Development of Machine Learning Models for the Prediction of BMI and Complications After Bariatric Surgery (CABS-Study)
Recruiting
- Conditions
- Post-Op ComplicationHiatal HerniaInternal HerniaIntussusceptionBody WeightSleep Apnea, ObstructiveAnastomosis, LeakingGERDMesenteric HerniaDiabetes Mellitus, Type 2
- Registration Number
- NCT05710913
- Lead Sponsor
- Dr. Med Anas Taha
- 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
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 10000
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.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Complication after surgery [Time Frame: From index surgery up to 3 months postoperatively] Body mass Index (KG/m2) after surgery [Time Frame: From index surgery up to 1 year postoperatively] Diabetes mellitus type II remission rate postoperatively [Time Frame: From index surgery up to 2 year postoperatively]
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
University of Basel - Department of Biomedical Engineering
🇨🇭Basel, Switzerland