Development and Validation of an Interpretable Machine Learning Model for Noninvasive Differentiation of Diabetic Kidney Disease and Non-Diabetic Kidney Disease in Type 2 Diabetes: A Multicenter Retrospective Cohort Study
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 2,201
- 试验地点
- 1
- 主要终点
- Diagnostic classification of DKD versus NDKD
研究概览
简要总结
This multicenter retrospective observational study aims to develop and validate an interpretable machine learning model for differentiating diabetic kidney disease (DKD) from non-diabetic kidney disease (NDKD) in patients with type 2 diabetes mellitus. Clinical, laboratory, and pathological data from biopsy-confirmed patients were collected from 14 medical centers in China. Multiple machine learning algorithms were evaluated and externally validated. The final model was implemented as a web-based clinical decision support tool.
详细描述
This study retrospectively collected clinical and pathological data from adult patients with type 2 diabetes who underwent kidney biopsy between January 2019 and December 2022 at 14 medical centers in China.
Patients were classified as having diabetic kidney disease (DKD), non-diabetic kidney disease (NDKD), or mixed pathology according to kidney biopsy findings. Demographic characteristics, diabetic complications, laboratory measurements, and renal function parameters were extracted from electronic medical records.
Six machine learning algorithms were trained and compared for discriminating DKD from NDKD. Recursive feature elimination was used for feature selection. The best-performing model was externally validated using an independent cohort enrolled between January 2022 and December 2024. Model interpretability was assessed using SHapley Additive exPlanations (SHAP).
The primary objective was to develop a noninvasive and interpretable diagnostic model capable of distinguishing DKD from NDKD using routinely available clinical variables.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 70 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age 18-70 years
- •Diagnosis of type 2 diabetes mellitus according to ADA criteria
- •Underwent kidney biopsy
- •Definitive pathological diagnosis available
- •Availability of required clinical and laboratory data
排除标准
- •Type 1 diabetes mellitus
- •Secondary diabetes
- •Missing key clinical data
- •Non-diagnostic kidney biopsy
- •Incomplete pathological information
结局指标
主要结局
Diagnostic classification of DKD versus NDKD
时间窗: During procedure
Pathological diagnosis based on kidney biopsy findings.
次要结局
- Area under the receiver operating characteristic curve (AUC)(Through study completion (December 2024))
- Sensitivity (%)(Through study completion (December 2024))
- Specificity (%)(Through study completion (December 2024))
- Accuracy (%)(Through study completion (December 2024))