Development of Machine Learning Models for the Prediction of BMI and Complications After Bariatric Surgery (CABS-Study)
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Body Weight
- Sponsor
- Dr. Med Anas Taha
- Enrollment
- 10000
- Locations
- 1
- Primary Endpoint
- Complication after surgery
- Status
- Recruiting
- Last Updated
- 3 years ago
Overview
Brief Summary
This Study aims to develop machine learning models with the ability to predict patients' BMI and complications after Bariatric Surgery (CABS-Score).
This Study also aims to develop machine learning models with the ability to predict diabetic (DM II)patients' remission rate after Bariatric Surgery.
The service mentioned above will be publicly available as a web-based application
Investigators
Dr. Med Anas Taha
Research Fellow
University of Basel
Eligibility Criteria
Inclusion Criteria
- •Patients undergoing bariatric surgery
- •Patients \>18 years
Exclusion Criteria
- •Patients \<18 years
- •Patients who cannot be followed up on for more than 6 month after surgery
- •Patients who are unable to provide informed approval to participate according to each centre's rules will be excluded.
Outcomes
Primary Outcomes
Complication after surgery
Time Frame: [Time Frame: From index surgery up to 3 months postoperatively]
Body mass Index (KG/m2) after surgery
Time Frame: [Time Frame: From index surgery up to 1 year postoperatively]
Diabetes mellitus type II remission rate postoperatively
Time Frame: [Time Frame: From index surgery up to 2 year postoperatively]