Intelligent System for Preventing and Managing Diabetic Kidney Disease Across Its Course
Studies an artificial intelligence system to predict and manage diabetic kidney disease in adults.
Plain-language title generated from the registry record
Registry title: The Intelligent Prevention And Control System And Strategy For The Whole Disease Cycle Of Diabetic Nephropathy
Key facts
- Where
- Beijing, ChinaSee the site
AI summary: who the study is looking for
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The trial is looking for adults with type 2 diabetes, either with normal kidneys or with kidney damage who had a kidney biopsy.
- Age
- 18 years or older.
- Sex
- All sexes can join.
- Disease stage
- Two groups. Group 1: type 2 diabetes for more than 5 years, no protein in the urine, normal creatinine. Group 2: type 2 diabetes with kidney damage (small or large amounts of albumin in the urine, or kidney insufficiency).
- Earlier treatment
- Group 2 must have had a kidney needle biopsy with complete kidney pathology data.
- Biomarker or test result
- Group 1: negative proteinuria and normal creatinine. Group 2: microalbuminuria, overt albuminuria or kidney insufficiency.
Main reasons for not taking part
- Incomplete medical records
- No eye (fundus) microvessel exam or new imaging results (group 1)
- Autoimmune disease (both groups); tumors (group 1)
- Gestational diabetes, special type diabetes, or inherited kidney disease (group 2)
- Pregnancy plans during the study (group 2)
Read by machine on 11 November 2026.
Where in China
- Chinese PLA General HospitalBeijing, ChinaTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Chinese PLA General Hospital
- Trial code
- NCT06843304
- Record updated
- 20 April 2025
- Original description
Diabetic nephropathy is one of the most severe microvascular complications of diabetes and a major cause of premature death and disability. It has become a leading cause of end-stage renal failure both in China and worldwide, consuming substantial medical resources. The establishment of a comprehensive regulatory system for the development and progression of diabetic nephropathy is a critical need for effective prevention and control. However, there is a lack of representative cohorts covering the entire disease cycle of diabetic nephropathy both domestically and internationally, creating technical bottlenecks in comprehensively describing its developmental patterns. This project aims to expand and integrate existing large-sample natural population cohorts and prospective follow-up cohorts covering the entire disease cycle of diabetes and diabetic nephropathy. It will construct a panoramic life database to identify risk factors, clinical phenotypes, and multimodal biomarkers at different disease stages. By integrating multi-organ interactions (e.g., kidney, eye), the project will establish novel imaging and functional assessment technologies for microvascular complications. Utilizing artificial intelligence to process multimodal medical data, it will build and validate risk prediction models and evaluation systems for the entire disease cycle of diabetic nephropathy. The project will develop effective intelligent prevention and treatment strategies for diabetic nephropathy, promote the adoption of new technologies, and establish a medical quality control system to provide services for medical institutions. Ultimately, it aims to improve and sustain medical quality, reducing the incidence of end-stage renal disease.Read full original descriptionShow less
The Intelligent Prevention And Control System And Strategy For The Whole Disease Cycle Of Diabetic Nephropathy
Diabetic nephropathy is one of the most severe microvascular complications of diabetes and a major cause of premature death and disability. It has become a leading cause of end-stage renal failure both in China and worldwide, consuming substantial medical resources. The establishment of a comprehensive regulatory system for the development and progression of diabetic nephropathy is a critical need for effective prevention and control. However, there is a lack of representative cohorts covering the entire disease cycle of diabetic nephropathy both domestically and internationally, creating technical bottlenecks in comprehensively describing its developmental patterns. This project aims to expand and integrate existing large-sample natural population cohorts and prospective follow-up cohorts covering the entire disease cycle of diabetes and diabetic nephropathy. It will construct a panoramic life database to identify risk factors, clinical phenotypes, and multimodal biomarkers at different disease stages. By integrating multi-organ interactions (e.g., kidney, eye), the project will establish novel imaging and functional assessment technologies for microvascular complications. Utilizing artificial intelligence to process multimodal medical data, it will build and validate risk prediction models and evaluation systems for the entire disease cycle of diabetic nephropathy. The project will develop effective intelligent prevention and treatment strategies for diabetic nephropathy, promote the adoption of new technologies, and establish a medical quality control system to provide services for medical institutions. Ultimately, it aims to improve and sustain medical quality, reducing the incidence of end-stage renal disease.
Inclusion: Age ≥18 years old, gender is not limited; Diagnosed with type 2 diabetes; A history of type 2 diabetes for more than 5 years; Negative proteinuria; Creatinine is normal; Good compliance, voluntarily sign informed consent; Age ≥18 years old, gender is not limited; Diagnosed with type 2 diabetes; Kidney damage (microalbuminuria or dominant albuminuria or renal insufficiency); Have undergone renal puncture biopsy and have complete renal pathological diagnosis data; Sign informed consent voluntarily.
Exclusion: Combined with autoimmune diseases and tumors; Type 2 diabetes patients undergoing renal biopsy; Gestational diabetes mellitus, special type diabetes mellitus; Patients with hereditary kidney disease; Combined with autoimmune diseases; Incomplete medical records; Lack of fundus microvascular examination or new imaging technology examination results data; Diabetic nephropathy The indicators in the comprehensive assessment model of the risk of renal progression could not be obtained; There were pregnancy plans in the study period.
T2DM.