ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2022
Establishment and Validation of a Nomogram Model for Prediction of Diabetic Nephropathy in Type 2 Diabetic Patients with Proteinuria.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.
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11 citing papers in PubMed, 3 syntheses or guidelines pooled it, 10 citations in OpenAlex.
- Risk factors for diabetic kidney disease in type 2 diabetes mellitus in Asia: a meta-analysis.Frontiers in endocrinology · 2026Pooled it
- Diagnostic accuracy of neutrophil-to-lymphocyte ratio in type 2 diabetic nephropathy: a meta-analysis.Frontiers in endocrinology · 2025Pooled it
- Risk prediction models for diabetic nephropathy among type 2 diabetes patients in China: a systematic review and meta-analysis.Frontiers in endocrinology · 2024Pooled it
- A nomogram prediction model incorporating noninvasive lens AGEs and conventional biochemical indicators for assessing and predicting diabetic kidney disease.Scientific reports · 2026Article
- Detection of Nondiabetic Kidney Disease in Patients with Diabetes Using Machine Learning and Electronic Medical Record Data.Kidney & blood pressure research · 2026Article
- Development and validation of a model that predicts the risk of diabetic kidney disease in type 2 diabetes mellitus patients: a retrospective study.Frontiers in endocrinology · 2025Article
- A Machine Learning Model for Predicting Diabetic Nephropathy Based on TG/Cys-C Ratio and Five Clinical Indicators.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- Clinical study of different prediction models in predicting diabetic nephropathy in patients with type 2 diabetes mellitus.World journal of diabetes · 2024Article
- The Diagnostic Performance of a Clinical Diagnosis of Diabetic Kidney Disease.Life (Basel, Switzerland) · 2023Article
- Development and Empirical Study of a Lower Extremity Deep Vein Thrombosis Prevention Protocol for Patients Undergoing Gynecologic Laparoscopic Surgery.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
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5 authors at 2 institutions in 1 country.
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Abstract
Purpose: To establish and validate the nomogram model for predicting diabetic nephropathy (DN) in type 2 diabetes mellitus (T2DM) patients with proteinuria. Methods: A total of 102 patients with T2DM and proteinuria who underwent renal biopsy were included in this study. According to pathological classification of the kidney, the patients were divided into two groups, namely, a DN group (52 cases) and a non-diabetic renal disease (NDRD) group (50 cases). The clinical data were collected, and the factors associated with diabetic nephropathy (DN) were analyzed with multivariate logistic regression. A nomogram model for predicting DN risk was constructed by using R4.1 software. Receiver operator characteristic (ROC) curves were generated, and the K-fold cross-validation method was used for validation. A consistency test was performed by generating the correction curve. Results: Systolic blood pressure (SBP), diabetic retinopathy (DR), hemoglobin (Hb), fasting plasma glucose (FPG) and triglyceride/cystatin C (TG/Cys-C) ratio were independent factors for DN in T2DM patients with proteinuria (P<0.05). The nomogram model had good prediction efficiency. If the total score of the nomogram exceeds 200, the probability of DN is as high as 95%. The area under the ROC curve was 0.9412 (95% confidence interval (CI) = 0.8981-0.9842). The 10-fold cross-validation showed that the prediction accuracy of the model was 0.8427. The Hosmer-Lemeshow (H-L) test showed that there was no significant difference between the predicted value and the actual observed value ( Conclusion: The nomogram model constructed in the present study improves the diagnostic efficiency of DN in T2DM patients with proteinuria, and it has a high clinical value.
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