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Long COVID Classification: Findings from a Clustering Analysis in the Predi-COVID Cohort Study

The increasing number of people living with Long COVID requires the development of more personalized care; currently, limited treatment options and rehabilitation programs adapted to the variety of Long COVID presentations are available. Our objective was to design an easy-to-use Long COVID classifi...

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Published in:International journal of environmental research and public health 2022-11, Vol.19 (23), p.16018
Main Authors: Fischer, Aurélie, Badier, Nolwenn, Zhang, Lu, Elbéji, Abir, Wilmes, Paul, Oustric, Pauline, Benoy, Charles, Ollert, Markus, Fagherazzi, Guy
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creator Fischer, Aurélie
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description The increasing number of people living with Long COVID requires the development of more personalized care; currently, limited treatment options and rehabilitation programs adapted to the variety of Long COVID presentations are available. Our objective was to design an easy-to-use Long COVID classification to help stratify people with Long COVID. Individual characteristics and a detailed set of 62 self-reported persisting symptoms together with quality of life indexes 12 months after initial COVID-19 infection were collected in a cohort of SARS-CoV-2 infected people in Luxembourg. A hierarchical ascendant classification (HAC) was used to identify clusters of people. We identified three patterns of Long COVID symptoms with a gradient in disease severity. Cluster-Mild encompassed almost 50% of the study population and was composed of participants with less severe initial infection, fewer comorbidities, and fewer persisting symptoms (mean = 2.9). Cluster-Moderate was characterized by a mean of 11 persisting symptoms and poor sleep and respiratory quality of life. Compared to the other clusters, Cluster-Severe was characterized by a higher proportion of women and smokers with a higher number of Long COVID symptoms, in particular vascular, urinary, and skin symptoms. Our study evidenced that Long COVID can be stratified into three subcategories in terms of severity. If replicated in other populations, this simple classification will help clinicians improve the care of people with Long COVID.
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source PubMed (Medline); Publicly Available Content Database; Free Full-Text Journals in Chemistry; Coronavirus Research Database
subjects Brief Report
Classification
Clustering
Cohort analysis
Cohort Studies
Comorbidity
Coronaviruses
COVID-19
COVID-19 - epidemiology
Disease
Female
Females
Humans
Hypertension
Illnesses
Infections
Long COVID
Population studies
Post-Acute COVID-19 Syndrome
Quality of Life
Questionnaires
Rehabilitation
SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2
Signs and symptoms
Sleep
title Long COVID Classification: Findings from a Clustering Analysis in the Predi-COVID Cohort Study
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