Abstract
Heart rate fragmentation (HRF), a marker of abnormal sinoatrial dynamics, was shown to be associated with incident cardiovascular events in the Multi-Ethnic Study of Atherosclerosis (MESA). Here, we test the hypothesis that HRF is also associated with incident atrial fibrillation (AF) in the MESA cohort of participants who underwent in-home polysomnography (PSG) and in two high-risk subgroups: those ≥70 yr taking antihypertensive medication and those with serum concentrations of NH(2)-terminal prohormone B-type natriuretic peptide (NT-proBNP) >125 pg/ml (top quartile). Heart rate time series (n = 1,858) derived from the ECG channel of the PSG were analyzed using newly developed HRF metrics, traditional heart rate variability (HRV) indices and two widely used nonlinear measures. Eighty-three participants developed AF over a mean follow-up period of 3.83 ± 0.87 yr. A one-standard deviation increase in HRF was associated with a 31% (95% CI: 3-66%) increase in risk of incident AF, in Cox models adjusted for age, height, NT-proBNP, and frequent premature supraventricular complexes. Furthermore, HRF added value to the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF models. Traditional HRV and nonlinear indices were not significantly associated with incident AF. In the two high-risk subgroups defined above, HRF was also significantly associated with incident AF in unadjusted and adjusted models. These findings support the translational utility of HRF metrics for short-term (∼4-yr) prediction of AF. In addition, they support broadening the concept of atrial remodeling to include electrodynamical remodeling, a term used to refer to pathophysiological alterations in sinus interbeat interval dynamics.NEW & NOTEWORTHY This study is the first demonstration that heart rate fragmentation (HRF), a marker of anomalous sinoatrial dynamics, is an independent predictor of atrial fibrillation (AF). Traditional measures of heart rate variability and two widely used nonlinear measures were not associated with incident AF in the Multi-Ethnic Study of Atherosclerosis. Fragmentation measures added value to the strongest contemporary predictors of AF, including ECG-derived parameters, coronary calcification score, serum concentrations of NH(2)-terminal prohormone B-type natriuretic peptide, and supraventricular ectopy. The computational algorithms for quantification of HRF could be readily incorporated into wearable ECG monitoring devices.