Actively Recruiting

Age: 18Years +
All Genders
NCT07030166

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

Led by Lanyue Zhu · Updated on 2026-04-02

10000

Participants Needed

1

Research Sites

78 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

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

Official Title

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

Who Can Participate

Age: 18Years +
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • 18 years old or above
  • Undergo non-cardiac surgery
Not Eligible

You will not qualify if you...

  • No serum creatinine measurement before and after the operation
  • End-stage renal disease requiring dialysis within the past year
  • Baseline serum creatinine 4.5 mg/dl or higher
  • Acute kidney injury occurred within 7 days before the operation
  • Surgical procedure is renal surgery
  • Operation time is less than 2 hours

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

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Trial Site Locations

Total: 1 location

1

Zhongda Hospital Southeast University

Nanjing, China

Actively Recruiting

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Research Team

Y

Yue Lan Zhu

CONTACT

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

2

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