跳至主要内容
临床试验/NCT06843304
NCT06843304招募中不适用

The Intelligent Prevention And Control System And Strategy For The Whole Disease Cycle Of Diabetic Nephropathy

Chinese PLA General Hospital1 个研究点 分布在 1 个国家目标入组 2,000 人开始时间: 2024年1月1日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
发起方
入组人数
2,000
试验地点
1
主要终点
The incidence of complex renal endpoints

研究概览

简要总结

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.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者
否

入选标准

  • •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

排除标准

  • •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

结局指标

主要结局

The incidence of complex renal endpoints

时间窗: 3 years

The incidence of complex renal endpoints includes eGFR decreased progressively by more than 30% from baseline, ESRD and all-cause death.

次要结局

未报告次要终点

研究者

发起方
Chinese PLA General Hospital
申办方类型
Other
责任方
Principal Investigator
主要研究者

Xiangmei Chen

Academician/Principal Investigator/ Clinical Professor/Director

Chinese PLA General Hospital

研究点 (1)

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