Observational studyScientific reports2021
Development and validation of resource-driven risk prediction models for incident chronic kidney disease in type 2 diabetes.
Observational study in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Chronic kidney disease risk assessment: Findings from backward-looking study using annual health check-up data in Japan.Diabetes, obesity & metabolism · 2025Article
- Predicting the onset of chronic kidney disease (CKD) for diabetic patients with aggregated longitudinal EMR data.PLOS digital health · 2025Article
- External validation of a minimal-resource model to predict reduced estimated glomerular filtration rate in people with type 2 diabetes without diagnosis of chronic kidney disease in Mexico: a comparison between country-level and regional performance.Frontiers in endocrinology · 2024Observational
- Development and Validation of a Prediction Model for Future Estimated Glomerular Filtration Rate in People With Type 2 Diabetes and Chronic Kidney Disease.JAMA network open · 2023Article
- Review
- Prediction of 3-year risk of diabetic kidney disease using machine learning based on electronic medical records.Journal of translational medicine · 2022Article
- Development and Validation of a Prediction Model for 5-Year Risk of Kidney Dysfunction in Patients with Hypertension and Glucose Metabolism Disorder.Risk management and healthcare policy · 2022Article
Corrections and comments
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Authors and funding
16 authors at 7 institutions in 2 countries.
Funding
Abstract
Prediction models for population-based screening need, for global usage, to be resource-driven, involving predictors that are affordably resourced. Here, we report the development and validation of three resource-driven risk models to identify people with type 2 diabetes (T2DM) at risk of stage 3 CKD defined by a decline in estimated glomerular filtration rate (eGFR) to below 60 mL/min/1.73m
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What OpenQuestion holds
Registered trials
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 OpenQuestion graph.