Evidence map›Paper›PMID 38383883›Full record

ArticleCommunications medicine2024

A cross-sectional and population-based study from primary care on post-COVID-19 conditions in non-hospitalized patients.

Dominik J Ose, Elena Gardner, Morgan Millar, Andrew Curtin, Jiqiang Wu, Mingyuan Zhang, Camie Schaefer, Jing Wang, Jennifer Leiser, Kirsten Stoesser and 1 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Communications medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

5 · Who and what money

Authors and funding

11 authors at 1 institution in 2 countries.

Dominik J Ose *University of Utah Health, School of Medicine, Department of Family and Preventive Medicine, Salt Lake City, UT, USA.ORCID http://orcid.org/0000-0002-5079-2152
Elena Gardner *University of Utah Health, School of Medicine, Department of Family and Preventive Medicine, Salt Lake City, UT, USA.
Morgan MillarUniversity of Utah Health, School of Medicine, Department of Internal Medicine, Salt Lake City, UT, USA.ORCID http://orcid.org/0000-0001-5532-6970
Andrew CurtinUniversity of Utah Health, School of Medicine, Department of Family and Preventive Medicine, Salt Lake City, UT, USA.
Jiqiang WuUniversity of Utah Health, School of Medicine, Department of Family and Preventive Medicine, Salt Lake City, UT, USA.
Mingyuan ZhangUniversity of Utah Health, Data Science Services, Salt Lake City, UT, USA.ORCID http://orcid.org/0000-0002-9837-4187
Camie SchaeferUniversity of Utah Health, School of Medicine, Department of Family and Preventive Medicine, Salt Lake City, UT, USA.
Jing WangUniversity of Utah Health, School of Medicine, Department of Family and Preventive Medicine, Salt Lake City, UT, USA.
Jennifer LeiserUniversity of Utah Health, School of Medicine, Department of Family and Preventive Medicine, Salt Lake City, UT, USA.ORCID http://orcid.org/0000-0001-6152-6143
Kirsten StoesserUniversity of Utah Health, School of Medicine, Department of Family and Preventive Medicine, Salt Lake City, UT, USA.ORCID http://orcid.org/0000-0001-9108-4438
Bernadette KiralyUniversity of Utah Health, School of Medicine, Department of Family and Preventive Medicine, Salt Lake City, UT, USA. bernadette.kiraly@hsc.utah.edu.ORCID http://orcid.org/0000-0003-2243-6553
University of Utah · US

Funding

Utah Center for Clinical and Translational ScienceUL1TR002538 · NCATS · UNIVERSITY OF UTAH · PI HESS, RACHEL, MAJERSIK, JENNIFER JUHL · 2018 to 2022
$26.0M
CTSA UM1 Program at University of UtahUM1TR004409 · NCATS · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI RACHEL HESS, Jennifer Juhl Majersik · 2023 to 2026
$21.9M
NCATS NIH HHS UL1 TR002538NCATS NIH HHS UM1 TR004409
6 · The paper itself

Abstract

backgroundCurrent research on post-COVID-19 conditions (PCC) has focused on hospitalized COVID-19 patients, and often lacks a comparison group. This study assessed the prevalence of PCC in non-hospitalized COVID-19 primary care patients compared to primary care patients not diagnosed with COVID-19.

methodsThis cross-sectional, population-based study (n = 2539) analyzed and compared the prevalence of PCC in patients with a positive COVID-19 test (n = 1410) and patients with a negative COVID-19 test (n = 1129) never hospitalized for COVID-19 related conditions. Participants were identified using electronic health records and completed an electronic questionnaire, available in English and Spanish, including 54 potential post COVID-19 symptoms. Logistic regression was conducted to assess the association of PCC with COVID-19.

resultsPost-COVID-19 conditions are prevalent in both groups, and significantly more prevalent in patients with COVID-19. Strong significant differences exist for the twenty most reported conditions, except for anxiety. Common conditions are fatigue (59.5% (COVID-19 positive) vs. 41.3% (COVID-19 negative); OR 2.15 [1.79-2.60]), difficulty sleeping (52.1% (positive) vs. 41.9% (negative); OR 1.42 [1.18-1.71]) and concentration problems (50.6% (positive) vs 28.5% (negative); OR 2.64 [2.17-3.22]). Similar disparities in prevalence are also observed after comparing two groups (positive vs. negative) by age, sex, time since testing, and race/ethnicity.

conclusionsPCC is highly prevalent in non-hospitalized COVID-19 patients in primary care. However, it is important to note that PCC strongly overlaps with common health symptoms seen in primary care, including fatigue, difficulty sleeping, and headaches, which makes the diagnosis of PCC in primary care even more challenging.

Identifiers

PMID38383883
PMCPMC10881566
OpenAlexW4391998496

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.