Interim Analysis of Risk Factors for Severe Outcomes among a Cohort of Hospitalized Adults Identified through the U.S. Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET)

BackgroundAs of May 15, 2020, the United States has reported the greatest number of coronavirus disease 2019 (COVID-19) cases and deaths globally. ObjectiveTo describe risk factors for severe outcomes among adults hospitalized with COVID-19. DesignCohort study of patients identified through the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network. Setting154 acute care hospitals in 74 counties in 13 states. Patients2491 patients hospitalized with laboratory-confirmed COVID-19 during March 1-May 2, 2020. MeasurementsAge, sex, race/ethnicity, and underlying medical conditions. ResultsNinety-two percent of patients had [≥]1 underlying condition; 32% required intensive care unit (ICU) admission; 19% invasive mechanical ventilation; 15% vasopressors; and 17% died during hospitalization. Independent factors associated with ICU admission included ages 50-64, 65-74, 75-84 and [≥]85 years versus 18-39 years (adjusted risk ratio (aRR) 1.53, 1.65, 1.84 and 1.43, respectively); male sex (aRR 1.34); obesity (aRR 1.31); immunosuppression (aRR 1.29); and diabetes (aRR 1.13). Independent factors associated with in-hospital mortality included ages 50-64, 65-74, 75-84 and [≥]85 years versus 18-39 years (aRR 3.11, 5.77, 7.67 and 10.98, respectively); male sex (aRR 1.30); immunosuppression (aRR 1.39); renal disease (aRR 1.33); chronic lung disease (aRR 1.31); cardiovascular disease (aRR 1.28); neurologic disorders (aRR 1.25); and diabetes (aRR 1.19). Race/ethnicity was not associated with either ICU admission or death. LimitationData were limited to patients who were discharged or died in-hospital and had complete chart abstractions; patients who were still hospitalized or did not have accessible medical records were excluded. ConclusionIn-hospital mortality for COVID-19 increased markedly with increasing age. These data help to characterize persons at highest risk for severe COVID-19-associated outcomes and define target groups for prevention and treatment strategies. Funding SourceThis work was supported by grant CK17-1701 from the Centers of Disease Control and Prevention through an Emerging Infections Program cooperative agreement and by Cooperative Agreement Number NU38OT000297-02-00 awarded to the Council of State and Territorial Epidemiologists from the Centers for Disease Control and Prevention.