Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study

Matthew J Cummings; Matthew R Baldwin; Darryl Abrams; Samuel D Jacobson; Benjamin J Meyer; Elizabeth M Balough; Justin G Aaron; Jan Claassen; LeRoy E Rabbani; Jonathan Hastie; Beth R Hochman; John Salazar-Schicchi; Natalie H Yip; Daniel Brodie; Max R O'Donnell

Continuous variables were expressed as means (standard deviation) and medians (interquartile ranges). Categorical variables were summarized as counts and percentages. Missing data was rare and not imputed. We created Kaplan-Meier survival plots and used the log rank test to compare survival patterns by co-morbidity. We estimated hazard ratios for death using Cox proportional-hazards models. We measured time-to-event in days from the date of hospital admission to the date of in-hospital death or hospital discharge alive. Follow-up time was rightcensored on April 14 th , 2020. We included age, sex, duration of symptoms prior to hospital presentation, severe obesity (defined as body-mass-index ≥ 35), and co-morbidities (hypertension, chronic cardiovascular, pulmonary, and kidney disease and diabetes mellitus) as independent variables in our Cox models. We also included serum IL-6 and plasma d-dimer concentrations as independent variables in our models because there is emerging evidence of dysregulated immune activation and coagulopathy in patients with severe COVID-19, and interest in treating this patient population with targeted immunomodulatory therapies and anticoagulation. 13, 14 We confirmed the proportional hazards assumption of the Cox models using the Schoenfeld residuals test. All analyses were performed using Stata (version 16, StataCorp, College Station, TX, USA).