Machine Learning-Based Risk Profile Classification of Patients Undergoing Elective Heart Valve Surgery
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Enrollment
- 2,229
- Primary Endpoint
- Area under the curve for different prediction models
Study Overview
Brief 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.
Detailed 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.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Retrospective
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
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
Outcomes
Primary Outcomes
Area under the curve for different prediction models
Time Frame: Patients will included from 01.01.2008 - 31.12.2014
Three different predictions models will be used.
Secondary Outcomes
No secondary outcomes reported
Investigators
Jens Meier
Prof. Dr.
Kepler University Hospital