Key result
High-comorbidity AF phenotype is linked to a ~143% increase in major composite cardiovascular outcomes.
Why the study?
Conventional classification based on disease subtype or arrhythmia patterns may not adequately characterize the clinical heterogeneity of atrial fibrillation patients.
Observational (n=3,980)
Yes
Hazard Ratio: 2.43 (95% CI 1.7–3.46)
Absolute Event Rate: 8.3% vs 3.1%
p-value: p=<0.001
Comorbidity clustering may refine AF risk stratification; hypothesis-generating and requires prospective validation before clinical use.
BACKGROUND AND PURPOSE: Given the great clinical heterogeneity of atrial fibrillation (AF) patients, conventional classification only based on disease subtype or arrhythmia patterns may not adequately characterize this population. We aimed to identify different groups of AF patients who shared common clinical phenotypes using cluster analysis and evaluate the association between identified clusters and clinical outcomes. METHODS: We performed a hierarchical cluster analysis in AF patients from AMADEUS and BOREALIS trials. The primary outcome was a composite of stroke/thromboembolism (TE), cardiovascular (CV) death, myocardial infarction, and/or all-cause death. Individual components of the primary outcome and major bleeding were also assessed. RESULTS: We included 3980 AF patients treated with the Vitamin-K Antagonist from the AMADEUS and BOREALIS studies. The analysis identified four clusters in which patients varied significantly among clinical characteristics. Cluster 1 was characterized by patients with low rates of CV risk factors and comorbidities; Cluster 2 was characterized by patients with a high burden of CV risk factors; Cluster 3 consisted of patients with a high burden of CV comorbidities; Cluster 4 was characterized by the highest rates of non-CV comorbidities. After a mean follow-up of 365 (standard deviation 187) days, Cluster 4 had the highest cumulative risk of outcomes. Compared with Cluster 1, Cluster 4 was independently associated with an increased risk for the composite outcome (hazard ratio (HR) 2.43, 95% confidence interval (CI) 1.70-3.46), all-cause death (HR 2.35, 95% CI 1.58-3.49) and major bleeding (HR 2.18, 95% CI 1.19-3.96). CONCLUSIONS: Cluster analysis identified four different clinically relevant phenotypes of AF patients that had unique clinical characteristics and different outcomes. Cluster analysis highlights the high degree of heterogeneity in patients with AF, suggesting the need for a phenotype-driven approach to comorbidities, which could provide a more holistic approach to management aimed to improve patients' outcomes.
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Vitolo et al. (2021) conducted an observational in Atrial Fibrillation (n=3,980). Cluster 4 phenotype (high non-cardiovascular comorbidities) vs. Cluster 1 phenotype (low cardiovascular risk factors) was evaluated on Composite of stroke/thromboembolism, cardiovascular death, myocardial infarction, and/or all-cause death (HR 2.43, 95% CI 1.70-3.46, p=<0.001). Atrial fibrillation patients in Cluster 4, characterized by high non-cardiovascular comorbidities, had a significantly increased risk of the primary composite outcome compared to Cluster 1 (HR 2.43).
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