Clustering Analysis Identified Three Long COVID Phenotypes and Their Association with General Health Status and Working Ability.

Kisiel MA, Lee S, Malmquist S, Rykatkin O, Holgert S, Janols H, Janson C, Zhou X

J Clin Med 12 (11) - [2023-05-23; online 2023-05-23]

This study aimed to distinguish different phenotypes of long COVID through the post-COVID syndrome (PCS) score based on long-term persistent symptoms following COVID-19 and evaluate whether these symptoms affect general health and work ability. In addition, the study identified predictors for severe long COVID. This cluster analysis included cross-sectional data from three cohorts of patients after COVID-19: non-hospitalized (n = 401), hospitalized (n = 98) and those enrolled at the post-COVID outpatient's clinic (n = 85). All the subjects responded to the survey on persistent long-term symptoms and sociodemographic and clinical factors. K-Means cluster analysis and ordinal logistic regression were used to create PCS scores that were used to distinguish patients' phenotypes. 506 patients with complete data on persistent symptoms were divided into three distinct phenotypes: none/mild (59%), moderate (22%) and severe (19%). The patients with severe phenotype, with the predominating symptoms were fatigue, cognitive impairment and depression, had the most reduced general health status and work ability. Smoking, snuff, body mass index (BMI), diabetes, chronic pain and symptom severity at COVID-19 onset were factors predicting severe phenotype. This study suggested three phenotypes of long COVID, where the most severe was associated with the highest impact on general health status and working ability. This knowledge on long COVID phenotypes could be used by clinicians to support their medical decisions regarding prioritizing and more detailed follow-up of some patient groups.

Category: Post-COVID

Category: Social Science & Humanities

Type: Journal article

PubMed 37297812

DOI 10.3390/jcm12113617

Crossref 10.3390/jcm12113617

pmc: PMC10253616
pii: jcm12113617


Publications 9.5.1