Machine Learning Models for Prediction of Acute Kidney Injury After Noncardiac Surgery
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
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Rao Sun
- Phone Number: +86-27-83663173
- Email: raosun@hust.edu.cn
Study Locations
-
-
Hubei
-
Wuhan, Hubei, China, 430030
- Rao Sun
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
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
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
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
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Rao Sun, Tongji Hospital
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- TJH-20230608C
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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