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Demographic Disparities in Clinical Outcomes of COVID-19: Data From a Statewide Cohort in South Carolina.
Yang, Xueying; Zhang, Jiajia; Chen, Shujie; Olatosi, Bankole; Bruner, Larisa; Diedhiou, Abdoulaye; Scott, Cheryl; Mansaray, Ali; Weissman, Sharon; Li, Xiaoming.
  • Yang X; South Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
  • Zhang J; University of South Carolina Big Data Health Science Center, Columbia, South Carolina, USA.
  • Chen S; Department of Health Promotion, Education and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
  • Olatosi B; South Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
  • Bruner L; University of South Carolina Big Data Health Science Center, Columbia, South Carolina, USA.
  • Diedhiou A; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
  • Scott C; South Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
  • Mansaray A; University of South Carolina Big Data Health Science Center, Columbia, South Carolina, USA.
  • Weissman S; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
  • Li X; South Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
Open Forum Infect Dis ; 8(9): ofab428, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1434434
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ABSTRACT

BACKGROUND:

Current literature examining the clinical characteristics of coronavirus disease 2019 (COVID-19) patients under-represent COVID-19 cases who were either asymptomatic or had mild symptoms.

METHODS:

We analyzed statewide data from 280 177 COVID-19 cases from various health care facilities during March 4-December 31, 2020. Each COVID-19 case was reported using the standardized Case Report Form (CRF), which collected information on demographic characteristics, symptoms, hospitalization, and death. We used multivariable logistic regression to analyze the associations between sociodemographics and disease severity, hospitalization, and mortality.

RESULTS:

Among a total of 280 177 COVID-19 cases, 5.2% (14 451) were hospitalized and 1.9% (5308) died. Older adults, males, and Black individuals had higher odds of hospitalization and death from COVID-19 (all P < 0.0001). In particular, individuals residing in rural areas experienced a high risk of death (odds ratio [OR], 1.16; 95% CI, 1.08-1.25). Regarding disease severity, older adults (OR, 1.06; 95% CI, 1.03-1.10) and Hispanic or Latino patients (OR, 2.06; 95% CI, 1.95-2.18) had higher odds of experiencing moderate/severe symptoms, while male and Asian patients, compared with White patients, had lower odds of experiencing moderate/severe symptoms.

CONCLUSIONS:

As the first statewide population-based study using data from multiple health care systems with a long follow-up period in the United States, we provide a more generalizable picture of COVID-19 symptoms and clinical outcomes. The findings from this study reinforce the fact that rural residence and racial/ethnic social determinants of health, unfortunately, remain predictors of adverse health outcomes for COVID-19 patients.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Observational study / Prognostic study Topics: Long Covid Language: English Journal: Open Forum Infect Dis Year: 2021 Document Type: Article Affiliation country: Ofid

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Observational study / Prognostic study Topics: Long Covid Language: English Journal: Open Forum Infect Dis Year: 2021 Document Type: Article Affiliation country: Ofid