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Background: Understanding the distribution of organ failure before and during the COVID-19 pandemic surge can provide a deeper understanding of how the pandemic strained health care systems and affected outcomes., Objective: To assess the distribution of organ failure in 3 New York City hospitals during the COVID-19 pandemic., Methods: A retrospective cohort study of adult admissions across hospitals from February 1, 2020, through May 31, 2020, was conducted. The cohort was stratified into those admitted before March 17, 2020 (prepandemic) and those admitted on or after that date (SARS-CoV-2-positive and non-SARS-CoV-2). Sequential Organ Failure Assessment scores were computed every 2 hours for each admission., Results: A total of 1 794 975 scores were computed for 20 704 admissions. Before and during the pandemic, renal failure was the most common type of organ failure at admission and respiratory failure was the most common type of hospital-onset organ failure. The SARS-CoV-2-positive group showed a 231% increase in respiratory failure compared with the prepandemic group. More than 65% of hospital-onset organ failure in the prepandemic group and 83% of hospital-onset respiratory failure in the SARS-CoV-2-positive group occurred outside intensive care units. The SARS-CoV-2-positive group showed a 341% increase in multiorgan failure compared with the prepandemic group. Compared with the prepandemic and non-SARS-CoV-2 patients, SARS-CoV-2-positive patients had significantly higher mortality for the same admission and maximum organ failure score., Conclusion: Most hospital-onset organ failure began outside intensive care units, with a marked increase in multiorgan failure during pandemic surge conditions and greater hospital mortality for the severity of organ failure., (©2022 American Association of Critical-Care Nurses.)

Background: Acute respiratory failure occurs frequently in hospitalized patients and often starts before ICU admission. A risk stratification tool to predict mortality and risk for mechanical ventilation (MV) may allow for earlier evaluation and intervention. We developed and validated an automated electronic health record (EHR)-based model-Accurate Prediction of Prolonged Ventilation (APPROVE)-to identify patients at risk of death or respiratory failure requiring >= 48 h of MV., Methods: This was an observational study of adults admitted to four hospitals in 2013 or a fifth hospital in 2017. Clinical data were extracted from the EHRs. The 2013 patients were randomly split 50:50 into a derivation/validation cohort. The qualifying event was death or intubation leading to MV >= 48 h. Random forest method was used in model derivation. APPROVE was calculated retrospectively whenever data were available in 2013, and prospectively every 4 h after hospital admission in 2017. The Modified Early Warning Score (MEWS) and National Early Warning Score (NEWS) were calculated at the same times as APPROVE. Clinicians were not alerted except for APPROVE in 2017cohort., Results: There were 68,775 admissions in 2013 and 2258 in 2017. APPROVE had an area under the receiver operator curve of 0.87 (95% CI 0.85-0.88) in 2013 and 0.90 (95% CI 0.84-0.95) in 2017, which is significantly better than the MEWS and NEWS in 2013 but similar to the MEWS and NEWS in 2017. At a threshold of > 0.25, APPROVE had similar sensitivity and positive predictive value (PPV) (sensitivity 63% and PPV 21% in 2013 vs 64% and 16%, respectively, in 2017). Compared to APPROVE in 2013, at a threshold to achieve comparable PPV (19% at MEWS > 4 and 22% at NEWS > 6), the MEWS and NEWS had lower sensitivity (16% for MEWS and NEWS). Similarly in 2017, at a comparable sensitivity threshold (64% for APPROVE > 0.25 and 67% for MEWS and NEWS > 4), more patients who triggered an alert developed the event with APPROVE (PPV 16%) while achieving a lower false positive rate (FPR 5%) compared to the MEWS (PPV 7%, FPR 14%) and NEWS (PPV 4%, FPR 25%)., Conclusions: An automated EHR model to identify patients at high risk of MV or death was validated retrospectively and prospectively, and was determined to be feasible for real-time risk identification., Trial Registration: ClinicalTrials.gov, NCT02488174 . Registered on 18 March 2015.

Introduction: Acute respiratory failure (ARF) often presents and progresses outside of the intensive care unit. However, recognition and treatment of acute critical illness is often delayed with inconsistent adherence to evidence-based care known to decrease the duration of mechanical ventilation (MV) and complications of critical illness. The goal of this trial is to determine whether the implementation of an electronic medical record-based early alert for progressive respiratory failure coupled with a checklist to promote early compliance to best practice in respiratory failure can improve the outcomes of patients at risk for prolonged respiratory failure and death., Methods and Analysis: A pragmatic stepped-wedged cluster clinical trial involving 6 hospitals is planned. The study will include adult hospitalised patients identified as high risk for MV >48 hours or death because they were mechanically ventilated outside of the operating room or they were identified as high risk for ARF on the Accurate Prediction of PROlonged VEntilation (APPROVE) score. Patients with advanced directives limiting intubation will be excluded. The intervention will consist of (1) automated identification and notification of clinician of high-risk patients by APPROVE or by invasive MV and (2) checklist of evidence-based practices in ARF (Prevention of Organ Failure Checklist-PROOFCheck). APPROVE and PROOFCheck will be developed in the pretrial period. Primary outcome is hospital mortality. Secondary outcomes include length of stay, ventilator and organ failure-free days and 6-month and 12-month mortality. Predefined subgroup analysis of patients with limitation of aggressive care after study entry is planned. Generalised estimating equations will be used to compare patients in the intervention phase with the control phase, adjusting for clustering within hospitals and time., Ethics and Dissemination: The study was approved by the institutional review boards. Results will be published in peer-reviewed journals and presented at international meetings., Trial Registration Number: NCT02488174., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)