SynthesisAnnals of medicine2024
Scoring and validation of a simple model for predicting diabetic retinopathy in patients with type 2 diabetes based on a meta-analysis approach of 21 cohorts.
Synthesis in Annals of medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Ibero-American position statement on therapeutic recommendations for the preventive management of cardiovascular complications in latin-American patients with type 2 diabetes mellitus: consensus of the prevention council of the inter-American society of cardiology (SIAC-PREVENT).Diabetology & metabolic syndrome · 2026Review
- Interpretable machine learning for predicting 30-day mortality following intracranial hemorrhage surgery.Frontiers in neurology · 2026Article
- The association between glycated hemoglobin and intraocular inflammatory factors in patients with proliferative diabetic retinopathy.International journal of retina and vitreous · 2025Article
- Diabetic retinal disease.Nature reviews. Disease primers · 2025Review
- C-reactive protein to high-density lipoprotein cholesterol ratio: an independent risk factor for diabetic retinopathy in type 2 diabetes patients.Frontiers in nutrition · 2025Article
- Development of machine learning predictive model for type 2 diabetic retinopathy using the triglyceride-glucose index explained by SHAP method.Frontiers in endocrinology · 2025Article
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Authors and funding
6 authors.
Funding
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Abstract
aimTo develop and validate a model for predicting diabetic retinopathy (DR) in patients with type 2 diabetes.
methodsAll risk factors with statistical significance in the DR prediction model were scored by their weights. Model performance was evaluated by the area under the receiver operating characteristic (ROC) curve, Kaplan-Meier curve, calibration curve and decision curve analysis. The prediction model was externally validated using a validation cohort from a Chinese hospital.
resultsIn this meta-analysis, 21 cohorts involving 184,737 patients with type 2 diabetes were examined. Sex, smoking, diabetes mellitus (DM) duration, albuminuria, glycated haemoglobin (HbA1c), systolic blood pressure (SBP) and TG were identified to be statistically significant. Thus, they were all included in the model and scored according to their weights (maximum score: 35.0). The model was validated using an external cohort with median follow-up time of 32 months. At a critical value of 16.0, the AUC value, sensitivity and specificity of the validation cohort are 0.772 ((95% confidence interval (95%CI): 0.740-0.803),
conclusionsThe simple DR prediction model developed has good overall calibration and discrimination performance. It can be used as a simple tool to detect patients at high risk of DR.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.