Harhay, Michael Oscar

OBJECTIVES: To describe the outcomes of hospitalized patients in a multicenter, international coronavirus disease 2019 registry. DESIGN: Cross-sectional observational study including coronavirus disease 2019 patients hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus-2 infection between February 15, 2020, and November 30, 2020, according to age and type of organ support therapies. SETTING: About 168 hospitals in 16 countries within the Society of Critical Care Medicine’s Discovery Viral Infection and Respiratory Illness University Study coronavirus disease 2019 registry. PATIENTS: Adult hospitalized coronavirus disease 2019 patients who did and did not require various types and combinations of organ support (mechanical ventilation, renal replacement therapy, vasopressors, and extracorporeal membrane oxygenation). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Primary outcome was hospital mortality. Secondary outcomes were discharge home with or without assistance and hospital length of stay. Risk-adjusted variation in hospital mortality for patients receiving invasive mechanical ventilation was assessed by using multilevel models with hospitals as a random effect, adjusted for age, race/ethnicity, sex, and comorbidities. Among 20,608 patients with coronavirus disease 2019, the mean (± sd ) age was 60.5 (±17), 11,1887 (54.3%) were men, 8,745 (42.4%) were admitted to the ICU, and 3,906 (19%) died in the hospital. Hospital mortality was 8.2% for patients receiving no organ support ( n = 15,001). The most common organ support therapy was invasive mechanical ventilation ( n = 5,005; 24.3%), with a hospital mortality of 49.8%. Mortality ranged from 40.8% among patients receiving only invasive mechanical ventilation ( n =1,749) to 71.6% for patients receiving invasive mechanical ventilation, vasoactive drugs, and new renal replacement therapy ( n = 655). Mortality was 39% for patients receiving extracorporeal membrane oxygenation ( n = 389). Rates of discharge home ranged from 73.5% for patients who did not require organ support therapies to 29.8% for patients who only received invasive mechanical ventilation, and 8.8% for invasive mechanical ventilation, vasoactive drugs, and renal replacement; 10.8% of patients older than 74 years who received invasive mechanical ventilation were discharged home. Median hospital length of stay for patients on mechanical ventilation was 17.1 days (9.7-28 d). Adjusted interhospital variation in mortality among patients receiving invasive mechanical ventilation was large (median odds ratio 1.69). CONCLUSIONS: Coronavirus disease 2019 prognosis varies by age and level of organ support. Interhospital variation in mortality of mechanically ventilated patients was not explained by patient characteristics and requires further evaluation.

Background: After critical illness, new or worsening impairments in physical, cognitive, and/or mental health function are common among patients who have survived. Who should be screened for long-term impairments, what tools to use, and when remain unclear. Objectives: Provide pragmatic recommendations to clinicians caring for adult survivors of critical illness related to screening for postdischarge impairments. Participants: Thirty-one international experts in risk-stratification and assessment of survivors of critical illness, including practitioners involved in the Society of Critical Care Medicine’s Thrive Post-ICU Collaboratives, survivors of critical illness, and clinical researchers. Design: Society of Critical Care Medicine consensus conference on post-intensive care syndrome prediction and assessment, held in Dallas, in May 2019. A systematic search of PubMed and the Cochrane Library was conducted in 2018 and updated in 2019 to complete an original systematic review and to identify pre-existing systematic reviews. Meeting Outcomes: We concluded that existing tools are insufficient to reliably predict post-intensive care syndrome. We identified factors before (e.g., frailty, preexisting functional impairments), during (e.g., duration of delirium, sepsis, acute respiratory distress syndrome), and after (e.g., early symptoms of anxiety, depression, or post-traumatic stress disorder) critical illness that can be used to identify patients at high-risk for cognitive, mental health, and physical impairments after critical illness in whom screening is recommended. We recommend serial assessments, beginning within 2–4 weeks of hospital discharge, using the following screening tools: Montreal Cognitive Assessment test; Hospital Anxiety and Depression Scale; Impact of Event Scale-Revised (post-traumatic stress disorder); 6-minute walk; and/or the EuroQol-5D-5L, a health-related quality of life measure (physical function). Conclusions: Beginning with an assessment of a patient’s pre-ICU functional abilities at ICU admission, clinicians have a care coordination strategy to identify and manage impairments across the continuum. As hospital discharge approaches, clinicians should use brief, standardized assessments and compare these results to patient’s pre-ICU functional abilities (“functional reconciliation”). We recommend serial assessments for post-intensive care syndrome-related problems continue within 2–4 weeks of hospital discharge, be prioritized among high-risk patients, using the identified screening tools to prompt referrals for services and/or more detailed assessments.

Objectives: Use of observational data to inform the response and care of patients during a pandemic faces unique challenges. Design: The Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study COVID 2019 Registry Core data and research methodology team convened over virtual meetings throughout March to June 2020 to determine best practice goals for development of a pandemic disease registry to support rapid data collection and analysis. Setting: International, multi-center registry of hospitalized patients. Patients: None. Interventions: None. Measurements and Main Results: Large-scale observational data collection requires: 1) quality assurance and harmonization across many sites; 2) a transparent process for selecting from among many potential research questions; 3) the use of best practices in design of descriptive, predictive, and inferential studies; (4) innovative approaches to characterize random error in the setting of constantly updated data; (5) rapid peer-review and reporting; and (6) transitions from a focus on discovery to implementation. Herein, we describe the guiding principles to best practices and suggestions for innovations to study design and reporting within the coronavirus disease 2019 Viral Infection and Respiratory Illness Universal Study pandemic registry. Conclusions: Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study coronavirus disease 2019 registry sought to develop and implement prespecified best practices combined with grassroots efforts from clinical sites worldwide in order to develop clinically useful knowledge in response to a pandemic.

Objectives: The coronavirus disease 2019 pandemic has disproportionally strained intensive care services worldwide. Large areas of uncertainly regarding epidemiology, physiology, practice patterns, and resource demands for patients with coronavirus disease 2019 require rapid collection and dissemination of data. We describe the conception and implementation of an intensive care database rapidly developed and designed to meet data analytic needs in response to the coronavirus disease 2019 pandemic—the multicenter, international Society of Critical Care Medicine Discovery Network Viral Infection and Respiratory Illness Universal Study. Design: Prospective cohort study and disease registry. Setting: Multinational cohort of ICUs. Patients: Critically ill patients with a diagnosis of coronavirus disease 2019. Interventions: None. Measurements and Main Results: Within 2 weeks of conception of the Society of Critical Care Medicine Discovery Network Viral Infection and Respiratory Illness Universal Study, study leadership was convened, registry case report forms were designed, electronic data entry set up, and more than 250 centers had submitted the protocol for institutional review board approval, with more than 100 cases entered. Conclusions: The Society of Critical Care Medicine Discovery Network Viral Infection and Respiratory Illness Universal Study provides an example of a rapidly deployed, international, pandemic registry that seeks to provide near real-time analytics and information regarding intensive care treatments and outcomes for patients with coronavirus disease 2019.

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of “modifiable risk factors”, measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details.