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OBJECTIVE: Prior evidence has suggested the multisystem symptomatic manifestations of post-acute COVID-19 condition (PCC). Here we conducted a network cluster analysis of 24 WHO proposed symptoms to identify potential latent subclasses of PCC. STUDY DESIGN AND SETTING: Individuals with a positive test of or diagnosed with SARS-CoV-2 after 09/2020 and with at least one symptom within ≥90 to 365 days following infection were included. Sub-analyses were conducted among people with ≥3 different symptoms. Summary characteristics were provided for each cluster. All analyses were conducted separately in 9 databases from 7 countries, including data from primary care, hospitals, national health claims and national health registries, allowing to compare clusters across the different healthcare settings. RESULTS: 787,078 persons with PCC were included. Single-symptom clusters were common across all databases, particularly for joint pain, anxiety, depression and allergy. Complex clusters included anxiety-depression and abdominal-gastrointestinal symptoms. CONCLUSION: Substantial heterogeneity within and between PCC clusters was seen across healthcare settings. Current definitions of PCC should be critically reviewed to reflect this variety in clinical presentation.

Original publication

DOI

10.1016/j.jclinepi.2025.111867

Type

Journal article

Journal

J Clin Epidemiol

Publication Date

13/06/2025

Keywords

Clustering, Latent class analysis, Long COVID, Post-acute COVID-19 condition, Real-world data