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Objective: Although medical intensive care unit nurses at our institution routinely use the Intensive Care Delirium Screening Checklist (ICDSC) to identify delirium, physicians rely on traditional diagnostic methods. We sought to measure the effect of physicians' use of the ICDSC on their ability to detect delirium.Design: Before-after study.Setting: Medical intensive care unit of an academic medical center.Patients and Participants: A total of 25 physicians with >or=1 month of clinical experience in the medical intensive care unit conducted 300 delirium assessments in 100 medical intensive care unit patients.Measurements and Main Results: Physicians sequentially evaluated two patients for delirium using whatever diagnostic method preferred. Following standardized education regarding ICDSC use, each physician evaluated two different patients for delirium using the ICDSC. Each physician assessment was preceded by consecutive, but independent, evaluations for delirium by the patient's nurse and then a validated judge using the ICDSC. Before (PRE) physician ICDSC use, the validated judge identified delirium in five patients; the physicians and nurses identified delirium in zero and four of these patients, respectively. The physicians incorrectly identified delirium in four additional patients. After (POST) physician ICDSC use, the validated judge identified delirium in 11 patients; the physicians and nurses identified delirium in eight and ten of these patients, respectively. The physicians incorrectly identified delirium in one patient. After physician ICDSC use, agreement improved between both the physicians and validated judge (PRE kappa = -0.14 [95% confidence interval {CI} = -0.27 to -0.02] to POST kappa = 0.67 [95% CI = 0.38 to 0.96]) and physicians and nurses (PRE kappa = -0.15 [95% CI = -0.29 to -0.02] to POST kappa = 0.58 [95% CI = 0.25 to 0.91]). Nurses vs. validated judge agreement was strong in both periods (PRE kappa = 0.65 [95% CI = 0.29 to 1.00] and POST kappa = 0.92 [95% CI = 0.76 to 1.00]).Conclusions: Use of the ICDSC, along with education supporting its use, improves the ability of physicians to detect delirium in the medical intensive care unit. [ABSTRACT FROM AUTHOR]

OBJECTIVES: Noninvasive positive-pressure ventilation (NPPV) is increasingly used in patients with acute respiratory failure, but few data exist regarding current sedation practices during NPPV. We sought to characterize current practices and attitudes regarding sedation during NPPV. DESIGN: Cross-sectional Web-based survey. SETTING: Medical institutions. PARTICIPANTS: Physician members of the American College of Chest Physician's Critical Care Network (n = 2,656) and the European Respiratory Society's Assembly of Critical Care (n = 339). INTERVENTIONS: Survey. MEASUREMENTS AND MAIN RESULTS: Of the 790 of 2,985 (27%) of physicians who responded, 15%, 6%, and 28% never used sedation, analgesia, or hand restraints any of the time for NPPV patients, respectively, and the large majority reported using these interventions in < or =25% of patients. Sedation, analgesia, and hand restraints were more commonly used by North Americans than Europeans (41% vs. 24% for sedation, 48% vs. 35% for analgesia, and 27% vs. 16% for hand restraints, all p < .01) and critical care vs. noncritical care physicians (42% vs. 24% for sedation and 50% vs. 34% for analgesia, all p < .01). A benzodiazepine alone was the most preferred (33%), followed by an opioid alone (29%). Europeans were less likely to use a benzodiazepine alone (25% vs. 39%, p < .001) but more likely to use an opioid alone (37% vs. 26%, p < .009). Sedation was usually administered as an intermittent intravenous bolus, outside of a protocol, and was assessed by nurses using clinical end points rather than a sedation scale. CONCLUSIONS: Most physicians infrequently use sedation and analgesic therapy for NPPV to treat acute respiratory failure, but practices vary widely within and between specialties and geographic regions. [ABSTRACT FROM AUTHOR]

Introduction: We hypothesized that delirium symptoms may respond differently to antipsychotic therapy. The purpose of this paper was to retrospectively compare duration and time to first resolution of individual delirium symptoms from the database of a randomized, double-blind, placebo-controlled study comparing quetiapine (Q) or placebo (P), both with haloperidol rescue, for critically ill patients with delirium.Methods: Data for 10 delirium symptoms from the eight-domain, intensive care delirium screening checklist (ICDSC) previously collected every 12 hours were extracted for 29 study patients. Data between the Q and P groups were compared using a cut-off P-value of ≤ 0.10 for this exploratory study.Results: Baseline ICDSC scores (5 (4 to 7) (Q) vs 5 (4 to 6)) (median, interquartile range (IQR)) and % of patients with each ICDSC symptom were similar in the two groups (all P > 0.10). Among patients with the delirium symptom at baseline, use of Q may lead to a shorter time (days) to first resolution of symptom fluctuation (4 (Q) vs. 14, P = 0.004), inattention (3 vs. 8, P = .10) and disorientation (2 vs. 10, P = 0.10) but a longer time to first resolution of agitation (3 vs. 1, P = 0.04) and hyperactivity (5 vs. 1, P = 0.07). Among all patients, Q-treated patients tended to spend a smaller percent of time with inattention (47 (0 to 67) vs. 78 (43 to 100), P = 0.025), hallucinations (0 (0 to 17) vs. 28 (0 to 43), P = 0.10) and symptom fluctuation (47 (19 to 67) vs. 89 (33 to 00), P = 0.04] and there was a trend for Q-treated patients to spend a greater percent of time at an appropriate level of consciousness (26% (13 to 63%) vs. 14% (0 to 33%), P = 0.17].Conclusions: Our exploratory analysis suggests that quetiapine may resolve several intensive care unit (ICU) delirium symptoms faster than the placebo. Individual symptom resolution appears to differ in association with the pharmacologic intervention (that is, P vs Q, both with as needed haloperidol). Future studies evaluating antipsychotics in ICU patients with delirium should measure duration and resolution of individual delirium symptoms and their relation to long-term outcomes. [ABSTRACT FROM AUTHOR]

Background: Whether cognitive and functional recovery in skilled nursing facilities (SNF) following hospitalization differs by delirium and Alzheimer's disease related dementias (ADRD) has not been examined., Objective: To compare change in cognition and function among short-stay SNF patients with delirium, ADRD, or both., Design: Retrospective cohort study using claims data from 2011 to 2013., Setting: Centers for Medicare and Medicaid certified SNFs., Participants: A total of 740,838 older adults newly admitted to a short-stay SNF without prevalent ADRD who had at least two assessments of cognition and function., Measurements: Incident delirium was measured by the Minimum Data Set (MDS) Confusion Assessment Method and ICD-9 codes, and incident ADRD by ICD-9 codes and MDS diagnoses. Cognitive improvement was a better or maximum score on the MDS Brief Interview for Mental Status, and functional recovery was a better or maximum score on the MDS Activities of Daily Living Scale., Results: Within 30 days of SNF admission, the rate of cognitive improvement in patients with both delirium/ADRD was half that of patients with neither delirium/ADRD (HR = 0.45, 95% CI:0.43, 0.46). The ADRD-only and delirium-only groups also were 43% less likely to have improved cognition or function compared to those with neither delirium/ADRD (HR = 0.57, 95% CI:0.56, 0.58 and HR = 0.57, 95% CI:0.55, 0.60, respectively). Functional improvement was less likely in patients with both delirium/ADRD, as well (HR = 0.85, 95% CI:0.83, 0.87). The ADRD only and delirium only groups were also less likely to improve in function (HR = 0.93, 95% CI:0.92, 0.94 and HR = 0.92, 95% CI:0.90, 0.93, respectively) compared to those with neither delirium/ADRD., Conclusions: Among older adults without dementia admitted to SNF for post-acute care following hospitalization, a positive screen for delirium and a new diagnosis of ADRD, within 7 days of SNF admission, were both significantly associated with worse cognitive and functional recovery. Patients with both delirium and new ADRD had the worst cognitive and functional recovery., (© 2024 The Author(s). Journal of the American Geriatrics Society published by Wiley Periodicals LLC on behalf of The American Geriatrics Society.)

Introduction: Sedation in mechanically ventilated adults in the intensive care unit (ICU) is commonly achieved with intravenous infusions of propofol, dexmedetomidine or benzodiazepines. Significant limitations associated with each can impact their usage. Inhaled isoflurane has potential benefit for ICU sedation due to its safety record, sedation profile, lack of metabolism and accumulation, and fast wake-up time. Administration in the ICU has historically been restricted by the lack of a safe and effective delivery system for the ICU. The Sedaconda Anaesthetic Conserving Device-S (Sedaconda ACD-S) has enabled the delivery of inhaled volatile anaesthetics for sedation with standard ICU ventilators, but it has not yet been rigorously evaluated in the USA. We aim to evaluate the efficacy and safety of inhaled isoflurane delivered via the Sedaconda ACD-S compared with intravenous propofol for sedation of mechanically ventilated ICU adults in USA hospitals., Methods and Analysis: INhaled Sedation versus Propofol in REspiratory failure in the ICU (INSPiRE-ICU1) is a phase 3, multicentre, randomised, controlled, open-label, assessor-blinded trial that aims to enrol 235 critically ill adults in 14 hospitals across the USA. Eligible patients are randomised in a 1.5:1 ratio for a treatment duration of up to 48 (±6) hours or extubation, whichever occurs first, with primary follow-up period of 30 days and additional follow-up to 6 months. Primary outcome is percentage of time at target sedation range. Key secondary outcomes include use of opioids during treatment, spontaneous breathing efforts during treatment, wake-up time at end of treatment and cognitive recovery after treatment., Ethics and Dissemination: Trial protocol has been approved by US Food and Drug Administration (FDA) and central (Advarra SSU00208265) or local institutional review boards ((IRB), Cleveland Clinic IRB FWA 00005367, Tufts HS IRB 20221969, Houston Methodist IRB PRO00035247, Mayo Clinic IRB Mod22-001084-08, University of Chicago IRB21-1917-AM011 and Intermountain IRB 033175). Results will be presented at scientific conferences, submitted for publication, and provided to the FDA., Trial Registration Number: NCT05312385., Competing Interests: Competing interests: CB, TDG, JK and CH have received consulting fees from Sedana Medical AB as members of their US Trials Steering Committee. JWD has received speaker honoraria from Sedana Medical AB. IS and MF and PVS are employed by Sedana Medical AB., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Importance: The optimal screening frequency and spontaneous breathing trial (SBT) technique to liberate adults from ventilators are unknown., Objective: To compare the effects of screening frequency (once-daily screening vs more frequent screening) and SBT technique (pressure-supported SBT with a pressure support level that was >0-≤8 cm H2O and a positive end-expiratory pressure [PEEP] level that was >0-≤5 cm H2O vs T-piece SBT) on the time to successful extubation., Design, Setting, and Participants: Randomized clinical trial with a 2 × 2 factorial design including critically ill adults who were receiving invasive mechanical ventilation for at least 24 hours, who were capable of initiating spontaneous breaths or triggering ventilators, and who were receiving a fractional concentration of inspired oxygen that was 70% or less and a PEEP level of 12 cm H2O or less. Recruitment was between January 2018 and February 2022 at 23 intensive care units in North America; last follow-up occurred October 18, 2022., Interventions: Participants were enrolled early to enable protocolized screening (more frequent vs once daily) to identify the earliest that patients met criteria to undergo pressure-supported or T-piece SBT lasting 30 to 120 minutes., Main Outcome and Measures: Time to successful extubation (time when unsupported, spontaneous breathing began and was sustained for ≥48 hours after extubation)., Results: Of 797 patients (198 in the once-daily screening and pressure-supported SBT group, 204 in once-daily screening and T-piece SBT, 195 in more frequent screening and pressure-supported SBT, and 200 in more frequent screening and T-piece SBT), the mean age was 62.4 (SD, 18.4) years and 472 (59.2%) were men. There were no statistically significant differences by screening frequency (hazard ratio [HR], 0.88 [95% CI, 0.76-1.03]; P = .12) or by SBT technique (HR, 1.06 [95% CI, 0.91-1.23]; P = .45). The median time to successful extubation was 2.0 days (95% CI, 1.7-2.7) for once-daily screening and pressure-supported SBT, 3.1 days (95% CI, 2.7-4.8) for once-daily screening and T-piece SBT, 3.9 days (95% CI, 2.9-4.7) for more frequent screening and pressure-supported SBT, and 2.9 days (95% CI, 2.0-3.1) for more frequent screening and T-piece SBT. An unexpected interaction between screening frequency and SBT technique required pairwise contrasts that revealed more frequent screening (vs once-daily screening) and pressure-supported SBT increased the time to successful extubation (HR, 0.70 [95% CI, 0.50-0.96]; P = .02). Once-daily screening and pressure-supported SBT (vs T-piece SBT) did not reduce the time to successful extubation (HR, 1.30 [95% CI, 0.98-1.70]; P = .08)., Conclusions and Relevance: Among critically ill adults who received invasive mechanical ventilation for more than 24 hours, screening frequency (once-daily vs more frequent screening) and SBT technique (pressure-supported vs T-piece SBT) did not change the time to successful extubation. However, an unexpected and statistically significant interaction was identified; protocolized more frequent screening combined with pressure-supported SBTs increased the time to first successful extubation., Trial Registration: ClinicalTrials.gov Identifiers: NCT02399267 and NCT02969226.

Background: An association between driving pressure (∆P) and the outcomes of invasive mechanical ventilation (IMV) may exist. However, the effect of a sustained limitation of ∆P on mortality in patients with acute respiratory distress syndrome (ARDS), including patients with COVID-19 (COVID-19-related acute respiratory distress syndrome (C-ARDS)) undergoing IMV, has not been rigorously evaluated. The use of emulations of a target trial in intensive care unit research remains in its infancy. To inform future, large ARDS target trials, we explored using a target trial emulation approach to analyse data from a cohort of IMV adults with C-ARDS to determine whether maintaining daily ∆p<15 cm H 2 O (in addition to traditional low tidal volume ventilation (LTVV) (tidal volume 5-7 cc/PBW+plateau pressure (P plat ) ≤30 cm H 2 O), compared with LTVV alone, affects the 28-day mortality., Methods: To emulate a target trial, adults with C-ARDS requiring >24 hours of IMV were considered to be assigned to limited ∆P or LTVV. Lung mechanics were measured twice daily after ventilator setting adjustments were made. To evaluate the effect of each lung-protective ventilation (LPV) strategy on the 28-day mortality, we fit a stabilised inverse probability weighted marginal structural model that adjusted for baseline and time-varying confounders known to affect protection strategy use/adherence or survival., Results: Among the 92 patients included, 27 (29.3%) followed limited ∆P ventilation, 23 (25.0%) the LTVV strategy and 42 (45.7%) received no LPV strategy. The adjusted estimated 28-day survival was 47.0% (95% CI 23%, 76%) in the limited ∆P group, 70.3% in the LTVV group (95% CI 37.6%, 100%) and 37.6% (95% CI 20.8%, 58.0%) in the no LPV strategy group., Interpretation: Limiting ∆P may not provide additional survival benefits for patients with C-ARDS over LTVV. Our results help inform the development of future target trial emulations focused on evaluating LPV strategies, including reduced ∆P, in adults with ARDS., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Despite the use of multidomain prevention strategies, delirium still frequently occurs in hospitalized adults. With delirium often associated with undesirable symptoms and deleterious outcomes, including cognitive decline, treatment is important. Risk-factor reduction and the protocolized use of multidomain, nonpharmacologic bundles remain the mainstay of delirium treatment. There is a current lack of strong evidence to suggest any pharmacologic intervention to treat delirium will help resolve it faster, reduce its symptoms (other than agitation), facilitate hospital throughput, or improve post-hospital outcomes including long-term cognitive function. With the exception of dexmedetomidine as a treatment of severe delirium-associated agitation in the ICU, current practice guidelines do not recommend the routine use of any pharmacologic intervention to treat delirium in any hospital population. Future research should focus on identifying and evaluating new pharmacologic delirium treatment interventions and addressing key challenges and gaps surrounding delirium treatment research., Competing Interests: The author disclosed that he has received unrelated grant support from the NIA, AHRQ, Sedana Medical, and BioXcel Therapeutics and has served as a consultant to Ceribell Inc., (Thieme. All rights reserved.)

Competing Interests: Dr. Hamblin’s institution received funding from Prytime. Dr. Devlin has disclosed that he does not have any potential conflicts of interest.

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., Competing Interests: The authors have no competing interests to disclose., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

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., Competing Interests: Dr. Devlin disclosed he has received research funding from BioExcel, Sedana Medical, and the National Institute of Aging (R13185760, R33HL23452, and R21/R33 AG05797) and that he serves as a consultant to BioExcel, La Jolla Pharmaceuticals, and Ceribell. Dr. Kane-Gill received funding from the Society of Critical Care Medicine. The remaining authors have disclosed that they do not have any potential conflict of interest., (Copyright © 2024 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)