Why the study?
Atrial fibrillation commonly coexists with multiple cardiovascular and non-cardiovascular comorbidities that may cluster into distinct clinical phenotypes with different outcome implications.
Cohort (n=1,233)
Hazard Ratio: 2.81 (95% CI 1.83–4.34)
Latent class analysis identifies distinct comorbidity phenotypes in AF patients with varying adverse event risks, while adherence to integrated care remains associated with lower risk across all complexity levels.
AF phenotypes stratify adverse outcome risk; supports integrated care associations across groups but leaves practice change to trials.
BACKGROUND: Atrial fibrillation (AF) commonly coexists with multiple cardiovascular (CV) and non-CV comorbidities, which may cluster in distinct clinical phenotypes with different outcome implications. OBJECTIVE: We aim to identify comorbidity-based phenotypes in AF using latent class analysis (LCA), characterize their clinical course and assess the association of integrated care adherence with outcomes across phenotypes. METHODS: A LCA based on 11 conditions (CV and non-CV) was performed. The primary outcome was a composite of all-cause death, thromboembolic (TE) events, and acute coronary syndrome (ACS). Secondary outcomes were all-cause death and ACS/TE events. RESULTS: We included 1233 AF patients (median age 75 [66-82] years, females 37.5%). Four clinical LCA-derived phenotypes were identified: "Low comorbidity" (31.5%); "Cardio-metabolic" (33.9%); "Elderly comorbid" (22.9%); and "Atherosclerotic-HF" (11.8%). During a median follow-up of 542 days, 234 patients (22.7%) experienced the primary outcome. Compared to "Low comorbidity", "Cardio-metabolic" (aHR 1.64, 95% CI 1.13-2.39), "Elderly comorbid" (aHR 1.62, 95% CI 1.09-2.42) and "Atherosclerotic-HF" (aHR 2.81, 95%CI 1.83-4.34) phenotypes were independently associated with a higher risk of the primary outcome. Adherence to integrated care varied across phenotypes and was associated with a lower risk of adverse events, with no evidence of significant heterogeneity across phenotypes (p int=0.157). CONCLUSIONS: Latent class analysis identified distinct AF clinical phenotypes characterized by specific patterns of comorbidities and associated with different risk of adverse outcomes. The absence of significant heterogeneity in the association between integrated care and outcomes across phenotypes supports its potential value across different levels of clinical complexity in AF patients.
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Mantovani et al. (2026) conducted a cohort in Atrial fibrillation (AF) (n=1,233). Atherosclerotic-HF phenotype vs. Low comorbidity phenotype was evaluated on composite of all-cause death, thromboembolic (TE) events, and acute coronary syndrome (ACS) (aHR 2.81, 95% CI 1.83-4.34).
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