUREMENTS AND MAIN RESULTS

The final recommendations were iteratively refined based on the survey results, participants' reactions to those results, summaries written by panel moderators, and a review of the meeting transcripts made from audio recordings. Fifteen recommendations were developed for study design and conduct, subject enrollment, outcomes, and measurement instruments. Consensus recommendations included obtaining input from ICU survivors and/or their families, ensuring adequate training for personnel using validated instruments for assessments of sedation, pain, and delirium in the ICU environment, and the need for methodological standardization.

CONCLUSIONS

These recommendations are intended to assist researchers in the design, conduct, selection of endpoints, and reporting of clinical trials involving sedative medications and/or sedation protocols for adult ICU patients who require mechanical ventilation. These recommendations should be viewed as a starting point to improve clinical trials and help reduce methodological heterogeneity in future clinical trials.

Opioid Use Increases the Risk of Delirium in Critically Ill Adults Independently of Pain

Rationale: It is unclear whether opioid use increases the risk of ICU delirium. Prior studies have not accounted for confounding, including daily severity of illness, pain, and competing events that may preclude delirium detection.Objectives: To evaluate the association between ICU opioid exposure, opioid dose, and delirium occurrence.Methods: In consecutive adults admitted for more than 24 hours to the ICU, daily mental status was classified as awake without delirium, delirium, or unarousable. A first-order Markov model with multinomial logistic regression analysis considered four possible next-day outcomes (i.e., awake without delirium, delirium, unarousable, and ICU discharge or death) and 11 delirium-related covariables (baseline: admission type, age, sex, Acute Physiology and Chronic Health Evaluation IV score, and Charlson comorbidity score; daily: ICU day, modified Sequential Organ Failure Assessment, ventilation use, benzodiazepine use, and severe pain). This model was used to quantify the association between opioid use, opioid dose, and delirium occurrence the next day.Measurements and Main Results: The 4,075 adults had 26,250 ICU days; an opioid was administered on 57.0% (n = 14,975), severe pain occurred on 7.0% (n = 1,829), and delirium occurred on 23.5% (n = 6,176). Severe pain was inversely associated with a transition to delirium (odds ratio [OR] 0.72; 95% confidence interval [CI], 0.53-0.97). Any opioid administration in awake patients without delirium was associated with an increased risk for delirium the next day [OR, 1.45; 95% CI, 1.24-1.69]. Each daily 10-mg intravenous morphine-equivalent dose was associated with a 2.4% increased risk for delirium the next day.Conclusions: The receipt of an opioid in the ICU increases the odds of transitioning to delirium in a dose-dependent fashion.

A core outcome set for studies evaluating interventions to prevent and/or treat delirium for adults requiring an acute care hospital admission: an international key stakeholder informed consensus study

BACKGROUND

Trials of interventions to prevent or treat delirium in adults in an acute hospital setting report heterogeneous outcomes. Our objective was to develop international consensus among key stakeholders for a core outcome set (COS) for future trials of interventions to prevent and/or treat delirium in adults with an acute care hospital admission and not admitted to an intensive care unit.

METHODS

A rigorous COS development process was used including a systematic review, qualitative interviews, modified Delphi consensus process, and in-person consensus using nominal group technique (registration http://www.comet - initiative.org/studies/details/796 ). Participants in qualitative interviews were delirium survivors or family members. Participants in consensus methods comprised international representatives from three stakeholder groups: researchers, clinicians, and delirium survivors and family members.

RESULTS

Item generation identified 8 delirium-specific outcomes and 71 other outcomes from 183 studies, and 30 outcomes from 18 qualitative interviews, including 2 that were not extracted from the systematic review. De-duplication of outcomes and formal consensus processes involving 110 experts including researchers (N = 32), clinicians (N = 63), and delirium survivors and family members (N = 15) resulted in a COS comprising 6 outcomes: delirium occurrence and reoccurrence, delirium severity, delirium duration, cognition, emotional distress, and health-related quality of life. Study limitations included exclusion of non-English studies and stakeholders and small representation of delirium survivors/family at the in-person consensus meeting.

CONCLUSIONS

This COS, endorsed by the American and Australian Delirium Societies and European Delirium Association, is recommended for future clinical trials evaluating delirium prevention or treatment interventions in adults presenting to an acute care hospital and not admitted to an intensive care unit.

Characterisation of ICU sleep by a commercially available activity tracker and its agreement with patient-perceived sleep quality

Background

A low-cost, quantitative method to evaluate sleep in the intensive care unit (ICU) that is both feasible for routine clinical practice and reliable does not yet exist. We characterised nocturnal ICU sleep using a commercially available activity tracker and evaluated agreement between tracker-derived sleep data and patient-perceived sleep quality.

Patients and methods

A prospective cohort study was performed in a 40-bed ICU at a community teaching hospital. An activity tracker (Fitbit Charge 2) was applied for up to 7 ICU days in English-speaking adults with an anticipated ICU stay ≥2 days and without mechanical ventilation, sleep apnoea, delirium, continuous sedation, contact isolation or recent anaesthesia. The Richards-Campbell Sleep Questionnaire (RCSQ) was administered each morning by a trained investigator.

Results

Available activity tracker-derived data for each ICU study night (20:00–09:00) (total sleep time (TST), number of awakenings (#AW), and time spent light sleep, deep sleep and rapid eye movement (REM) sleep) were downloaded and analysed. Across the 232 evaluated nights (76 patients), TST and RCSQ data were available for 232 (100%), #AW data for 180 (78%) and sleep stage data for 73 (31%). Agreement between TST (349±168 min) and RCSQ Score was moderate and significant (r=0.34; 95% CI 0.18 to 0.48). Agreement between #AW (median (IQR), 4 (2–9)) and RCSQ Score was negative and non-significant (r=−0.01; 95% CI −0.19 to 0.14). Agreement between time (min) spent in light (259 (182 to 328)), deep (43±29), and REM (47 (28–72)) sleep and RCSQ Score was moderate but non-significant (light (r=0.44, 95% CI −0.05 to 0.36); deep sleep (r=0.44, 95% CI −0.11 to 0.15) and REM sleep (r=0.44; 95% CI −0.21 to 0.21)).

Conclusions

A Fitbit Charge 2 when applied to non-intubated adults in an ICU consistently collects TST data but not #AW or sleep stage data at night. The TST moderately correlates with patient-perceived sleep quality; a correlation between either #AW or sleep stages and sleep quality was not found.

Is there an association between subjective sleep quality and daily delirium occurrence in critically ill adults? A post hoc analysis of a randomised controlled trial

OBJECTIVES

Whether and how delirium and sleep quality in the intensive care unit (ICU) are linked remains unclear. A recent randomised trial reported nocturnal low-dose dexmedetomidine (DEX) significantly reduces incident ICU delirium. Leeds Sleep Evaluation Questionnaire (LSEQ) scores were similar between intervention (DEX; n=50) and control (placebo (PLA); n=50) groups. We measured the association between morning LSEQ and delirium occurrence in the prior 24 hours (retrospective analysis) and the association between morning LSEQ and delirium occurrence in the following 24 hours (predictive analysis).

DESIGN

Post hoc analysis of randomised controlled trial data.

PARTICIPANTS

Adult ICU patients (n=100) underwent delirium screening twice a day using the Intensive Care Delirium Screening Checklist (ICDSC) if Richmond Agitation Sedation Scale (RASS) was ≥-3 and patient-reported sleep quality evaluations at 09:00 daily with the LSEQ if RASS was ≥-1.

OUTCOMES

The analysis included all 24-hour study periods with LSEQ documentation and matched delirium screening in coma-free patients. Separate logistic regression models controlling for age, baseline Acute Physiology and Chronic Health Evaluation II score and DEX/PLA allocation evaluated the association between morning LSEQ and delirium occurrence for both retrospective and predictive analyses.

RESULTS

The 100 patients spent 1115 24-hour periods in the ICU. Coma, delirium and no delirium occurred in 130 (11.7%), 114 (10.2%) and 871 (78.1%), respectively. In the retrospective analysis, when an LSEQ result was preceded by an ICDSC result (439/985 (44.6%) 24-hour periods), delirium occurred during 41/439 (9.3%) periods. On regression analysis, the LSEQ score had no relationship to prior delirium occurrence (OR (per every 1 point average LSEQ change) 0.97, 95% CI 0.72 to 1.31). For the predictive analysis, among the 387/985 (39.1%) 24-hour periods where an LSEQ result was followed by an ICDSC result, delirium occurred during 56/387 (14.5%) periods. On regression analysis, the LSEQ score did not predict subsequent delirium occurrence (OR (per 1 point LSEQ change) 1.02, 95% CI 0.99 to 1.05).

CONCLUSIONS

The sleep quality ICU patients perceive neither affects nor predicts delirium occurrence.

TRIAL REGISTRATION NUMBER

NCT01791296.

Dexmedetomidine or Propofol for Sedation in Mechanically Ventilated Adults with Sepsis

BACKGROUND

Guidelines currently recommend targeting light sedation with dexmedetomidine or propofol for adults receiving mechanical ventilation. Differences exist between these sedatives in arousability, immunity, and inflammation. Whether they affect outcomes differentially in mechanically ventilated adults with sepsis undergoing light sedation is unknown.

METHODS

In a multicenter, double-blind trial, we randomly assigned mechanically ventilated adults with sepsis to receive dexmedetomidine (0.2 to 1.5 μg per kilogram of body weight per hour) or propofol (5 to 50 μg per kilogram per minute), with doses adjusted by bedside nurses to achieve target sedation goals set by clinicians according to the Richmond Agitation-Sedation Scale (RASS, on which scores range from -5 [unresponsive] to +4 [combative]). The primary end point was days alive without delirium or coma during the 14-day intervention period. Secondary end points were ventilator-free days at 28 days, death at 90 days, and age-adjusted total score on the Telephone Interview for Cognitive Status questionnaire (TICS-T; scores range from 0 to 100, with a mean of 50±10 and lower scores indicating worse cognition) at 6 months.

RESULTS

Of 432 patients who underwent randomization, 422 were assigned to receive a trial drug and were included in the analyses - 214 patients received dexmedetomidine at a median dose of 0.27 μg per kilogram per hour, and 208 received propofol at a median dose of 10.21 μg per kilogram per minute. The median duration of receipt of the trial drugs was 3.0 days (interquartile range, 2.0 to 6.0), and the median RASS score was -2.0 (interquartile range, -3.0 to -1.0). We found no difference between dexmedetomidine and propofol in the number of days alive without delirium or coma (adjusted median, 10.7 vs. 10.8 days; odds ratio, 0.96; 95% confidence interval [CI], 0.74 to 1.26), ventilator-free days (adjusted median, 23.7 vs. 24.0 days; odds ratio, 0.98; 95% CI, 0.63 to 1.51), death at 90 days (38% vs. 39%; hazard ratio, 1.06; 95% CI, 0.74 to 1.52), or TICS-T score at 6 months (adjusted median score, 40.9 vs. 41.4; odds ratio, 0.94; 95% CI, 0.66 to 1.33). Safety end points were similar in the two groups.

CONCLUSIONS

Among mechanically ventilated adults with sepsis who were being treated with recommended light-sedation approaches, outcomes in patients who received dexmedetomidine did not differ from outcomes in those who received propofol. (Funded by the National Institutes of Health; ClinicalTrials.gov number, NCT01739933.).

Safety and Efficacy of Dexmedetomidine in Acutely Ill Adults Requiring Noninvasive Ventilation: A Systematic Review and Meta-analysis of Randomized Trials

BACKGROUND

Although clinical studies have evaluated dexmedetomidine as a strategy to improve noninvasive ventilation (NIV) comfort and tolerance in patients with acute respiratory failure (ARF), their results have not been summarized.

RESEARCH QUESTION

Does dexmedetomidine, when compared with another sedative or placebo, reduce the risk of delirium, mortality, need for intubation and mechanical ventilation, or ICU length of stay (LOS) in adults with ARF initiated on NIV in the ICU?

STUDY DESIGN AND METHODS

We electronically searched MEDLINE, EMBASE, and the Cochrane Library from inception through July 31, 2020, for randomized clinical trials (RCTs). We calculated pooled relative risks (RRs) for dichotomous outcomes and mean differences (MDs) for continuous outcomes with the corresponding 95% CIs using a random-effect model.

RESULTS

Twelve RCTs were included in our final analysis (n = 738 patients). The use of dexmedetomidine, compared with other sedation strategies or placebo, reduced the risk of intubation (RR, 0.54; 95% CI, 0.41-0.71; moderate certainty), delirium (RR, 0.34; 95% CI, 0.22-0.54; moderate certainty), and ICU LOS (MD, -2.40 days; 95% CI, -3.51 to -1.29 days; low certainty). Use of dexmedetomidine was associated with an increased risk of bradycardia (RR, 2.80; 95% CI, 1.92-4.07; moderate certainty) and hypotension (RR, 1.98; 95% CI, 1.32-2.98; moderate certainty).

INTERPRETATION

Compared with any sedation strategy or placebo, dexmedetomidine reduced the risk of delirium and the need for mechanical ventilation while increasing the risk of bradycardia and hypotension. The results are limited by imprecision, and further large RCTs are needed.

TRIAL REGISTRY

PROSPERO; No.: 175086; URL: www.crd.york.ac.uk/prospero/.

Association of Positive Delirium Screening with Incident Dementia in Skilled Nursing Facilities

BACKGROUND AND OBJECTIVE

Early detection of delirium in skilled nursing facilities (SNFs) is a priority. The extent to which delirium screening leads to a potentially inappropriate diagnosis of Alzheimer's disease and related dementia (ADRD) is unknown.

DESIGN

Nationwide retrospective cohort study from 2011 to 2013.

SETTING

An SNF.

PARTICIPANTS

A total of 1,175,550 Medicare enrollees who entered the SNF from a hospital and had no prior diagnosis of dementia.

EXPOSURE

A positive screen for delirium using the validated Confusion Assessment Method (CAM), performed as part of the federally mandated Minimum Data Set (MDS) assessment.

MEASUREMENTS

Incident all-cause dementia, ascertained through International Classification of Diseases, Ninth Revision (ICD-9), diagnosis in Medicare claims or active diagnoses in MDS.

RESULTS

Positive screening for delirium was identified in 7.7% of cases (n = 90,449), and most occurred within the first 7 days of SNF admission (62.5%). The overall incidence of ADRD was 6.3% (n = 73,542). Nearly all new diagnoses of ADRD (93.5%) occurred within the first 30 days of SNF admission. Patients who screened CAM positive for delirium had a nearly threefold increased risk of receiving an incident ADRD diagnosis on the same day (hazard ratio (HR) = 2.63; 95% confidence interval (CI) = 1.50-4.63). Among patients who screened CAM positive for delirium, those who were cognitively intact or had mild cognitive impairments were, on average, six times more likely to receive an incident ADRD diagnosis (HR = 6.64; 95% CI = 1.76-25.0) relative to those testing CAM negative.

CONCLUSION AND RELEVANCE

Among older adults not previously diagnosed with dementia, a positive screen for delirium was significantly associated with higher risk of ADRD diagnosis after admission to a SNF. This risk was highest for patients in the first days of their stay and with the least cognitive impairment, suggesting that the ADRD diagnosis was potentially inappropriate.

Impact of a Pharmacist-Led Intensive Care Unit Sleep Improvement Protocol on Sleep Duration and Quality

BACKGROUND

Sleep improvement protocols are recommended for use in the intensive care unit (ICU) despite questions regarding which interventions to include, whether sleep quality or duration will improve, and the role of pharmacists in their development and implementation.

OBJECTIVE

To characterize the impact of a pharmacist-led, ICU sleep improvement protocol on sleep duration and quality as evaluated by a commercially available activity tracker and patient perception.

METHODS

Critical care pharmacists from a 40-bed, mixed ICU at a large community hospital led the development and implementation of an interprofessional sleep improvement protocol. It included daily pharmacist medication review to reduce use of medications known to disrupt sleep or increase delirium and guideline-based recommendations on both environmental and nonpharmacological sleep-focused interventions. Sleep duration and quality were compared before (December 2018 to December 2019) and after (January to June 2019) protocol implementation in non-mechanically ventilated adults using both objective (total nocturnal sleep time [TST] measured by an activity tracker (Fitbit Charge 2) and subjective (patient-perceived sleep quality using the Richards-Campbell Sleep Questionnaire [RCSQ]) measures.

RESULTS

Groups before (n = 48) and after (n = 29) sleep protocol implementation were well matched. After protocol implementation, patients had a longer TST (389 ± 123 vs 310 ± 147 minutes; P = 0.02) and better RCSQ-perceived sleep quality (63 ± 18 vs 42 ± 24 mm; P = 0.0003) compared with before implementation.

CONCLUSION AND RELEVANCE

A sleep protocol that incorporated novel elements led to objective and subjective improvements in ICU sleep duration and quality. Application of this study may result in increased utilization of sleep protocols and pharmacist involvement.

Approaches to Optimize Medication Data Analysis in Clinical Cohort Studies

OBJECTIVES

Methods for pharmacoepidemiologic studies of large-scale data repositories are established. Although clinical cohorts of older adults often contain critical information to advance our understanding of medication risk and benefit, the methods best suited to manage medication data in these samples are sometimes unclear and their degree of validation unknown. We sought to provide researchers, in the context of a clinical cohort study of delirium in older adults, with guidance on the methodological tools to use data from clinical cohorts to better understand medication risk factors and outcomes.

DESIGN

Prospective cohort study.

SETTING

The Successful Aging After Elective Surgery (SAGES) prospective cohort.

PARTICIPANTS

A total of 560 older adults (aged ≥70 years) without dementia undergoing elective major surgery.

MEASUREMENTS

Using the SAGES clinical cohort, methods used to characterize medications were identified, reviewed, analyzed, and distinguished by appropriateness and degree of validation for characterizing pharmacoepidemiologic data in smaller clinical data sets.

RESULTS

Medication coding is essential; the American Hospital Formulary System, most often used in the United States, is not preferred over others. Use of equivalent dosing scales (e.g., morphine equivalents) for a single medication class (e.g., opioids) is preferred over multiclass analgesic equivalency scales. Medication aggregation from the same class (e.g., benzodiazepines) is well established; the optimal prevalence breakout for aggregation remains unclear. Validated scale(s) to combine structurally dissimilar medications (e.g., anticholinergics) should be used with caution; a lack of consensus exists regarding the optimal scale. Directed acyclic graph(s) are an accepted method to conceptualize causative frameworks when identifying potential confounders. Modeling-based strategies should be used with evidence-based, a priori variable-selection strategies.

CONCLUSION

As highlighted in the SAGES cohort, the methods used to classify and analyze medication data in clinically rich cohort studies vary in the rigor by which they have been developed and validated.

Efficacy of halopeRIdol to decrease the burden of Delirium In adult Critically ill patiEnts (EuRIDICE): study protocol for a prospective randomised multi-centre double-blind placebo-controlled clinical trial in the Netherlands

INTRODUCTION

Delirium in critically ill adults is associated with prolonged hospital stay, increased mortality and greater cognitive and functional decline. Current practice guideline recommendations advocate the use of non-pharmacological strategies to reduce delirium. The routine use of scheduled haloperidol to treat delirium is not recommended given a lack of evidence regarding its ability to resolve delirium nor improve relevant short-term and longer-term outcomes. This study aims to evaluate the efficacy and safety of haloperidol for the treatment of delirium in adult critically ill patients to reduce days spent with coma or delirium.

METHODS AND ANALYSIS

EuRIDICE is a prospective, multi-centre, randomised, double-blind, placebo-controlled trial. Study population consists of adult intensive care unit (ICU) patients without acute neurological injury who have delirium based on a positive Intensive Care Delirium Screening Checklist (ICDSC) or Confusion Assessment Method for the ICU (CAM-ICU) assessment. Intervention is intravenous haloperidol 2.5 mg (or matching placebo) every 8 hours, titrated daily based on ICDSC or CAM-ICU positivity to a maximum of 5 mg every 8 hours, until delirium resolution or ICU discharge. Main study endpoint is delirium and coma-free days (DCFD) up to 14 days after randomisation. Secondary endpoints include (1) 28-day and 1-year mortality, (2) cognitive and functional performance at 3 and 12 months, (3) patient and family delirium and ICU experience, (4) psychological sequelae during and after ICU stay, (4) safety concerns associated with haloperidol use and (5) cost-effectiveness. Differences in DCFDs between haloperidol and placebo group will be analysed using Poisson regression analysis. Study recruitment started in February 2018 and continues.

ETHICS AND DISSEMINATION

The study has been approved by the Medical Ethics Committee of the Erasmus University Medical Centre Rotterdam (MEC2017-511) and by the Institutional Review Boards of the participating sites. Its results will be disseminated via peer-reviewed publication and conference presentations.

TRIAL REGISTRATION

NCT03628391.

Role for Anti-Cytokine Therapies in Severe Coronavirus Disease 2019

The causative agent for coronavirus disease 2019, severe acute respiratory syndrome coronavirus 2, appears exceptional in its virulence and immunopathology. In some patients, the resulting hyperinflammation resembles a cytokine release syndrome. Our knowledge of the immunopathogenesis of coronavirus disease 2019 is evolving and anti-cytokine therapies are under active investigation. This narrative review summarizes existing knowledge of the immune response to coronavirus infection and highlights the current and potential future roles of therapeutic strategies to combat the hyperinflammatory response of patients with coronavirus disease 2019.

DATA SOURCES

Relevant and up-to-date literature, media reports, and author experiences were included from Medline, national newspapers, and public clinical trial databases.

STUDY SELECTION

The authors selected studies for inclusion by consensus.

DATA EXTRACTION

The authors reviewed each study and selected approrpriate data for inclusion through consensus.

DATA SYNTHESIS

Hyperinflammation, reminiscent of cytokine release syndromes such as macrophage activation syndrome and hemophagocytic lymphohistiocytosis, appears to drive outcomes among adults with severe coronavirus disease 2019. Cytokines, particularly interleukin-1 and interleukin-6, appear to contribute importantly to such systemic hyperinflammation. Ongoing clinical trials will determine the efficacy and safety of anti-cytokine therapies in coronavirus disease 2019. In the interim, anti-cytokine therapies may provide a treatment option for adults with severe coronavirus disease 2019 unresponsive to standard critical care management, including ventilation.

CONCLUSIONS

This review provides an overview of the current understanding of the immunopathogenesis of coronavirus disease 2019 in adults and proposes treatment considerations for anti-cytokine therapy use in adults with severe disease.