Simple Risk Model Predicts Incidence of Atrial Fibrillation in a Racially and Geographically Diverse Population: the CHARGE‐AF Consortium

By Á. Alonso, B. Krijthe, T. Aspelund, Katherine A. Stepas, Michael J. Pencina, C. Moser, Moritz F. Sinner, N. Sotoodehnia, J. Fontes, A. Janssens and 23 more. Journal of the American Heart Association : Cardiovascular and Cerebrovascular Disease, 2013

792 citations recorded by the source corpus.

Background Tools for the prediction of atrial fibrillation (AF) may identify high‐risk individuals more likely to benefit from preventive interventions and serve as a benchmark to test novel putative risk factors. Methods and Results Individual‐level data from 3 large cohorts in the United States (Atherosclerosis Risk in Communities [ARIC] study, the Cardiovascular Health Study [CHS], and the Framingham Heart Study [FHS]), including 18 556 men and women aged 46 to 94 years (19% African Americans, 81% whites) were pooled to derive predictive models for AF using clinical variables. Validation of the derived models was performed in 7672 participants from the Age, Gene and Environment—Reykjavik study (AGES) and the Rotterdam Study (RS). The analysis included 1186 incident AF cases in the derivation cohorts and 585 in the validation cohorts. A simple 5‐year predictive model including the variables age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes, and history of myocardial infarction and heart failure had good discrimination (C‐statistic, 0.765; 95% CI, 0.748 to 0.781). Addition of variables from the electrocardiogram did not improve the overall model discrimination (C‐statistic, 0.767; 95% CI, 0.750 to 0.783; categorical net reclassification improvement, −0.0032; 95% CI, −0.0178 to 0.0113). In the validation cohorts, discrimination was acceptable (AGES C‐statistic, 0.664; 95% CI, 0.632 to 0.697 and RS C‐statistic, 0.705; 95% CI, 0.664 to 0.747) and calibration was adequate. Conclusion A risk model including variables readily available in primary care settings adequately predicted AF in diverse populations from the United States and Europe.

Subfields: Cardiology and Cardiovascular Medicine, Epidemiology

View Paper: https://www.semanticscholar.org/paper/919d119b25eb1534206c3b687101eac2a62f3849

Citations in the corpus

• Atrial Fibrillation Begets Heart Failure and Vice Versa: Temporal Associations and Differences in Preserved vs. Reduced Ejection Fraction (2016, neutral): “Analyses were first adjusted for age and sex and then further adjusted for established risk factors of AF (height, weight, systolic and diastolic blood pressures, current smoking, use of antihypertensive medication, diabetes mellitus, and history of myocardial infarction).(15) In secondary analyses,”