Evidence map›Paper›PMID 35784256›Full record

ArticleFrontiers in public health2022

How Different Pre-existing Mental Disorders and Their Co-occurrence Affects COVID-19 Clinical Outcomes? A Real-World Data Study in the Southern United States.

Shan Qiao, Jiajia Zhang, Shujie Chen, Bankole Olatosi, Suzanne Hardeman, Meera Narasimhan, Larisa Bruner, Abdoulaye Diedhiou, Cheryl Scott, Ali Mansaray and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 29% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

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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

12 authors at 3 institutions in 1 country.

Shan QiaoDepartment of Health Promotion Education and Behavior, South Carolina StateSmart Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Jiajia ZhangDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Shujie ChenDepartment of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
Bankole OlatosiDepartment of Health Services Policy and Management, School of Public Health, University of South Carolina, Columbia, SC, United States.
Suzanne HardemanDepartment of Neuropsychiatry and Behavioral Science, Prisma Health (Midlands), Columbia, SC, United States.
Meera NarasimhanDepartment of Neuropsychiatry and Behavioral Science, Prisma Health (Midlands), Columbia, SC, United States.
Larisa BrunerSouth Carolina Department of Health and Environmental Control, Columbia, SC, United States.
Abdoulaye DiedhiouSouth Carolina Department of Health and Environmental Control, Columbia, SC, United States.
Cheryl ScottSouth Carolina Department of Health and Environmental Control, Columbia, SC, United States.
Ali MansaraySouth Carolina Department of Health and Environmental Control, Columbia, SC, United States.
Sharon WeissmanDepartment of Internal Medicine, School of Medicine, University of South Carolina, Columbia, SC, United States.
Xiaoming LiDepartment of Health Promotion Education and Behavior, South Carolina StateSmart Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, United States.
University of South Carolina · USSouth Carolina Department of Health and Environmental Control · USPrisma Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Although a psychiatric history might be an independent risk factor for COVID-19 infection and mortality, no studies have systematically investigated how different clusters of pre-existing mental disorders may affect COVID-19 clinical outcomes or showed how the coexistence of mental disorder clusters is related to COVID-19 clinical outcomes. Methods: Using a retrospective cohort study design, a total of 476,775 adult patients with lab-confirmed and probable COVID-19 between March 06, 2020 and April 14, 2021 in South Carolina, United States were included in the current study. The electronic health record data of COVID-19 patients were linked to all payer-based claims data through the SC Revenue and Fiscal Affairs Office. Pre-existing mental disorder diagnoses from Jan 2, 2019 to Jan 14, 2021 were extracted from the patients' healthcare utilization data via ICD-10 codes. Results: There is an elevated risk of COVID-19-related hospitalization and death among participants with pre-existing mental disorders adjusting for key socio-demographic and comorbidity covariates. Co-occurrence of any two clusters was positively associated with COVID-19-related hospitalization and death. The odds ratio of being hospitalized was 1.26 (95% CI: 1.151, 1.383) for patients with internalizing and externalizing disorders, 1.65 (95% CI: 1.298, 2.092) for internalizing and thought disorders, 1.76 (95% CI: 1.217, 2.542) for externalizing and thought disorders, and 1.64 (95% CI: 1.274, 2.118) for three clusters of mental disorders. Conclusions: Pre-existing internalizing disorders and thought disorders are positively related to COVID-19 hospitalization and death. Co-occurrence of any two clusters of mental disorders have elevated risk of COVID-19-related hospitalization and death compared to those with a single cluster.

Indexed as

COVID-19Mental DisordersAdultComorbidityHumansPreexisting Condition CoverageRetrospective StudiesUnited Statesco-occurrenceCOVID-19 outcomeselectronic health records (EHRs)pre-existing mental disordersUnited States

Identifiers

PMID35784256
PMCPMC9244141
OpenAlexW4282975568

What OpenQuestion holds

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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.