A Cluster Analysis of the Japanese Multicenter Outpatient Registry of Patients With Atrial Fibrillation.

Recently, cluster analysis was used to identify unique clinically relevant phenotypes of atrial fibrillation (AF) in a cohort from the United States (US) and classified clusters according to the presence of comorbid behavioral disorders, those with conduction disorders, or atherosclerotic comorbidities. Whether these phenotypes are consistent in AF cohorts outside the US remains unknown. Thus, we sought to conduct a cluster analysis in a cohort of Japanese AF patients. We conducted a cluster analysis of phenotypic data (46 variables) in an AF patient cohort recruited from 11 Japanese sites participating in the KiCS-AF Registry. Overall, 2,458 AF patients (median [IQR] age, 68.0 [60.0 to 76.0]; 30.3% female; median [IQR] CHADS-Vasc, 2 [1, 3]) were analyzed. Similar to the US cohort, atherosclerotic comorbidities were identified as distinguishing factors to characterize clusters. Distribution of AF type and left atrial (LA) size substantially varied and was the key feature for cluster formation. CHADS-Vasc score also contributed to cluster formation, although behavioral disorders and/or conduction disorders did not readily characterize clusters. Subsequently, the cohort was classified into 3 clusters: (1) Younger paroxysmal AF (n = 1,190); (2) Persistent/permanent AF with LA enlargement (n = 1,143); and (3) Atherosclerotic comorbid AF in elderly patients (N = 125). In conclusion, conventional classifications, such as atherosclerotic risk factors and CHADS-Vasc score contributed to cluster formation in mutually, whereas in nonatherosclerotic clusters, AF type or LA size rather than the presence or absence of behavior risk factors or sinus node dysfunction (tachy-brady syndrome) seemed to contribute to cluster formation in the Japanese cohort.