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Development of Machine Learning Models for the Prediction of BMI and Complications After Bariatric Surgery (CABS-Study)

Recruiting
Conditions
Post-Op Complication
Hiatal Hernia
Internal Hernia
Intussusception
Body Weight
Sleep Apnea, Obstructive
Anastomosis, Leaking
GERD
Mesenteric Hernia
Diabetes 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
NameTimeMethod
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
NameTimeMethod

Trial Locations

Locations (1)

University of Basel - Department of Biomedical Engineering

🇨🇭

Basel, Switzerland

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