Predicting the Development of Myocardial Infarction in Middle-Aged Adults with Type 2 Diabetes: A Risk Model Generated from a Nationwide Population-Based Cohort Study in Korea

Abstract

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 with type 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 2012 were recruited from the Korean National Health Insurance database. Seventy percent of the subjects (n=891,095) were sampled to develop 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 risk nomogram 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, body mass index, chronic kidney disease, duration of diabetes, number of anti-diabetic medications, fasting blood glucose, systolic blood pressure, total cholesterol, and atrial fibrillation were significant risk factors for the development of MI and were incorporated into the 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 2 diabetes. This model may provide useful information for identifying high-risk patients and improving quality of care.

Nonalcoholic fatty liver disease and the risk of insulin-requiring gestational diabetes

“…The NHIS database is available for population-based cohort studies. Information on demographics, national health screening data, diagnosis statements defined by the International Classification of Disease 10 th revision (ICD-10) codes, medical treatments, and drug prescriptions is routinely collected and undergoes quality control before being released for research purposes [ 12 – 14 ]. Enrollees in the NHIS are recommended to undergo a standardized medical examination at least every 2 years.…”

“…We classified the study population into three groups according to the FLI as follows [ 13 , 14 ]: low-risk group, defined as FLI < 30; intermediate-risk group, defined as 30 ≤ FLI < 60; and high-risk group, defined as FLI ≥ 60. FLI scores < 30 ruled out hepatic steatosis, while FLI ≥ 60 indicated NAFLD [ 15 , 16 ].…”

Current Trends of Big Data Research Using the Korean National Health Information Database

“…Myocardial infarction (MI) was defined according to ICD-10 codes I21 or I22 recorded during hospitalization [ 23 , 24 ]. Stroke was defined using principal diagnosis codes from I60 to I64 with the enforcement of brain computerized tomography or magnetic resonance imaging at the emergency center or outpatient clinic, or during hospitalization [ 25 ].…”

“…Stroke was defined using principal diagnosis codes from I60 to I64 with the enforcement of brain computerized tomography or magnetic resonance imaging at the emergency center or outpatient clinic, or during hospitalization [ 25 ]. Ischemic stroke was defined as a recording of ICD-10 codes I63 or I64 during hospitalization with a claim for brain magnetic resonance imaging or brain computerized tomography ( Table 4 ) [ 23 , 24 ]. This definition has been widely adopted in previous studies using claims databases [ 26 , 27 ].…”

Assessing the Validity of the Criteria for the Extreme Risk Category of Atherosclerotic Cardiovascular Disease: A Nationwide Population-Based Study

“…Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of death throughout the world despite recent improvements in overall rates of lipid disorders. 1 2 3 4 5 Increasing life expectancy and various metabolic diseases might have contributed to the increase in the number of patients with ASCVD. 6 7 8 Especially, patients with established ASCVD are at high risk of ASCVD reoccurring in the same artery or different arteries.…”