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Prediction of Kidney Injury After Hyperthermic Intraperitoneal Chemotherapy (HIPEC)* With Machine Learning — HIPEC  

Acute Kidney Injury Clinical Trial

Official title:
Application of Machine Learning to Predict Postoperative Acute Kidney Injury in Patients Undergoing Cytoreduction and Hyperthermic Intraperitoneal Chemotherapy Using High-resolution, Time-synchronized Physiological Data From Vital Recorder

Clinical Trial Summary

Patients undergoing cytoreductive surgery with hyperthermic intraoperative chemotherapy (CRS with HIPEC) are prone to postoperative kidney dysfunction. Previous models predicting kidney injury after CRS with HIPEC did not include intraoperative physiologic data. This study is designed to include not only mean arterial pressure but other parameters such as systolic, diastolic arterial pressure, heart rate, oxygen saturation, body temperature, cardiac index, stroke volume variation and many other physical parameters using a data collection system that can record them every 1-7 seconds. The data will be analyzed using machine learning algorithms.

Clinical Trial Description

n/a

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT03895606
Study type Observational
Source Gangnam Severance Hospital
Contact
Status Completed
Phase
Start date March 29, 2019
Completion date March 18, 2020
View Details
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