Machine Learning-Based Risk Profile Classification of Patients Undergoing Elective Heart Valve Surgery

Surgery--Complications Clinical Trial

Official title:

Machine Learning-Based Risk Profile Classification of Patients Undergoing Elective Heart Valve Surgery

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03724123
• Other study ID #: K-82-15
• Status: Completed
• Start date: January 1, 2008
• Est. completion date: December 31, 2014

Study information

• Verified date: October 2018
• Source: Kepler University Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Machine learning methods potentially provide a highly accurate and detailed assessment of expected individual patient risk before elective cardiac surgery. Correct anticipation of this risk allows for improved counseling of patients and avoidance of possible complications. The investigators therefore investigate the benefit of modern machine learning methods in personalized risk prediction in patients undergoing elective heart valve surgery.

Description:

The investigators performe a monocentric retrospective study in patients who underwent elective heart valve surgery between January 1, 2008, and December 31, 2014 at our center. The investigators use random forests, artificial neural networks, and support vector machines to predict the 30-days mortality from a subset of demographic and preoperative parameters. Exclusion criteria were re-operation of the same patient, patients that needed anterograde cerebral perfusion due to aortic arch surgery, and patients with grown up congenital heart disease.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 2229
• Est. completion date: December 31, 2014
• Est. primary completion date: December 31, 2014
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Patients who underwent heart valve surgery of any kind between 2008-01-01 and 2014-12-31 were included.

Exclusion Criteria:

• re-operation of the same patient

• patients that needed anterograde cerebral perfusion due to aortic arch surgery

• patients with grown-up congenital heart disease

Related Conditions & MeSH terms

• Heart Valve Diseases
• Surgery--Complications

Locations

Country	Name	City	State
n/a

Sponsors (2)

Lead Sponsor	Collaborator
Kepler University Hospital	Institute of Bioinformatics, JKU Linz

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Area under the curve for different prediction models	Three different predictions models will be used.	Patients will included from 01.01.2008 - 31.12.2014