ArticleScientific reports2017
Development and validation of a risk prediction model for end-stage renal disease in patients with type 2 diabetes.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 3 of them syntheses that pooled it.
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Who cites it
24 citing papers in PubMed, 3 syntheses or guidelines pooled it, 47 citations in OpenAlex.
- Machine Learning Models for Prediction of Diabetic Microvascular Complications.Journal of diabetes science and technology · 2024Pooled it
- External validation of prognostic models for chronic kidney disease among type 2 diabetes.Journal of nephrology · 2022Pooled it
- Prognostic models of diabetic microvascular complications: a systematic review and meta-analysis.Systematic reviews · 2021Pooled it
- Scoring model to predict risk of chronic kidney disease in Chinese health screening examinees with type 2 diabetes.International urology and nephrology · 2022Trial
- Genetic risk score for risk prediction of diabetic nephropathy in Han Chinese type 2 diabetes patients.Scientific reports · 2019Trial
- Carbohydrate-dependent interaction between AMY1A/AMY2B copy number variation and APOA5 rs651821 associated with hypertriglyceridemia in Korean middle-aged adults.BMC nutrition · 2026Article
- Using machine learning algorithms to predict MACE in peritoneal dialysis patients.Scientific reports · 2026Article
- Setting Ranges in Potential Biomarkers for Type 2 Diabetes Mellitus Patients Early Detection By Sex-An Approach with Machine Learning Algorithms.Diagnostics (Basel, Switzerland) · 2024Article
- Proteinuria, measured or estimated albuminuria for risk prediction in patients with chronic kidney disease?Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024Article
- Development and deployment of a nationwide predictive model for chronic kidney disease progression in diabetic patients.Frontiers in nephrology · 2023Article
- Development and Validation of a Lifetime Risk Model for Kidney Failure and Treatment Benefit in Type 2 Diabetes: 10-Year and Lifetime Risk Prediction Models.Clinical journal of the American Society of Nephrology : CJASN · 2022Article
- A simplified prediction model for end-stage kidney disease in patients with diabetes.Scientific reports · 2022Article
- Development and implementation of patient-level prediction models of end-stage renal disease for type 2 diabetes patients using fast healthcare interoperability resources.Scientific reports · 2022Article
- Machine learning to predict end stage kidney disease in chronic kidney disease.Scientific reports · 2022Article
- Renal Replacement Therapy in People With and Without Diabetes in Germany, 2010-2016: An Analysis of More Than 25 Million Inhabitants.Diabetes care · 2021Article
- Empagliflozin ameliorates symptoms of diabetes and renal tubular dysfunction in a rat model of diabetes with enlarged kidney (DEK).PloS one · 2021Article
- Machine-learning-based early prediction of end-stage renal disease in patients with diabetic kidney disease using clinical trials data.Diabetes, obesity & metabolism · 2020Article
- Machine learning algorithm for early detection of end-stage renal disease.BMC nephrology · 2020Article
- Longitudinal Risk Prediction of Chronic Kidney Disease in Diabetic Patients Using a Temporal-Enhanced Gradient Boosting Machine: Retrospective Cohort Study.JMIR medical informatics · 2020Article
- Development of model to predict end-stage renal disease after coronary artery bypass grafting: The ACHE score.Medicine · 2019Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study is to develop a prediction model for ESRD in patients with type 2 diabetes. A retrospective cohort study was conducted, consisting of 24,104 Chinese patients with type 2 diabetes. We adopted the procedures proposed by the Framingham Heart Study to develop a prediction model for ESRD. Participants were randomly assigned to the derivation and validation sets at a 2:1 ratio. The Cox proportional hazard regression model was used for model development. A total of 813 and 402 subjects (5.06% and 5.00%, respectively) developed ESRD in the derivation and validation sets over a mean follow-up period of 8.3 years. The risk-scoring systems included age, gender, age of diabetes onset, combined statuses of blood pressure and anti-hypertensive medication use, creatinine, variation in HbA1c, variation in systolic blood pressure, diabetes retinopathy, albuminuria, anti-diabetes medications, and combined statuses of hyperlipidemia and anti-hyperlipidemia medication use. The area under curves of 3-year, 5-year, and 8-year ESRD risks were 0.90, 0.86, and 0.81 in the derivation set, respectively. This risk score model can be used as screening for early prevention. The risk prediction for 3-year, 5-year, and 8-year period demonstrated good predictive accuracy and discriminatory ability.
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