This review highlights recently described novel risk factors for atrial fibrillation, emphasizing the need to incorporate them into risk prediction models to explain residual risk.
This review emphasizes the importance of identifying and incorporating novel risk factors, including genetic and familial components, to improve atrial fibrillation risk prediction and prevention strategies.
A trial fibrillation (AF) is the most common cardiac arrhythmia; the lifetime risk is 1 in 4 for persons over the age of 40 years in the United States. 1 AF is associated with an increased risk of death, dementia, heart failure, and stroke. 2-5 AF leads to high healthcare system utilization rates. 6 Based on current US age-and sex-specific prevalence data, the national incremental AF cost in 2010 is estimated to range from 6. 0 to 26. 0 billion. 7 Risk factors for AF are diverse 8 and include advancing age, male sex, diabetes mellitus, hypertension, valvular disease, myocardial infarction, heart failure, obesity, elevated inflammatory marker concentrations, and PRinterval prolongation, as recently reviewed elsewhere. 9 Risk prediction models are important to define individual risk for AF, to identify novel risk factors for AF, to identify and assess potential targets of therapy, and to enhance the cost-effective implementation of therapies for both primary and secondary prevention of AF. 10 A recently published risk score for the development of AF based on the established cardiovascular risk factors accounted for only part of the AF risk (C-statistic 0. 76). 11 Thus, although many risk factors for AF have been described, a substantial proportion of AF risk still remains unexplained. In the past years, multiple novel AF risk factors have been studied. In the present review, we aim to describe recently described risk factors and will underscore that substantial efforts are needed to incorporate novel markers of AF into risk prediction models. Efforts to optimize risk prediction models and prevention algorithms are useful for risk communication, patient motivation, and clinical decision making. 10 Familial Aggregation, Ethnic Differences, and Genetics of AF Familial AggregationIn recent years, increasing data have been reported supporting the notion that AF in the general population is heritable. Diverse population-based studies have demonstrated that familial clustering of AF is common. In 1 such study, Framingham Heart Study investigators reported that a parental history of AF doubled the risk of AF in offspring, 12 and that a family history of AF improved risk prediction of AF. 13 An analysis of 1137 same-sex twin pairs (356 monozygotic and 781 dizygotic pairs) in which one or both members were diagnosed with AF from the Danish Twin Registry found that concordance rates were twice as high for monozygotic pairs as for dizygotic pairs (22. 0%versus 11. 6%, PϽ0. 0001).
Rienstra et al. (2012) conducted a review in Atrial Fibrillation. Novel risk factors was evaluated. This review highlights recently described novel risk factors for atrial fibrillation, emphasizing the need to incorporate them into risk prediction models to explain residual risk.