Identification of Distinct Long COVID Clinical Phenotypes Through Cluster Analysis of Self-Reported Symptoms.

ABSTRACT:

Background

We aimed to describe the clinical presentation of individuals presenting with prolonged recovery from coronavirus disease 2019 (COVID-19), known as long COVID.

Methods

This was an analysis within a multicenter, prospective cohort study of individuals with a confirmed diagnosis of COVID-19 and persistent symptoms >4 weeks from onset of acute symptoms. We performed a multiple correspondence analysis (MCA) on the most common self-reported symptoms and hierarchical clustering on the results of the MCA to identify symptom clusters.

Results

Two hundred thirty-three individuals were included in the analysis; the median age of the cohort was 43 (interquartile range [IQR], 36-54) years, 74% were women, and 77.3% reported a mild initial illness. MCA and hierarchical

SUBMITTER: Kenny G 

PROVIDER: S-EPMC8900926 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature