ArticleDiabetes & metabolism journal2018
Development and Validation of the Korean Diabetes Risk Score: A 10-Year National Cohort Study.
Article in Diabetes & metabolism journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04369833 (Development of Continuous Glucose Monitoring System Cohort for Personalized Diabetes Prevention and Management Platform Based on Artificial Intelligence Model Using Mathematical Analysis), which is not on this map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Development of Continuous Glucose Monitoring System Cohort for Personalized Diabetes Prevention and Management Platform Based on Artificial Intelligence Model Using Mathematical Analysis
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk prediction models for incident type 2 diabetes in Chinese people with intermediate hyperglycemia: a systematic literature review and external validation study.Cardiovascular diabetology · 2022Pooled it
- Development and temporal external validation of a high-specificity XGBoost rule-in model for diabetes in middle-aged and older Korean adults.Diabetology & metabolic syndrome · 2026Article
- Association between elevated glycosylated hemoglobin levels and hypertension among US adults: NHANES 2011-2018.BMC cardiovascular disorders · 2025Article
- Association between the ratio of aspartate aminotransferase to alanine aminotransferase and risk of diabetes and the mediating effect of BMI: a comparative analysis in Chinese and Japanese populations.Frontiers in endocrinology · 2025Article
- Approaches to predict future type 2 diabetes mellitus and chronic kidney disease: A scoping review.PloS one · 2025Article
- Comparisons of the prediction models for undiagnosed diabetes between machine learning versus traditional statistical methods.Scientific reports · 2023Article
- Low aspartate aminotransferase/alanine aminotransferase (DeRitis) ratio assists in predicting diabetes in Chinese population.Frontiers in public health · 2022Article
- Gamma-glutamyl transferase to high-density lipoprotein cholesterol ratio: A valuable predictor of type 2 diabetes mellitus incidence.Frontiers in endocrinology · 2022Article
- New risk score model for identifying individuals at risk for diabetes in southwest China.Preventive medicine reports · 2021Article
- Development and validation of a new diabetes index for the risk classification of present and new-onset diabetes: multicohort study.Scientific reports · 2021Article
- Development and Validation of a Deep Learning Based Diabetes Prediction System Using a Nationwide Population-Based Cohort.Diabetes & metabolism journal · 2021Article
- Prediction Models for Type 2 Diabetes Risk in the General Population: A Systematic Review of Observational Studies.International journal of endocrinology and metabolism · 2021Article
- Development of a predictive risk model for all-cause mortality in patients with diabetes in Hong Kong.BMJ open diabetes research & care · 2021Article
- Development of a clinical risk score for incident diabetes: A 10-year prospective cohort study.Journal of diabetes investigation · 2021Article
- Article
- Impact of obesity, fasting plasma glucose level, blood pressure, and renal function on the severity of COVID-19: A matter of sexual dimorphism?Diabetes research and clinical practice · 2020Article
- Smoking as a Target for Prevention of Diabetes.Diabetes & metabolism journal · 2020Article
- Multiple Biomarkers Improved Prediction for the Risk of Type 2 Diabetes Mellitus in Singapore Chinese Men and Women.Diabetes & metabolism journal · 2020Article
- Biomarker Score in Risk Prediction: Beyond Scientific Evidence and Statistical Performance.Diabetes & metabolism journal · 2020Article
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Authors and funding
7 authors.
Funding
Abstract
backgroundA diabetes risk score in Korean adults was developed and validated.
methodsThis study used the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) of 359,349 people without diabetes at baseline to derive an equation for predicting the risk of developing diabetes, using Cox proportional hazards regression models. External validation was conducted using data from the Korean Genome and Epidemiology Study. Calibration and discrimination analyses were performed separately for men and women in the development and validation datasets.
resultsDuring a median follow-up of 10.8 years, 37,678 cases (event rate=10.4 per 1,000 person-years) of diabetes were identified in the development cohort. The risk score included age, family history of diabetes, alcohol intake (only in men), smoking status, physical activity, use of antihypertensive therapy, use of statin therapy, body mass index, systolic blood pressure, total cholesterol, fasting glucose, and γ glutamyl transferase (only in women). The C-statistics for the models for risk at 10 years were 0.71 (95% confidence interval [CI], 0.70 to 0.73) for the men and 0.76 (95% CI, 0.75 to 0.78) for the women in the development dataset. In the validation dataset, the C-statistics were 0.63 (95% CI, 0.53 to 0.73) for men and 0.66 (95% CI, 0.55 to 0.76) for women.
conclusionThe Korean Diabetes Risk Score may identify people at high risk of developing diabetes and may be an effective tool for delaying or preventing the onset of condition as risk management strategies involving modifiable risk factors can be recommended to those identified as at high risk.
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