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

Postoperative Acute Kidney Injury Clinical Trial

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

Clinical Trial Summary

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.

Clinical Trial Description

n/a

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT06146829
Study type Observational
Source Tongji Hospital
Contact
Status Completed
Phase
Start date November 27, 2023
Completion date December 15, 2023
View Details
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