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Clinical Phenotype Classification of Atrial Fibrillation Patients Using Cluster Analysis and Associations with

Marco Vitolo1,2,3, Marco Proietti1,4,5, Alena Shantsila1

  • 1Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool L7 8TX, UK.

Biomedicines
|August 6, 2021
PubMed

Insights

Atrial fibrillation (AF) patient heterogeneity necessitates a phenotype-driven approach. Cluster analysis revealed four distinct AF patient groups with unique characteristics and outcomes, highlighting the need for personalized management strategies to improve patient health.

Area of Science:

  • Cardiology
  • Clinical Research
  • Data Science

Background:

  • Atrial fibrillation (AF) patient populations exhibit significant clinical heterogeneity.
  • Conventional classification methods may not fully capture this diversity.
  • Identifying distinct patient phenotypes is crucial for effective management.

Purpose of the Study:

  • To identify distinct clinical phenotypes within the atrial fibrillation (AF) patient population using cluster analysis.
  • To evaluate the association between identified AF patient clusters and key clinical outcomes.

Main Methods:

  • Hierarchical cluster analysis was performed on 3980 AF patients from the AMADEUS and BOREALIS trials.
  • Patients were treated with Vitamin-K Antagonist.
  • Primary outcome: composite of stroke/thromboembolism, cardiovascular death, myocardial infarction, and all-cause death. Secondary outcomes included major bleeding.

Main Results:

  • Four distinct AF patient clusters were identified based on clinical characteristics and comorbidities.
  • Cluster 4, characterized by the highest burden of non-cardiovascular comorbidities, exhibited the highest cumulative risk of adverse outcomes.
  • Compared to Cluster 1 (low comorbidity burden), Cluster 4 showed significantly increased risks for the composite outcome, all-cause death, and major bleeding.

Conclusions:

  • Cluster analysis successfully identified four clinically relevant AF patient phenotypes.
  • These phenotypes possess unique characteristics and are associated with differential clinical outcomes.
  • A phenotype-driven management approach for AF patients is warranted to address heterogeneity and improve outcomes.
Abstract

Keywords:
atrial fibrillationcluster analysisphenotype classificationstroke

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