Clusters of post-acute COVID-19 symptoms: a latent class analysis across 9 databases and 7 countries

Prior evidence has suggested the multisystem symptomatic manifestations of post-acute COVID-19 condition (PCC). Here we conducted a network cluster analysis of 24 World Health Organization–proposed symptoms to identify potential latent subclasses of PCC. Individuals with a positive test of or diagno...

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Bibliographic Details
Published in:Journal of clinical epidemiology Vol. 185; p. 111867
Main Authors: López-Güell, Kim, Català, Martí, Dedman, Daniel, Duarte-Salles, Talita, Kolde, Raivo, López-Blasco, Raúl, Martínez, Álvaro, Mercier, Gregoire, Abellan, Alicia, Arinze, Johnmary T., Burkard, Theresa, Burn, Edward, Cuccu, Zara, Delmestri, Antonella, Delseny, Dominique, Khalid, Sara, Kim, Chungsoo, Kim, Ji-woo, Kostka, Kristin, Loste, Cora, Mayer, Miguel A., Meléndez-Cardiel, Jaime, Mercadé-Besora, Núria, Mosseveld, Mees, Nishimura, Akihito, Nordeng, Hedvig ME, Oyinlola, Jessie O., Paredes, Roger, Pérez-Crespo, Laura, Pineda-Moncusí, Marta, Ramírez-Anguita, Juan Manuel, Trinh, Nhung T.H., Uusküla, Anneli, Valdivieso, Bernardo, Prieto-Alhambra, Daniel, Xie, Junqing, Mateu, Lourdes, Jödicke, Annika M.
Format: Journal Article
Language:English
Published: United States Elsevier Inc 01.09.2025
Elsevier Limited
Subjects:
Adult
Aged
Algorithms
Allergies
Anxiety
Arthralgia
Cluster Analysis
Clustering
COVID-19
COVID-19 - complications
COVID-19 - epidemiology
Data models
Databases, Factual
Dyspnea
Fatigue
Female
Gastrointestinal symptoms
Health care
Health care policy
Heterogeneity
Hospitals
Humans
Internal Medicine
Latent Class Analysis
Long COVID
Male
Mental depression
Middle Aged
Pain
Post-acute COVID-19 condition
Post-Acute COVID-19 Syndrome
Primary care
Real-world data
SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2
Viral diseases
Netherlands
United Kingdom > UK
United States > US
Norway
France
Estonia
Spain
Post-acute COVID-19 condition
Long COVID
Clustering
Latent class analysis
Real-world data
ISSN:0895-4356, 1878-5921, 1878-5921
Online Access:Get full text
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Summary:Prior evidence has suggested the multisystem symptomatic manifestations of post-acute COVID-19 condition (PCC). Here we conducted a network cluster analysis of 24 World Health Organization–proposed symptoms to identify potential latent subclasses of PCC. Individuals with a positive test of or diagnosed with SARS-CoV-2 after September 2020 and with at least 1 symptom within ≥90 to 365 days following infection were included. Subanalyses 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. This study included 787,078 persons with PCC. 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. Substantial heterogeneity within and between PCC clusters was seen across health-care settings. Current definitions of PCC should be critically reviewed to reflect this variety in clinical presentation. •This study included 787,078 persons with post-acute COVID-19 condition (PCC), which makes it the largest international PCC study to our knowledge.•Complex multisymptomatic clusters included anxiety-depression, abdominal-gastrointestinal symptoms, and respiratory problems with fatigue and joint pain.•Substantial heterogeneity was seen across health-care settings.
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ISSN:0895-4356
1878-5921
1878-5921
DOI:10.1016/j.jclinepi.2025.111867