Clinical phenotype classification to predict risk and optimize the management of patients with atrial fibrillation using the Atrial Fibrillation Better Care (ABC) pathway: a report from the COOL-AF registry

Phenotypic classification is a method of grouping patients with similar phenotypes. We aimed to use phenotype classification based on a clustering process for risk stratification of patients with non-valvular atrial fibrillation (AF) and second, to assess the benefit of the Atrial Fibrillation Better Care (ABC) pathway. Patients with AF were prospectively enrolled from 27 hospitals in Thailand from 2014 to 2017, and followed up every 6 months for 3 years. Cluster analysis was performed from 46 variables using the hierarchical clustering using the Ward minimum variance method. Outcomes were a composite of all-cause death, ischemic stroke/systemic embolism, acute myocardial infarction and heart failure. A total of 3405 patients were enrolled (mean age 67.8 ± 11.3 years, 58.2% male). During the mean follow-up of 31.8 ± 8.7 months. Three clusters were identified: Cluster 1 had the highest risk followed by Cluster 3 and Cluster 2 with a hazard ratio (HR) and 95% confidence interval (CI) of composite outcomes of 2.78 (2.25, 3.43), P