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Wiley Open Access, Journal of the American Heart Association, 2(5), 2016

DOI: 10.1161/jaha.115.003077

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Prediction of Atrial Fibrillation in a Racially Diverse Cohort: The Multi‐Ethnic Study of Atherosclerosis (MESA)

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Background Existing equations for prediction of atrial fibrillation ( AF ) have been developed and validated in white and African‐American populations. Whether these models adequately predict AF in more racially and ethnically diverse populations is unknown. Methods and Results We studied 6663 men and women 45 to 84 years of age without AF at baseline (2000–2002) enrolled in the Multi‐Ethnic Study of Atherosclerosis ( MESA ). Of these, 38% were non‐Hispanic whites, 28% non‐Hispanic African Americans, 22% Hispanics, and 12% Chinese Americans. AF during follow‐up was ascertained from hospitalization discharge codes through 2012. Information collected at baseline was used to calculate predicted 5‐year risk of AF using the previously published simple CHARGE ‐ AF model, which only includes clinical variables, and a biomarker‐enriched CHARGE ‐ AF model, which also considers levels of circulating N‐terminal of the prohormone B‐type natriuretic peptide and C‐reactive protein. For comparison purposes, we also assessed performance of the 10‐year Framingham AF model. During a mean follow‐up of 10.2 years, 351 cases of AF were identified. The C‐statistic of the CHARGE ‐ AF models were 0.779 (95% CI , 0.744–0.814) for the simple model and 0.825 (95% CI , 0.791–0.860) for the biomarker‐enriched model. Calibration was adequate in the biomarker‐enriched model (χ 2 =7.9; P =0.55), but suboptimal in the simple model (χ 2 =25.6; P =0.002). In contrast, the 10‐year Framingham score had a C‐statistic (95% CI ) of 0.746 (0.720–0.771) and showed poor calibration (χ 2 =57.4; P <0.0001). Conclusion The CHARGE ‐ AF risk models adequately predicted 5‐year AF risk in a large multiethnic cohort. These models could be useful to select high‐risk individuals for AF screening programs or for primary prevention trials in diverse populations.