DOI 10.1016/j.hrthm.2026.10.011
Latent class analysis-derived patterns of comorbidities in patients with atrial fibrillation, adherence to integrated care and impact on long-term outcomes: an analysis from a prospective cohort.
Аннотация
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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