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Simple risk model predicts incidence of atrial fibrillation in a racially and geographically diverse population: the CHARGE-AF consortium.

TitleSimple risk model predicts incidence of atrial fibrillation in a racially and geographically diverse population: the CHARGE-AF consortium.
Publication TypeJournal Article
Year of Publication2013
AuthorsAlonso A, Krijthe BP, Aspelund T, Stepas KA, Pencina MJ, Moser CB, Sinner MF, Sotoodehnia N, Fontes JD, Janssens CAJW, Kronmal RA, Magnani JW, Witteman JC, Chamberlain AM, Lubitz SA, Schnabel RB, Agarwal SK, McManus DD, Ellinor PT, Larson MG, Burke GL, Launer LJ, Hofman A, Levy D, Gottdiener JS, Kääb S, Couper DJ, Harris TB, Soliman EZ, Stricker BHC, Gudnason V, Heckbert SR
Secondary AuthorsBenjamin EJ
JournalJ Am Heart Assoc
Volume2
Issue2
Paginatione000102
Date Published2013 Mar 18
ISSN2047-9980
KeywordsAfrican Americans, Age Factors, Aged, Aged, 80 and over, Atrial Fibrillation, Cohort Studies, Diabetes Mellitus, European Continental Ancestry Group, Female, Heart Failure, Humans, Hypertension, Iceland, Incidence, Male, Middle Aged, Myocardial Infarction, Netherlands, Proportional Hazards Models, Risk Assessment, Smoking, United States
Abstract

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.

DOI10.1161/JAHA.112.000102
Alternate JournalJ Am Heart Assoc
PubMed ID23537808
PubMed Central IDPMC3647274
Grant ListHHSN268201100012C / HL / NHLBI NIH HHS / United States
HHSN268201100009I / HL / NHLBI NIH HHS / United States
1RC1HL101056 / HL / NHLBI NIH HHS / United States
K24 HL105780 / HL / NHLBI NIH HHS / United States
RC1HL099452 / HL / NHLBI NIH HHS / United States
HHSN268201100010C / HL / NHLBI NIH HHS / United States
HHSN268201100008C / HL / NHLBI NIH HHS / United States
U01 HL080295 / HL / NHLBI NIH HHS / United States
HHSN268201100005G / HL / NHLBI NIH HHS / United States
HHSN268201100008I / HL / NHLBI NIH HHS / United States
R01 HL092577 / HL / NHLBI NIH HHS / United States
HHSN268201100007C / HL / NHLBI NIH HHS / United States
R01HL088456 / HL / NHLBI NIH HHS / United States
AG-15928 / AG / NIA NIH HHS / United States
UL1 TR000161 / TR / NCATS NIH HHS / United States
HHSN268201100011I / HL / NHLBI NIH HHS / United States
HHSN268201100011C / HL / NHLBI NIH HHS / United States
N01-HC 25195 / HC / NHLBI NIH HHS / United States
RC1 HL099452 / HL / NHLBI NIH HHS / United States
AG-20098 / AG / NIA NIH HHS / United States
RC1 HL101056 / HL / NHLBI NIH HHS / United States
R01 HL088456 / HL / NHLBI NIH HHS / United States
R01 HL105756 / HL / NHLBI NIH HHS / United States
RC1HL101056 / HL / NHLBI NIH HHS / United States
AG-027058 / AG / NIA NIH HHS / United States
HHSN268201100006C / HL / NHLBI NIH HHS / United States
R01 HL102214 / HL / NHLBI NIH HHS / United States
HHSN268201100005I / HL / NHLBI NIH HHS / United States
R01 HL080295 / HL / NHLBI NIH HHS / United States
KL2 TR000160 / TR / NCATS NIH HHS / United States
6R01-NS 17950 / NS / NINDS NIH HHS / United States
HHSN268201100009C / HL / NHLBI NIH HHS / United States
N01-AG-12100 / AG / NIA NIH HHS / United States
HHSN268201100005C / HL / NHLBI NIH HHS / United States
HHSN268201100007I / HL / NHLBI NIH HHS / United States
HL080295 / HL / NHLBI NIH HHS / United States
1R01HL102214 / HL / NHLBI NIH HHS / United States
1R01AG028321 / AG / NIA NIH HHS / United States
AG-023629 / AG / NIA NIH HHS / United States
1R01HL092577 / HL / NHLBI NIH HHS / United States
R01 AG028321 / AG / NIA NIH HHS / United States
1R21HL106092 / HL / NHLBI NIH HHS / United States
R21 HL106092 / HL / NHLBI NIH HHS / United States