Evidence map›Paper›PMID 41282756›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Long COVID Longitudinal Symptoms Burden Clusters Within A National Community-Based Cohort.

Yanhan Shen, Zach Shahn, McKaylee M Robertson, Kelly Gebo, Denis Nash

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Yanhan ShenInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, USA.ORCID 0000-0002-9703-4412
Zach ShahnInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, USA.
McKaylee M RobertsonInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, USA.ORCID 0000-0002-8426-6572
Kelly GeboDepartment of Medicine, Johns Hopkins University; Baltimore, MD, USA.
Denis NashInstitute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York, NY, USA.

Funding

Following a U.S. National Cohort of Vulnerable Men to Improve HIV Prevention and CareUH3AI133675 · NIAID · GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY · PI GROV, CHRISTIAN · 2019 to 2021
$6.9M
NIAID NIH HHS UH3 AI133675
6 · The paper itself

Abstract

Background: Long COVID is clinically heterogeneous, with evolving symptom trajectories that complicate classification. Prior clustering studies often rely on Electronic Health Records data, risking underreporting. We used longitudinal, community-based data to characterize symptom clusters and risk factors. Methods: We analyzed CHASING COVID Cohort participants with confirmed SARS-CoV-2 infection between December 2020 and December 2022, ≥12 months of follow-up, and long COVID (≥1 new symptom and concurrent activity limitation 3-12 months post-infection, both absent pre-infection). The infection in this window was the index infection; those with pre-index long COVID were excluded. Symptoms were self-reported pre-infection and at ~3, 6, 9, and 12 months. Missing data were handled via multiple imputation by chained equations (30 datasets). Longitudinal K-means clustering was performed within each imputed dataset, with hierarchical aggregation to derive final assignments. Multivariable logistic regression (adjusting for age, sex) assessed associations of demographic, clinical, and social factors with cluster membership. Within the highest-burden cluster, hierarchical clustering identified symptom phenotypes. Results: Of 1,787 infected participants, 511 met criteria (22% ≥50 years; 55% female; 60% White non-Hispanic; 54% mental health disorder; 7.2% immunodeficiency; 21% ≥2 comorbidities; 30% prior infection; 24% never vaccinated pre-index). Three clusters emerged: highest, moderate, and lowest burden. The highest-burden cluster (median 6 symptoms at 6 and 9 months) was characterized by fatigue (57%-74%), concentration difficulty, post-exertional malaise, myalgia, sleep disturbance, gastrointestinal symptoms, headache, irritability, and mobility limitations (each ~46%-53%). The moderate cluster peaked at 3 symptoms (fatigue 42%); the lowest remained ~1 symptom (fatigue 24% at 12 months). Older age (aOR 2.68, 95% CI 1.59-4.53), female sex (2.36, 1.48-3.76), mental health disorder (2.65, 1.65-4.25), and immunodeficiency (4.23, 1.71-10.51) were associated with highest vs lowest burden. Within the highest-burden cluster, three phenotypes emerged: neurological/multisystemic, psychiatric/neurological, and physical/respiratory. Conclusions: Distinct long-COVID clusters and phenotypes underscore heterogeneity and support tailored management and risk stratification.

Indexed as

clusterslong COVIDlongitudinalSARS-CoV-2symptoms

Identifiers

PMID41282756
PMCPMC12637793

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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.