ArticleScientific reports2020
A prediction nomogram for the 3-year risk of incident diabetes among Chinese adults.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
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Who cites it
23 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Progress of the application clinical prediction model in polycystic ovary syndrome.Journal of ovarian research · 2023Pooled 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 validation of a prediction model of catheter-related thrombosis in patients with cancer undergoing chemotherapy based on ultrasonography results and clinical information.Journal of thrombosis and thrombolysis · 2022Trial
- Development and Validation of a SHAP-Interpretable Machine Learning Model for Stroke Risk Prediction Using Circulating MicroRNA Biomarkers.Journal of molecular neuroscience : MN · 2026Article
- Pathophysiological Risk Factors Preceding Incidence of Type 2 Diabetes Subtypes: A Pooled Cohort Study in the United States.Diabetes care · 2026Article
- Triglyceride glucose-waist circumference as a useful predictor for diabetes mellitus: a secondary retrospective analysis utilizing a Japanese cohort study.BMC endocrine disorders · 2025Article
- Non-linear relationship between lipid accumulation products and risk of diabetes in Japanese adults.Scientific reports · 2024Article
- Association of preoperative red blood cell width and postoperative 30-day mortality in patients undergoing non-cardiac surgery: a retrospective cohort study using propensity-score matching.Perioperative medicine (London, England) · 2024Article
- Inhibition of YIPF2 Improves the Vulnerability of Oligodendrocytes to Human Islet Amyloid Polypeptide.Neuroscience bulletin · 2024Article
- A machine learning screening model for identifying the risk of high-frequency hearing impairment in a general population.BMC public health · 2024Article
- Machine learning for predicting hepatitis B or C virus infection in diabetic patients.Scientific reports · 2023Article
- A Nomogram for Predicting Prognosis of AdvancedTropical medicine and infectious disease · 2023Article
- Association Between Hypertension and New-Onset Non-Alcoholic Fatty Liver Disease in Chinese Non-Obese People: A Longitudinal Cohort Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Article
- The nonlinear correlation between the cardiometabolic index and the risk of diabetes: A retrospective Japanese cohort study.Frontiers in endocrinology · 2023Article
- Development and validation of a nonalcoholic fatty liver disease-based self-diagnosis tool for diabetes.Annals of translational medicine · 2022Article
- Development and validation of a nomogram based on the hospital information system for quantitative assessment of the risk of cardiocerebrovascular complications of diabetes.Annals of translational medicine · 2022Article
- Development of nomogram to predict in-hospital death for patients with intracerebral hemorrhage: A retrospective cohort study.Frontiers in neurology · 2022Article
- Development and validation of a carotid atherosclerosis risk prediction model based on a Chinese population.Frontiers in cardiovascular medicine · 2022Article
- Article
- Predicting Type 2 Diabetes Using Logistic Regression and Machine Learning Approaches.International journal of environmental research and public health · 2021Article
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7 authors.
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Abstract
Identifying individuals at high risk for incident diabetes could help achieve targeted delivery of interventional programs. We aimed to develop a personalized diabetes prediction nomogram for the 3-year risk of diabetes among Chinese adults. This retrospective cohort study was among 32,312 participants without diabetes at baseline. All participants were randomly stratified into training cohort (n = 16,219) and validation cohort (n = 16,093). The least absolute shrinkage and selection operator model was used to construct a nomogram and draw a formula for diabetes probability. 500 bootstraps performed the receiver operating characteristic (ROC) curve and decision curve analysis resamples to assess the nomogram's determination and clinical use, respectively. 155 and 141 participants developed diabetes in the training and validation cohort, respectively. The area under curve (AUC) of the nomogram was 0.9125 (95% CI, 0.8887-0.9364) and 0.9030 (95% CI, 0.8747-0.9313) for the training and validation cohort, respectively. We used 12,545 Japanese participants for external validation, its AUC was 0.8488 (95% CI, 0.8126-0.8850). The internal and external validation showed our nomogram had excellent prediction performance. In conclusion, we developed and validated a personalized prediction nomogram for 3-year risk of incident diabetes among Chinese adults, identifying individuals at high risk of developing diabetes.
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