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.
Study Type
OBSERVATIONAL
Enrollment
175,559
postoperative complications
Postoperative complications are classified by means of the Clavien-Dindo-Score. The Clavien-Dindo-Score describes classes of severity of postoperative complications: Grade I: any deviation from the normal postoperative course without the need for pharmacological treatment or surgical, endoscopic and radiological interventions Grade II: requiring pharmacological treatment Grade IIIa: requiring surgical, endoscopic or radiological intervention not under general anesthesia Grade IIIb: requiring surgical, endoscopic or radiological intervention under general anesthesia Grade IVa: single organ dysfunction Grade IVb: multiorgandysfunction Grade V: death of a patient
Time frame: 30 days
in-hospital mortality
mortality within hospital stay
Time frame: 30 days
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.