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자료유형
학술저널
저자정보
이승환 (가톨릭대학교) 한경도 (숭실대학교) 김헌성 (가톨릭대학교) 조재형 (가톨릭대학교) 윤건호 (가톨릭대학교) 김미경 (가톨릭대학교)
저널정보
대한내분비학회 Endocrinology and Metabolism Endocrinology and Metabolism Vol.35 No.3
발행연도
2020.1
수록면
636 - 646 (11page)

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Background: Most of the widely used prediction models for cardiovascular disease are known to overestimate the risk of this disease in Asians. We aimed to generate a risk model for predicting myocardial infarction (MI) in middle-aged Korean subjects withtype 2 diabetes. Methods: A total of 1,272,992 subjects with type 2 diabetes aged 40 to 64 who received health examinations from 2009 to 2012were recruited from the Korean National Health Insurance database. Seventy percent of the subjects (n=891,095) were sampled todevelop the risk prediction model, and the remaining 30% (n=381,897) were used for internal validation. A Cox proportional hazards regression model and Cox coefficients were used to derive a risk scoring system. Twelve risk variables were selected, and a risknomogram was created to estimate the 5-year risk of MI. Results: During 7.1 years of follow-up, 24,809 cases of MI (1.9%) were observed. Age, sex, smoking status, regular exercise, bodymass index, chronic kidney disease, duration of diabetes, number of anti-diabetic medications, fasting blood glucose, systolic bloodpressure, total cholesterol, and atrial fibrillation were significant risk factors for the development of MI and were incorporated intothe risk model. The concordance index for MI prediction was 0.682 (95% confidence interval [CI], 0.678 to 0.686) in the development cohort and 0.669 (95% CI, 0.663 to 0.675) in the validation cohort. Conclusion: A novel risk engine was generated for predicting the development of MI among middle-aged Korean adults with type 2diabetes. This model may provide useful information for identifying high-risk patients and improving quality of care.

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