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

Journal of the American Heart Association - Tập 2 Số 2 - 2013
Álvaro Alonso1, Bouwe P. Krijthe2, Thor Aspelund3,4, Katherine A. Stepas5, Michael Pencina5, Carlee Moser5, Moritz F. Sinner6,7,8, Nona Sotoodehnia9,10, João D. Fontes6, A. Cecile J.W. Janssens2,11, Richard A. Kronmal12, Jared W. Magnani6,13, Jacqueline C.M. Witteman2,11, Alanna M. Chamberlain14, Steven A. Lubitz7,15, Renate B. Schnabel16, Sunil Agarwal17, David D. McManus6,18,19, Patrick T. Ellinor7,15, Martin G. Larson6, Gregory L. Burke20, Lenore J. Launer21, Albert Hofman2,11, Daniel Levy6,22, John S. Gottdiener23, Stefan Kääb8,24, David Couper25, Tamara B. Harris21, Elsayed Z. Soliman26, Bruno H. Stricker2,27,28,29,11, Vilmundur Guðnason3,4, Susan R. Heckbert30, Emelia J. Benjamin6,13,31
11Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN (A.A.)
22Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands (B.P.K., C.W.J., J.C.W., A.H., B.C.S.)
3Icelandic Heart Association Research Institute, Kopavogur, Iceland
4The University of Iceland, Reykjavik, Iceland
57Department of Biostatistics, Boston University School of Public Health, Boston, MA (K.A.S., M.J.P., C.B.M.)
614National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA (M.F.S., J.F., J.W.M., D.D.M.M., M.G.L., D.L., E.J.B.)
718Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA (M.F.S., S.A.L., P.T.E.)
826Department of Medicine I, University Hospital Munich, Campus Grosshadern, Ludwig-Maximilians University, Munich, Germany (M.F.S., S.)
910Division of Cardiology, Department of Medicine, University of Washington, Seattle (N.S.)
10Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
11Netherlands Consortium for Healthy Aging (NCHA), The Netherlands
1212Department of Biostatistics, University of Washington, Seattle, WA (R.A.K.)
13Department of Medicine, Boston University School of Medicine, Boston, MA
1417Department of Health Sciences Research, Mayo Clinic, Rochester, MN (A.M.C.)
15Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA
1619Department of General and Interventional Cardiology, University Heart Center Hamburg-Eppendorf, Germany (R.B.S.)
1720Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC (S.K.A.)
1830Department of Medicine and Quantitative Health Sciences, University of Massachusetts, Worcester, MA (D.D.M.M.)
1931Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA (D.D.M.M.)
2022Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC (G.L.B.)
2123Laboratory of Epidemiology, Demography, and Biometry, National Institute of Aging, National Institutes of Health, Bethesda, MD (L.J.L., T.B.H.)
2224Center for Population Studies, NHLBI, Bethesda, MD (D.L.)
2325Division of Cardiology, University of Maryland Medical Center, Baltimore, MD (J.S.G.)
24Munich Heart Alliance, Munich, Germany
2521Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC (D.C.)
2627Epidemiological Cardiology Research Center (EPICARE), Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC (E.Z.S.)
27Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
28Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands
29Inspectorate for Health Care, The Hague, The Netherlands
3013Department of Epidemiology, University of Washington, Seattle, WA (S.R.H.)
31National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA

Tóm tắt

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 U nited S tates (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% A frican A mericans, 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 U nited S tates and E urope.

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Journal of the American Heart Association

Tập 2 Số 2

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