Background: Patients with atrial fibrillation are characterized by great clinical heterogeneity and com-plexity. The usual classifications may not adequately characterize this population. Data-driven cluster analysis reveals different possible patient classifications.Aims: To identify different clusters of patients with atrial fibrillation who share similar clinical pheno-types, and to evaluate the association between identified clusters and clinical outcomes, using cluster analysis.Methods: An agglomerative hierarchical cluster analysis was performed in non-anticoagulated patients from the Loire Valley Atrial Fibrillation cohort. Associations between clusters and a composite out-come comprising stroke/systemic embolism/death and all-cause death, stroke and major bleeding were evaluated using Cox regression analyses.Results: The study included 3434 non-anticoagulated patients with atrial fibrillation (mean age 70.3 & PLUSMN; 17 years; 42.8% female). Three clusters were identified: cluster 1 was composed of younger patients, with a low prevalence of co-morbidities; cluster 2 included old patients with permanent atrial fibrillation, cardiac pathologies and a high burden of cardiovascular co-morbidities; cluster 3 identified old female patients with a high burden of cardiovascular co-morbidities. Compared with cluster 1, clusters 2 and 3 were independently associated with an increased risk of the composite outcome (hazard ratio 2.85, 95% confidence interval 1.32-6.16 and hazard ratio 1.52, 95% confidence interval 1.09-2.11, respectively) and all-cause death (hazard ratio 3.54, 95% confidence interval 1.49-8.43 and hazard ratio 1.88, 95% confidence interval 1.26-2.79, respectively). Cluster 3 was independently associated with an increased risk of major bleeding (hazard ratio 1.72, 95% confidence interval 1.06-2.78).Conclusion: Cluster analysis identified three statistically driven groups of patients with atrial fibrillation, with distinct phenotype characteristics and associated with different risks for major clinical adverse events. & COPY; 2023 Elsevier Masson SAS. All rights reserved.

Phenotypes and outcomes in non-anticoagulated patients with atrial fibrillation: An unsupervised cluster analysis / A. Bisson, A. M. Fawzy, G.F. Romiti, M. Proietti, D. Angoulvant, W. El-Bouri, G. Y. H. Lip, L. Fauchier. - In: ARCHIVES OF CARDIOVASCULAR DISEASES. - ISSN 1875-2136. - 116:6-7(2023), pp. 342-351. [10.1016/j.acvd.2023.06.001]

Phenotypes and outcomes in non-anticoagulated patients with atrial fibrillation: An unsupervised cluster analysis

M. Proietti;
2023

Abstract

Background: Patients with atrial fibrillation are characterized by great clinical heterogeneity and com-plexity. The usual classifications may not adequately characterize this population. Data-driven cluster analysis reveals different possible patient classifications.Aims: To identify different clusters of patients with atrial fibrillation who share similar clinical pheno-types, and to evaluate the association between identified clusters and clinical outcomes, using cluster analysis.Methods: An agglomerative hierarchical cluster analysis was performed in non-anticoagulated patients from the Loire Valley Atrial Fibrillation cohort. Associations between clusters and a composite out-come comprising stroke/systemic embolism/death and all-cause death, stroke and major bleeding were evaluated using Cox regression analyses.Results: The study included 3434 non-anticoagulated patients with atrial fibrillation (mean age 70.3 & PLUSMN; 17 years; 42.8% female). Three clusters were identified: cluster 1 was composed of younger patients, with a low prevalence of co-morbidities; cluster 2 included old patients with permanent atrial fibrillation, cardiac pathologies and a high burden of cardiovascular co-morbidities; cluster 3 identified old female patients with a high burden of cardiovascular co-morbidities. Compared with cluster 1, clusters 2 and 3 were independently associated with an increased risk of the composite outcome (hazard ratio 2.85, 95% confidence interval 1.32-6.16 and hazard ratio 1.52, 95% confidence interval 1.09-2.11, respectively) and all-cause death (hazard ratio 3.54, 95% confidence interval 1.49-8.43 and hazard ratio 1.88, 95% confidence interval 1.26-2.79, respectively). Cluster 3 was independently associated with an increased risk of major bleeding (hazard ratio 1.72, 95% confidence interval 1.06-2.78).Conclusion: Cluster analysis identified three statistically driven groups of patients with atrial fibrillation, with distinct phenotype characteristics and associated with different risks for major clinical adverse events. & COPY; 2023 Elsevier Masson SAS. All rights reserved.
Atrial fibrillation; Cluster analysis; Machine learning; Outcomes
Settore MED/09 - Medicina Interna
Settore MED/11 - Malattie dell'Apparato Cardiovascolare
2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1039994
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