Journal
JOURNAL OF THE AMERICAN HEART ASSOCIATION
Volume 2, Issue 2, Pages -Publisher
WILEY
DOI: 10.1161/JAHA.112.000102
Keywords
atrial fibrillation; epidemiology; risk factors
Categories
Funding
- NIH [N01-AG-12100]
- NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association)
- Althingi (the Icelandic Parliament)
- National Heart, Lung, and Blood Institute [HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, HHSN268201100012C]
- NHLBI [RC1HL099452, RC1HL101056, N01-HC-85239, N01-HC-85079, N01-HC-85086, N01-HC-35129, N01 HC-15103, N01 HC-55222, N01-HC-75150, N01-HC-45133, HL080295, R01HL088456]
- American Heart Association [09SDG2280087, 09FTF2190028]
- NIA [AG-023629, AG-15928, AG-20098, AG-027058]
- German Heart Foundation
- Erasmus Medical Center
- Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw)
- Research Institute for Diseases in the Elderly (RIDE)
- Ministry of Education, Culture and Science
- Ministry for Health, Welfare and Sports
- European Commission (DG XII)
- Municipality of Rotterdam
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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.
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