The Intelligent Prevention And Control System And Strategy For The Whole Disease Cycle Of Diabetic Nephropathy
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Diabetic Nephropathy, T2DM. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
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.
Primary outcome measures
- The incidence of complex renal endpoints [Time frame: 3 years]
Eligibility criteria
T2DM
Inclusion criteria
- 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
Exclusion criteria
- Incomplete medical records
- Lack of fundus microvascular examination or new imaging technology examination results data
- Combined with autoimmune diseases and tumors
Type 2 diabetes patients undergoing renal biopsy
Inclusion criteria
- 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 criteria
- Gestational diabetes mellitus, special type diabetes mellitus
- Patients with hereditary kidney disease
- Combined with autoimmune diseases
- 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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
China · 1 center
- Chinese PLA General Hospital — Beijing
Identifiers
NCT: NCT06843304 · S2023-509-01