Background: Black individuals have a lower incidence of atrial fibrillation (AF) than White individuals despite a higher burden of many traditional cardiovascular risk factors. Differences in left atrial (LA) structure and function by race could partly explain the observed pattern of AF risk. Methods: This analysis included 4,576 (978 Black and 3,598 White) participants from the Atherosclerosis Risk in Communities (ARIC) study, followed between 2011 and 2021. The association of selected echocardiographic measures of LA structure and function with AF incidence was evaluated with race-specific Cox proportional hazards models with adjustment for sociodemographic and clinical covariates. Additional analyses assessed whether LA measures attenuated the association between race and incident AF. Results: The analysis included 778 AF cases (113 in Black and 665 in White participants, mean age 75 years). Larger LA size and worse LA function were associated with higher AF risk in both Black and White individuals, with most associations of similar magnitude in both groups, except for a slightly stronger association of LA reservoir strain in Black than White participants (Black: hazard ratio (HR) 0.89, 95% CI 0.86-0.92 per 1% increase; White: HR 0.94, 95% CI 0.92-0.95, p for interaction = 0.01). In the overall sample, White participants showed higher AF risk compared to Black participants (HR 1.59, 95% CI 1.24-2.03). Adjustment for most individual LA measures did not attenuate the association between race and AF risk. Conclusion: Larger LA size and worse LA function were associated with incident AF in both Black and White ARIC participants. However, these measures did not explain the lower AF incidence observed among Black participants. LA remodeling appears to be an important predictor of AF risk, but it is not the primary explanation for the Black-White AF paradox.
Yuchen Li, E. Soliman, Srishti Shrestha et al.· medRxiv· 0 citations
Background: The Cohorts for Heart and Aging Research in Genomic Epidemiology - Atrial Fibrillation (CHARGE-AF) score is a validated tool for estimating 5-year risk of atrial fibrillation (AF). We aimed to evaluate the utility of repeated CHARGE-AF scores for improving AF risk prediction. Methods: We analyzed participants from the Atherosclerosis Risk in Communities (ARIC) study with complete data from the first four clinic visits (9-year period) and with no prevalent AF by visit 4 (analysis baseline; N = 10,188). CHARGE-AF scores were calculated for each visit using clinical and demographic variables. Incident AF was determined from electrocardiograms, hospital discharge codes, and death certificates over a median follow-up of 19.5 years. Four Cox regression models were assessed: model 1 included only the visit 4 CHARGE-AF score, and subsequent models added prior CHARGE-AF scores in stepwise fashion. C-statistics were used to evaluate model discrimination, and comparison of observed versus predicted risk was employed to evaluate calibration. Secondary analysis restricted follow-up to five years. Results: During follow-up, 2,519 participants developed AF (14.2 cases per 1,000 person-years). The mean age of participants at start of follow-up was 62.8 (standard deviation 5.6) years. In the primary analysis, each 1% increase in the visit 4 CHARGE-AF score was associated with incident AF (Model 1 HR = 1.14, 95% CI 1.13-1.15). Addition of scores from prior visits did not significantly improve model discrimination (C-statistic: 0.702-0.703 for all models). Sex modified the association between a 1% increase in CHARGE-AF score and incident AF, with a stronger association among females (Model 1 HR = 1.21, 95% CI: 1.19-1.22) than among males (HR for model 1 = 1.12, 95% CI: 1.11-1.13). Similar patterns were observed in the secondary (5-year restricted) analysis. Conclusions: A single measurement of the CHARGE-AF score provided strong predictive value for incident AF, with the addition of prior scores offering limited incremental benefit. These findings suggest that, in clinical settings with longitudinal data, the most recent assessment is sufficient for AF risk prediction.
Eduardo Gonzalez Villarreal, F. Norby, L. Y. Chen et al.· medRxiv· 0 citations
