IMPORTANCE The US is currently an epicenter of the coronavirus disease 2019 (COVID-19) pandemic, yet few national data are available on patient characteristics, treatment, and outcomes of critical illness from COVID-19. OBJECTIVES To assess factors associated with death and to examine interhospital variation in treatment and outcomes for patients with COVID-19. DESIGN, SETTING, AND PARTICIPANTS This multicenter cohort study assessed 2215 adults with laboratory-confirmed COVID-19 who were admitted to intensive care units (ICUs) at 65 hospitals across the US from March 4 to April 4, 2020. EXPOSURES Patient-level data, including demographics, comorbidities, and organ dysfunction, and hospital characteristics, including number of ICU beds. MAIN OUTCOMES AND MEASURES The primary outcome was 28-day in-hospital mortality. Multilevel logistic regression was used to evaluate factors associated with death and to examine interhospital variation in treatment and outcomes. RESULTS A total of 2215 patients (mean [SD] age, 60.5 [14.5] years; 1436 [64.8%] male; 1738 [78.5%] with at least 1 chronic comorbidity) were included in the study. At 28 days after ICU admission, 784 patients (35.4%) had died, 824 (37.2%) were discharged, and 607 (27.4%) remained hospitalized. At the end of study follow-up (median, 16 days; interquartile range, 8-28 days), 875 patients (39.5%) had died, 1203 (54.3%) were discharged, and 137 (6.2%) remained hospitalized. Factors independently associated with death included older age (Ն80 vs <40 years of age: odds ratio [OR], 11.15; 95% CI, 6.19-20.06), male sex (OR, 1.50; 95% CI, 1.19-1.90), higher body mass index (Ն40 vs <25: OR, 1.51; 95% CI, 1.01-2.25), coronary artery disease (OR, 1.47; 95% CI, 1.07-2.02), active cancer (OR, 2.15; 95% CI, 1.35-3.43), and the presence of hypoxemia (PaO 2 :FIO 2 <100 vs Ն300 mm Hg: OR, 2.94; 95% CI, 2.11-4.08), liver dysfunction (liver Sequential Organ Failure Assessment score of 2 vs 0: OR, 2.61; 95% CI, 1.30-5.25), and kidney dysfunction (renal Sequential Organ Failure Assessment score of 4 vs 0: OR, 2.43; 95% CI, 1.46-4.05) at ICU admission. Patients admitted to hospitals with fewer ICU beds had a higher risk of death (<50 vs Ն100 ICU beds: OR, 3.28; 95% CI, 2.16-4.99). Hospitals varied considerably in the risk-adjusted proportion of patients who died (range, 6.6%-80.8%) and in the percentage of patients who received hydroxychloroquine, tocilizumab, and other treatments and supportive therapies. CONCLUSIONS AND RELEVANCE This study identified demographic, clinical, and hospital-level risk factors that may be associated with death in critically ill patients with COVID-19 and can facilitate the identification of medications and supportive therapies to improve outcomes.

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IMPORTANCE Therapies that improve survival in critically ill patients with coronavirus disease 2019 (COVID-19) are needed. Tocilizumab, a monoclonal antibody against the interleukin 6 receptor, may counteract the inflammatory cytokine release syndrome in patients with severe COVID-19 illness. OBJECTIVE To test whether tocilizumab decreases mortality in this population. DESIGN, SETTING, AND PARTICIPANTS The data for this study were derived from a multicenter cohort study of 4485 adults with COVID-19 admitted to participating intensive care units (ICUs) at 68 hospitals across the US from March 4 to May 10, 2020. Critically ill adults with COVID-19 were categorized according to whether they received or did not receive tocilizumab in the first 2 days of admission to the ICU. Data were collected retrospectively until June 12, 2020. A Cox regression model with inverse probability weighting was used to adjust for confounding. EXPOSURES Treatment with tocilizumab in the first 2 days of ICU admission. MAIN OUTCOMES AND MEASURES Time to death, compared via hazard ratios (HRs), and 30-day mortality, compared via risk differences. RESULTS Among the 3924 patients included in the analysis (2464 male [62.8%]; median age, 62 [interquartile range {IQR}, 52-71] years), 433 (11.0%) received tocilizumab in the first 2 days of ICU admission. Patients treated with tocilizumab were younger (median age, 58 [IQR, 48-65] vs 63 [IQR, 52-72] years) and had a higher prevalence of hypoxemia on ICU admission (205 of 433 [47.3%] vs 1322 of 3491 [37.9%] with mechanical ventilation and a ratio of partial pressure of arterial oxygen to fraction of inspired oxygen of <200 mm Hg) than patients not treated with tocilizumab. After applying inverse probability weighting, baseline and severity-of-illness characteristics were well balanced between groups. A total of 1544 patients (39.3%) died, including 125 (28.9%) treated with tocilizumab and 1419 (40.6%) not treated with tocilizumab. In the primary analysis, during a median follow-up of 27 (IQR, 14-37) days, patients treated with tocilizumab had a lower risk of death compared with those not treated with tocilizumab (HR, 0.71; 95% CI, 0.56-0.92). The estimated 30-day mortality was 27.5% (95% CI, 21.2%-33.8%) in the tocilizumab-treated patients and 37.1% (95% CI, 35.5%-38.7%) in the non-tocilizumab-treated patients (risk difference, 9.6%; 95% CI, 3.1%-16.0%). CONCLUSIONS AND RELEVANCE Among critically ill patients with COVID-19 in this cohort study, the risk of in-hospital mortality in this study was lower in patients treated with tocilizumab in the first 2 days of ICU admission compared with patients whose treatment did not include early use of tocilizumab. However, the findings may be susceptible to unmeasured confounding, and further research from randomized clinical trials is needed.

Body fat distribution has some influence on risk factors beyond total body fat content. Both waist circumference and BMI significantly predicted risk factors after adjustment for total body fat, and for clinical purposes, most of the predictive power for men was contained in waist circumference, whereas for women, BMI and waist circumference were similarly predictive. Finally, even though the correlations between combined body fat parameters and risk factors explained only a portion of the variation in the latter, the average number of categorical metabolic risk factors increased progressively with increasing obesity. Hence, obesity seemingly has more clinical impact than revealed in these correlative studies.

Abstract-Although recent studies have suggested that blacks compared with whites have an increased prevalence of left ventricular hypertrophy, it remains uncertain whether this is true despite adjustment for body composition (fat mass and fat-free mass) and when assessed by cardiac MRI in the general population. The Dallas Heart Study is a population-based study of Dallas County in which 1335 black and 858 white participants 30 to 67 years of age underwent detailed assessment including dual-energy x-ray absorptiometry scan to measure body composition and cardiac MRI. Left ventricular hypertrophy, whether defined by indexation to body surface area (PϽ0.001), fat-free mass (Pϭ0.002), or height 2.7 (PϽ0.001) was 2-to 3-fold more common in black versus white women. Similar results were seen when comparing black and white men (PϽ0.001 when left ventricular hypertrophy was indexed to body surface area or height 2.7 and Pϭ0.05 when indexed to fat-free mass). Ethnic disparities in left ventricular mass persisted in multivariable models despite adjustment for fat mass, fat-free mass, systolic blood pressure, age, gender, and measures of socioeconomic status. We conclude that blacks compared with whites have increased left ventricular mass and a 2-to 3-fold higher prevalence of left ventricular hypertrophy in the general population, as assessed by cardiac MRI. The ethnic differences in left ventricular mass are independent of differences in body composition.

Aim To identify distinct phenotypic subgroups in a highly‐dimensional, mixed‐data cohort of individuals with heart failure (HF) with preserved ejection fraction (HFpEF) using unsupervised clustering analysis. Methods and results The study included all Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) participants from the Americas (n = 1767). In the subset of participants with available echocardiographic data (derivation cohort, n = 654), we characterized three mutually exclusive phenogroups of HFpEF participants using penalized finite mixture model‐based clustering analysis on 61 mixed‐data phenotypic variables. Phenogroup 1 had higher burden of co‐morbidities, natriuretic peptides, and abnormalities in left ventricular structure and function; phenogroup 2 had lower prevalence of cardiovascular and non‐cardiac co‐morbidities but higher burden of diastolic dysfunction; and phenogroup 3 had lower natriuretic peptide levels, intermediate co‐morbidity burden, and the most favourable diastolic function profile. In adjusted Cox models, participants in phenogroup 1 (vs. phenogroup 3) had significantly higher risk for all adverse clinical events including the primary composite endpoint, all‐cause mortality, and HF hospitalization. Phenogroup 2 (vs. phenogroup 3) was significantly associated with higher risk of HF hospitalization but a lower risk of atherosclerotic event (myocardial infarction, stroke, or cardiovascular death), and comparable risk of mortality. Similar patterns of association were also observed in the non‐echocardiographic TOPCAT cohort (internal validation cohort, n = 1113) and an external cohort of patients with HFpEF [Phosphodiesterase‐5 Inhibition to Improve Clinical Status and Exercise Capacity in Heart Failure with Preserved Ejection Fraction (RELAX) trial cohort, n = 198], with the highest risk of adverse outcome noted in phenogroup 1 participants. Conclusions Machine learning‐based cluster analysis can identify phenogroups of patients with HFpEF with distinct clinical characteristics and long‐term outcomes.

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Our results demonstrate that careful color flow mapping of the vena contracta of the MR jet provides a simple quantitative assessment of MR that correlates well with quantitative Doppler techniques.