ArticleBMJ open2022
External validation of the risk prediction model for early diabetic kidney disease in Taiwan population: a retrospective cohort study.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Machine Learning Models for Prediction of Diabetic Microvascular Complications.Journal of diabetes science and technology · 2024Pooled 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
- Development and validation of a predictive model for diabetic kidney disease risk in patients with T2DM: a hospital data platform study.Frontiers in endocrinology · 2026Article
- High levels of high-density lipoprotein cholesterol may increase the risk of diabetic kidney disease in patients with type 2 diabetes.Scientific reports · 2024Article
- Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.Diabetes & metabolism journal · 2024Article
- [Detection of people at risk of having diabetes in the community pharmacy with the Findrisc test 2014-2021].Farmaceuticos comunitarios · 2024Article
- Article
- Correlation Between the Variability of Different Obesity Indices and Diabetic Kidney Disease: A Retrospective Cohort Study Based on Populations in Taiwan.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Article
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Authors and funding
6 authors.
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Abstract
objectivesThis study aims to independently and externally validate the Risk Prediction Model for Diabetic Kidney Disease (RPM-DKD) in patients with type 2 diabetes mellitus (T2DM).
designThis is a retrospective cohort study.
settingOutpatient clinics at Lee's United Clinics, Taiwan, China.
participantsA total of 2504 patients (average age 55.44 years, SD, 7.49 years) and 4455 patients (average age 57.88 years, SD, 8.80 years) were included for analysis in the DKD prediction and progression prediction cohorts, respectively. EXPOSURE: The predicted risk for DKD and DKD progression for each patient were all calculated using the RPM-DKD. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome measure was overall incidence of DKD. Secondary outcomes included DKD progression. The discrimination, calibration and precision of the RPM-DKD score were assessed.
resultsThe DKD prediction cohort and progression prediction cohort consisted of patients with 2504 and 4455 T2DM, respectively. The RPM-DKD examined in this study showed moderately discriminative ability with area under the curve ranged from 0.636 to 0.681 for the occurrence of DKD and 0.620 to 0.654 for the progression of DKD. The Hosmer-Lemeshow χ
conclusionsOn external validation, the RPM-DKD cannot accurately predict the risk of DKD occurrence and progression in patients with T2DM.
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