Clinical, biomarker, and genetic predictors of specific types of atrial fibrillation in a community-based cohort: Data of the PREVEND study

Aims Atrial fibrillation (AF) may present variously in time, and AF may progress from self-terminating to non-self-terminating AF, and is associated with impaired prognosis. However, predictors of AF types are largely unexplored. We investigate the clinical, biomarker, and genetic predictors of development of specific types of AF in a community-based cohort. Methods We included 8042 individuals (319 with incident AF) of the PREVEND study. Types of AF were compared, and multivariate multinomial regression analysis determined associations with specific types of AF. Results Mean age was 48.5 +/- 12.4 years and 50% were men. The types of incident AF were ascertained based on electrocardiograms; 103(32%) were classified as AF without 2-year recurrence, 158(50%) as self-terminating AF, and 58(18%) as non-self-terminating AF. With multivariate multinomial logistic regression analysis, advancing age (P <0.001 for all three types) was associated with all AF types, male sex was associated with AF without 2-year recurrence and self-terminating AF (P = 0.031 and P = 0.008, respectively). Increasing body mass index and MR-proANP were associated with both self-terminating (P = 0.009 and P, 0.001) and non-self-terminating AF (P = 0.003 and P