NCT04092933

Perioperative Risk Calculator

Machine-learning Model for Perioperative Risk Calculation

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 175,559 (actual)
• Sponsor: Technical University of Munich · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Not accepted

Summary

The aim of this project is to develop a machine-learning model for calculating the risk of postoperative complications. In addition to the data collected during the premedication, the model will include all intraoperative values recorded in the Patient Data Management System (PDMS), which include not only vital and respiratory parameters, but also medication and doses, intraoperative events and times. Postoperative complications are defined according to their severity according to the Clavien-Dindo score (Dindo, Demartines et al., 2004) and are collected from the data available in the health information system (HIS). The machine-learning model is created using an extreme-gradient boosting algorithm which has been updated with new data from the year 2021 to ensure accuracy of the model.

Conditions

• Perioperative/Postoperative Complications

Timeline

• Start date: 2014-05-01
• Primary completion: 2022-09-30
• Completion: 2024-12-31
• First posted: 2019-09-17
• Last updated: 2023-11-22