TY - JOUR
T1 - Factors Associated with COVID-19 Death in the United States
T2 - Cohort Study
AU - Chen, Uan I.
AU - Xu, Hua
AU - Krause, Trudy Millard
AU - Greenberg, Raymond
AU - Dong, Xiao
AU - Jiang, Xiaoqian
N1 - Funding Information:
eGFR: estimated glomerular filtration rate EHR: electronic health record HbA1C: glycated hemoglobin HR: hazard ratio ICD: International Classification of Diseases N3C: National COVID Cohort Collaborative NIH: National Institutes of Health NSF: National Science Foundation OCS: oral corticosteroids PCR: polymerase chain reaction SBMI: School of Biomedical Informatics UT: University of Texas UTHealth: University of Texas Health Science Center
Funding Information:
XJ is a Cancer Prevention & Research Institute of Texas (CPRIT) Scholar in Cancer Research (RR180012), and he was supported in part by a Christopher Sarofim Family Professorship; University of Texas (UT) Stars award; University of Texas Health Science Center (UTHealth) startup; the National Institutes of Health (NIH) under award numbers R01AG066749, R01AG066749-S1, and U01TR002062; and the National Science Foundation (NSF) RAPID #2027790.
Publisher Copyright:
©Uan-I Chen, Hua Xu, Trudy Millard Krause, Raymond Greenberg, Xiao Dong, Xiaoqian Jiang.
PY - 2022/5/1
Y1 - 2022/5/1
N2 - Background: Since the initial COVID-19 cases were identified in the United States in February 2020, the United States has experienced a high incidence of the disease. Understanding the risk factors for severe outcomes identifies the most vulnerable populations and helps in decision-making. Objective: This study aims to assess the factors associated with COVID-19–related deaths from a large, national, individual-level data set. Methods: A cohort study was conducted using data from the Optum de-identified COVID-19 electronic health record (EHR) data set; 1,271,033 adult participants were observed from February 1, 2020, to August 31, 2020, until their deaths due to COVID-19, deaths due to other reasons, or the end of the study. Cox proportional hazards models were constructed to evaluate the risks for each patient characteristic. Results: A total of 1,271,033 participants (age: mean 52.6, SD 17.9 years; male: 507,574/1,271,033, 39.93%) were included in the study, and 3315 (0.26%) deaths were attributed to COVID-19. Factors associated with COVID-19–related death included older age (80 vs 50-59 years old: hazard ratio [HR] 13.28, 95% CI 11.46-15.39), male sex (HR 1.68, 95% CI 1.57-1.80), obesity (BMI 40 vs <30 kg/m2: HR 1.71, 95% CI 1.50-1.96), race (Hispanic White, African American, Asian vs non-Hispanic White: HR 2.46, 95% CI 2.01-3.02; HR 2.27, 95% CI 2.06-2.50; HR 2.06, 95% CI 1.65-2.57), region (South, Northeast, Midwest vs West: HR 1.62, 95% CI 1.33-1.98; HR 2.50, 95% CI 2.06-3.03; HR 1.35, 95% CI 1.11-1.64), chronic respiratory disease (HR 1.21, 95% CI 1.12-1.32), cardiac disease (HR 1.10, 95% CI 1.01-1.19), diabetes (HR 1.92, 95% CI 1.75-2.10), recent diagnosis of lung cancer (HR 1.70, 95% CI 1.14-2.55), severely reduced kidney function (HR 1.92, 95% CI 1.69-2.19), stroke or dementia (HR 1.25, 95% CI 1.15-1.36), other neurological diseases (HR 1.77, 95% CI 1.59-1.98), organ transplant (HR 1.35, 95% CI 1.09-1.67), and other immunosuppressive conditions (HR 1.21, 95% CI 1.01-1.46). Conclusions: This is one of the largest national cohort studies in the United States; we identified several patient characteristics associated with COVID-19–related deaths, and the results can serve as the basis for policy making. The study also offered directions for future studies, including the effect of other socioeconomic factors on the increased risk for minority groups.
AB - Background: Since the initial COVID-19 cases were identified in the United States in February 2020, the United States has experienced a high incidence of the disease. Understanding the risk factors for severe outcomes identifies the most vulnerable populations and helps in decision-making. Objective: This study aims to assess the factors associated with COVID-19–related deaths from a large, national, individual-level data set. Methods: A cohort study was conducted using data from the Optum de-identified COVID-19 electronic health record (EHR) data set; 1,271,033 adult participants were observed from February 1, 2020, to August 31, 2020, until their deaths due to COVID-19, deaths due to other reasons, or the end of the study. Cox proportional hazards models were constructed to evaluate the risks for each patient characteristic. Results: A total of 1,271,033 participants (age: mean 52.6, SD 17.9 years; male: 507,574/1,271,033, 39.93%) were included in the study, and 3315 (0.26%) deaths were attributed to COVID-19. Factors associated with COVID-19–related death included older age (80 vs 50-59 years old: hazard ratio [HR] 13.28, 95% CI 11.46-15.39), male sex (HR 1.68, 95% CI 1.57-1.80), obesity (BMI 40 vs <30 kg/m2: HR 1.71, 95% CI 1.50-1.96), race (Hispanic White, African American, Asian vs non-Hispanic White: HR 2.46, 95% CI 2.01-3.02; HR 2.27, 95% CI 2.06-2.50; HR 2.06, 95% CI 1.65-2.57), region (South, Northeast, Midwest vs West: HR 1.62, 95% CI 1.33-1.98; HR 2.50, 95% CI 2.06-3.03; HR 1.35, 95% CI 1.11-1.64), chronic respiratory disease (HR 1.21, 95% CI 1.12-1.32), cardiac disease (HR 1.10, 95% CI 1.01-1.19), diabetes (HR 1.92, 95% CI 1.75-2.10), recent diagnosis of lung cancer (HR 1.70, 95% CI 1.14-2.55), severely reduced kidney function (HR 1.92, 95% CI 1.69-2.19), stroke or dementia (HR 1.25, 95% CI 1.15-1.36), other neurological diseases (HR 1.77, 95% CI 1.59-1.98), organ transplant (HR 1.35, 95% CI 1.09-1.67), and other immunosuppressive conditions (HR 1.21, 95% CI 1.01-1.46). Conclusions: This is one of the largest national cohort studies in the United States; we identified several patient characteristics associated with COVID-19–related deaths, and the results can serve as the basis for policy making. The study also offered directions for future studies, including the effect of other socioeconomic factors on the increased risk for minority groups.
KW - COVID-19
KW - EHR data
KW - cohort studies
KW - risk factors
KW - survival analysis
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U2 - 10.2196/29343
DO - 10.2196/29343
M3 - Article
C2 - 35377319
AN - SCOPUS:85130597699
SN - 2369-2960
VL - 8
JO - JMIR Public Health and Surveillance
JF - JMIR Public Health and Surveillance
IS - 5
M1 - e29343
ER -