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Development and Validation of a Machine Learning Model for Differentiating Diabetic Kidney Disease and Non-Diabetic Kidney Disease in Type 2 Diabetes

NCT07672639 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 2201

Last updated 2026-06-29

No results posted yet for this study

Summary

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.

Conditions

Sponsors & Collaborators

  • Beijing Tongren Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
70 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-01-01
Primary Completion
2022-12-01
Completion
2024-12-01

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07672639 on ClinicalTrials.gov