Evidence map›Paper›PMID 34552997›Full record

ArticleOpen forum infectious diseases2021

Demographic Disparities in Clinical Outcomes of COVID-19: Data From a Statewide Cohort in South Carolina.

Xueying Yang, Jiajia Zhang, Shujie Chen, Bankole Olatosi, Larisa Bruner, Abdoulaye Diedhiou, Cheryl Scott, Ali Mansaray, Sharon Weissman, Xiaoming Li

Abstract read
In one paragraph

Article in Open forum infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Xueying YangSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.ORCID https://orcid.org/0000-0001-6788-0688
Jiajia ZhangSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.ORCID https://orcid.org/0000-0003-4566-0822
Shujie ChenSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
Bankole OlatosiSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.ORCID https://orcid.org/0000-0002-8295-8735
Larisa BrunerSouth Carolina Department of Health and Environmental Control, Columbia, South Carolina, USA.
Abdoulaye DiedhiouSouth Carolina Department of Health and Environmental Control, Columbia, South Carolina, USA.
Cheryl ScottSouth Carolina Department of Health and Environmental Control, Columbia, South Carolina, USA.
Ali MansaraySouth Carolina Department of Health and Environmental Control, Columbia, South Carolina, USA.
Sharon WeissmanSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.
Xiaoming LiSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrent 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.

methodsWe 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.

resultsAmong 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

conclusionsAs 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.

Indexed as

COVID-19disease severityhospitalizationmortalitySouth Carolina

Identifiers

PMID34552997
PMCPMC8436371

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.