Model for assessing cardiovascular risk in a Korean population.

From the Department of Cardiology, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Daejeon, Korea (G.-M.P., S.H.H.); Departments of Biostatistics (S.H., J.B.L., M.S.L.), Preventive Medicine (M.-W.J.), Cardiology, (J.-M.A., S.-W.L., Y.-H.K., S.-W.P., S,-J.P.), Endocrinology and Metabolism (B.-J.K., J.-M.K.), and Health Screening and Promotion Center (H.-K.K., J.C.), Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea; Department of Nursing, College of Medicine, Dankook University, Cheonan, Korea (S.H.K.); Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea (H.C.K.); and Research and Development Center, Health Insurance Review and Assessment Service, Seoul, Korea (H.C.K.). From the Department of Cardiology, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Daejeon, Korea (G.-M.P., S.H.H.); Departments of Biostatistics (S.H., J.B.L., M.S.L.), Preventive Medicine (M.-W.J.), Cardiology, (J.-M.A., S.-W.L., Y.-H.K., S.-W.P., S,-J.P.), Endocrinology and Metabolism (B.-J.K., J.-M.K.), and Health Screening and Promotion Center (H.-K.K., J.C.), Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea; Department of Nursing, College of Medicine, Dankook University, Cheonan, Korea (S.H.K.); Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea (H.C.K.); and Research and Development Center, Health Insurance Review and Assessment Service, Seoul, Korea (H.C.K.). mdyhkim@amc.seoul.kr drchoe@hotmail.com.

Circulation. Cardiovascular quality and outcomes. 2014;(6):944-51

Abstract

BACKGROUND A model for predicting cardiovascular disease in Asian populations is limited. METHODS AND RESULTS In total, 57 393 consecutive asymptomatic Korean individuals aged 30 to 80 years without a prior history of cardiovascular disease who underwent a general health examination were enrolled. Subjects were randomly classified into the train (n=45 914) and validation (n=11 479) cohorts. Thirty-one possible risk factors were assessed. The cardiovascular event was a composite of cardiovascular death, myocardial infarction, and stroke. In the train cohort, the C-index (95% confidence interval) and Akaike Information Criterion were used to develop the best-fitting prediction model. In the validation cohort, the predicted versus the observed cardiovascular event rates were compared by the C-index and Nam and D'Agostino χ(2) statistics. During a median follow-up period of 3.1 (interquartile range, 1.9-4.3) years, 458 subjects had 474 cardiovascular events. In the train cohort, the best-fitting model consisted of age, diabetes mellitus, hypertension, current smoking, family history of coronary heart disease, white blood cell, creatinine, glycohemoglobin, atrial fibrillation, blood pressure, and cholesterol (C-index =0.757 [0.726-0.788] and Akaike Information Criterion =7207). When this model was tested in the validation cohort, it performed well in terms of discrimination and calibration abilities (C-index=0.760 [0.693-0.828] and Nam and D'Agostino χ(2) statistic =0.001 for 3 years; C-index=0.782 [0.719-0.846] and Nam and D'Agostino χ(2) statistic=1.037 for 5 years). CONCLUSIONS A risk model based on traditional clinical and biomarkers has a feasible model performance in predicting cardiovascular events in an asymptomatic Korean population.

Methodological quality

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