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)
2020
Background: As of May 15, 2020, the United States has reported the greatest number of coronavirus disease 2019 (COVID-19) cases and deaths globally.
Objective: To describe risk factors for severe outcomes among adults hospitalized with COVID-19.
Design: Cohort study of patients identified through the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network.
Setting: 154 acute care hospitals in 74 counties in 13 states.
Patients: 2491 patients hospitalized with laboratory-confirmed COVID-19 during March 1-May 2, 2020.
Measurements: Age, sex, race/ethnicity, and underlying medical conditions.
Results: Ninety-two percent of patients had at least 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.
Limitation: Data 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.
Conclusion: In-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.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
10
References
13
Citations
NaN
KQI