Machine Learning Models for Prediction of Acute Kidney Injury After Noncardiac Surgery

April 8, 2024 updated by: Rao Sun

Development of Interpretable Machine Learning Models for Prediction of Acute Kidney Injury After Noncardiac Surgery

Acute kidney injury (AKI) is a common surgical complication characterized by a rapid decline in renal function. Patients with AKI are at an increased risk of developing chronic kidney disease and end-stage renal disease, which has been associated with an increased risk of morbidity, mortality and financial burdens. Identifying high-risk patients for postoperative AKI early can facilitate the development of preventive and therapeutic management strategies, and prediction models can be helpful in this regard.

The goal of this retrospective study is to develop prediction models for postoperative AKI in noncardiac surgery using machine learning algorithms, and to simplify the models by including only preoperative variables or only important predictors.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Actual)

88367

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

    • Hubei
      • Wuhan, Hubei, China, 430030
        • Rao Sun

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Adult patients who underwent noncardiac surgical procedures at Tongji hospital between July 2018 and October 2022 were included.

Description

Inclusion Criteria:

  • Adult patients (age ≥ 18 years) who had a serum creatinine measurement within 10 days before surgery and at least one measurement within 7 days after surgery.
  • Eligible surgeries encompassed general, thoracic, orthopedic, obstetric, gynecology, and neurosurgery procedures lasting longer than 1 hour

Exclusion Criteria:

  • Patients with concurrent cardiac, vascular, urological, or transplant surgeries.
  • Patients with an American Society of Anesthesiologists (ASA) physical status V.
  • Patients with end-stage renal disease (i.e., a glomerular filtration rate [eGFR] of 15 mL/min/1.73 m² or receiving hemodialysis).

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Postoperative acute kidney injury
Time Frame: Within 7 days after surgery
In accordance with the KDIGO creatinine criteria: a serum creatinine increases of 26.5 mmol/L within 48 hours or 1.5 times baseline within 7 days after surgery.
Within 7 days after surgery

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Investigators

  • Principal Investigator: Rao Sun, Tongji Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

November 27, 2023

Primary Completion (Actual)

December 15, 2023

Study Completion (Actual)

December 15, 2023

Study Registration Dates

First Submitted

November 19, 2023

First Submitted That Met QC Criteria

November 19, 2023

First Posted (Actual)

November 27, 2023

Study Record Updates

Last Update Posted (Actual)

April 10, 2024

Last Update Submitted That Met QC Criteria

April 8, 2024

Last Verified

April 1, 2024

More Information

Terms related to this study

Other Study ID Numbers

  • TJH-20230608C

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.