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Updated: May 24, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

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Published on: June 26, 2013

Cluster analysis identifies long COVID subtypes in Belgian patients.

Pamela Mfouth Kemajou¹, Tatiana Besse-Hammer^2,3, Claire Lebouc³

¹School of Public Health, Centre for Research in Epidemiology, Biostatistics and Clinical Research, Université Libre de Bruxelles (ULB), B-1070 Brussels, Belgium.

Biology Methods & Protocols

|October 31, 2024

Summary

This study identified three distinct patient clusters for long COVID, a complex multisystemic condition. Classifying long COVID by clinical syndrome is crucial for personalized patient management and understanding distinct disease mechanisms.

Keywords:

SARS CoV-2 clinical forms clusters long COVID phenotypes

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Published on: July 18, 2017

Area of Science:

Medical Research
Infectious Diseases
Public Health

Background:

Long COVID, a sequela of severe acute respiratory syndrome coronavirus infection, presents as a multisystemic organ disease.
Understanding the heterogeneity of long COVID is essential for developing effective, individualized patient management strategies.
Existing clinical classifications may not fully capture the diverse presentations of long COVID.

Purpose of the Study:

To identify distinct clusters of long COVID patients using multidimensional analysis.
To correlate these patient clusters with established clinical classifications of long COVID.
To inform tailored management strategies for different long COVID patient groups.

Main Methods:

Retrospective cohort study of 205 long COVID patients.
Two-stage multidimensional exploratory analysis, including factorial analysis of mixed data.
Hierarchical clustering following component analysis using demographic, clinical, and biological variables.

Main Results:

Three distinct clusters of long COVID patients were identified through multidimensional analysis.
Biological data showed limited differentiation between the identified patient clusters.
The study identified three clinical forms: long, persistent, and post-viral syndrome.

Conclusions:

Classifying long COVID patients based on their predominant clinical syndrome is vital.
Identified long COVID phenotypes and clinical forms may be linked to specific pathophysiological mechanisms or genetic factors.
Further research is necessary to elucidate the underlying mechanisms and refine classification systems for long COVID.