Evidence map›Paper›PMID 40393039›Full record

ArticlePloS one2025

Comparison of long COVID, recovered COVID, and non-COVID Post-Acute Infection Syndromes over three years.

Caleb R Carr, Nicole L Gentile, Jeanne Bertolli, Warren Szewczyk, Jin-Mann S Lin, Elizabeth R Unger, Quan M Vu, Nona Sotoodehnia, Annette L Fitzpatrick

Abstract readComparative Study
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Observational
  2. Article
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

9 authors.

Caleb R CarrUniversity of Washington School of Medicine, Seattle, Washington, United States of America.
Nicole L GentileDepartment of Family Medicine, University of Washington, Seattle, Washington, United States of America.
Jeanne BertolliDivision of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Warren SzewczykDepartment of Epidemiology, University of Washington, Seattle, Washington, United States of America.ORCID https://orcid.org/0009-0007-1084-5743
Jin-Mann S LinDivision of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Elizabeth R UngerDivision of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.ORCID https://orcid.org/0000-0002-2925-5635
Quan M VuDivision of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Nona SotoodehniaDivision of Cardiology, Department of Medicine, University of Washington, Seattle, Washington, United States of America.
Annette L FitzpatrickDepartment of Family Medicine, University of Washington, Seattle, Washington, United States of America.ORCID https://orcid.org/0000-0003-1941-6586

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComparing the characteristics of patients with long COVID to those with other post-acute infection syndromes (PAIS) could potentially provide clues to common underlying disease processes that may affect patient recovery.

methodsWe identified records of patients who had documented SARS-CoV-2 tests in the University of Washington Medicine electronic health record (EHR) database from January 1, 2019, through January 31, 2022 (n = 139,472). Patients were classified into three groups: 1) long COVID defined by a positive SARS-CoV-2 test and a long COVID-related diagnosis code (n = 580); 2) recovered COVID defined by a positive test and no long COVID associated diagnosis codes (n = 7,437); and 3) non-COVID PAIS defined by a negative test, non-SARS-CoV-2 related PAIS diagnosis codes, and no COVID related codes (n = 106). Using multivariate logistic regression, we compared the clinical characteristics of these groups at three timeframes to address preclinical, acute and post-acute diagnoses: before index SARS-CoV-2 test, within 30 days of index test, and > 30 days after index test.

resultsThe long COVID group had a higher Charlson comorbidity index [median (IQR), 2 (0-4)] than the other two patient groups [median (IQR), 1 (0-3) and 1 (0-3)]. The long COVID and non-COVID PAIS patients were older and had greater smoking exposure than the recovered COVID group. Compared to the recovered COVID control group, the long COVID group had more health problems prior to the infection, including respiratory and metabolic as well as more severe infections and comorbidities based on the ICD codes found in the acute phase records. In the post-acute timeframe, many symptoms were more likely to be associated with long COVID than recovered patients with COVID-19 including abnormalities of heart beat [OR (95% CI), 5.31 (3.96-7.13)], cognition, perception, or emotional state symptoms [OR (95% CI), 5.14 (3.81-6.92)], malaise and fatigue [OR (95% CI), 4.20 (3.13-5.63)], and sleep disorders [OR (95% CI), 2.47, (1.79-3.43)], all p < 0.05. In contrast, the non-COVID PAIS group shared many similarities with the long COVID group across all three timeframes.

conclusionsPatients diagnosed with long COVID were more similar to patients with a non-COVID-related PAIS than to recovered patients with COVID-19. This suggests risk factors for PAIS may be similar and independent of the infectious agent.

Indexed as

COVID-19AdultAgedElectronic Health RecordsFemaleHumansMaleMiddle AgedPost-Acute COVID-19 SyndromeSARS-CoV-2

Identifiers

PMID40393039
PMCPMC12092011

What Socratic holds

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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 Socratic graph.