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NCT Number: NCT07030166

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

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.

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Key information

Conditions

Kidney Injury, Acute Acute Kidney Injury Female Urogenital Diseases Female Urogenital Diseases and Pregnancy Complications Kidney Diseases Male Urogenital Diseases Renal Insufficiency Urogenital Diseases Urologic Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Zhongda Hospital Southeast University

Nanjing, China

Location status: Recruiting

About this study

The data in this study are divided into two parts: retrospective and prospective. The retrospective data served as the development set, sourced from the electronic medical records of adult patients who underwent non-cardiac surgery during hospitalization between July 2015 and June 2025. The prospective data constituted an external (temporal) validation set, with data collection commencing in July 2025 and expected to conclude in February 2026.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 18 years old or above
  • Undergo non-cardiac surgery

Exclusion criteria

  • At least one measurement of serum creatinine (SCr) was not conducted before and after the operation
  • End-stage renal disease (ESRD) that has received dialysis within the past year
  • Baseline SCr ≥ 4.5 mg/dl (because the clinical criteria for AKI based on elevated SCr may not be applicable to these patients)
  • Acute kidney injury occurred within 7 days before the operation
  • The surgical procedure is renal surgery
  • The operation time is less than 2 hours

Treatment and study plan

No intervention measures were used.

Other

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

Primary outcomes

  1. Acute kidney injury

    Time frame: Within 7 days after the operation

Secondary outcomes

  1. Postoperative complications

    Time frame: Perioperative period

  2. Postoperative mortality

    Time frame: Perioperative period

  3. Hospitalization costs

    Time frame: Perioperative period

  4. Hospital stays

    Time frame: Perioperative period

Study contacts

Contact information is provided by the study sponsor or research team.

Yue Lan Zhu

CONTACT

[email protected]

+8618795969178

Sponsors and collaborators

Lead sponsor

Lanyue Zhu

Other

Registry information

Official study title

A Machine Learning Prediction Model for Postoperative Acute Kidney Injury in Non-Cardiac Surgery Patients: Development, Validation, and the Incremental Value of Frailty Assessment

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Jun 22, 2025
Registry last updated
Apr 2, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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