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

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 World Health Organization-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 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.

RESULTS

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.

CONCLUSION

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.