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A Machine Learning Prediction Model for Postoperative Acute Kidney Injury in Non-Cardiac Surgery Patients

NCT07030166 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 10000

Last updated 2026-04-02

No results posted yet for this study

Summary

Primary objectives of this study is to develop and validate a predictive model for acute kidney injury after non-cardiac surgery based on machine learning. Secondary objectives of this study is to incorporate frailty assessment as a new predictor into the model and measure its incremental value was measured.

Conditions

  • Kidney Injury, Acute

Interventions

OTHER

No intervention measures were used.

The exposure factors were the perioperative related operations experienced by the patients and their individual conditions

Sponsors & Collaborators

  • Lanyue Zhu

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-07-01
Primary Completion
2026-12-31
Completion
2026-12-31

Countries

  • China

Study Locations

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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 NCT07030166 on ClinicalTrials.gov