Obesity with an body mass index over 40
Conditions
Interventions
Group 1: Patients undergoing laparoscopic sleeve gastrectomy for obesity
Sponsors
Universitätsmedizin Mannheim
Eligibility
Sex/Gender
All
Age
18 Years to No maximum
Inclusion criteria
Inclusion criteria: - Scheduled for LSG - Written informed consent
Exclusion criteria
Exclusion criteria: - Previous bariatric or major upper gastrointestinal surgery - Language barriers or impaired mental state - Unable to attend follow-up examinations
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| To develop and validate a predictive algorithm using machine learning techniques that analyzes annotated surgical videos of laparoscopic sleeve gastrectomy to determine the likelihood of patients developing postoperative dysphagia, reflux symptoms, and to evaluate the degree of weight loss 12 months after LSG. | — |
Secondary
| Measure | Time frame |
|---|---|
| • To identify and analyze the correlation between specific intraoperative events or techniques (as captured in surgical videos) and the development of postoperative symptoms, including dysphagia and reflux, as well as the extent of weight loss. • To create and utilize a comprehensive dataset that combines surgical video annotations with clinical parameters (including postoperative symptomatology and weight loss metrics) for advanced research in bariatric surgery outcomes. • To assess the feasibility and effectiveness of machine learning algorithms in predicting surgical outcomes, focusing on both immediate postoperative complications (like dysphagia and reflux) and long-term outcomes (such as weight loss), based on intraoperative video data. | — |
Countries
Germany
Contacts
Public ContactCui Yang
Universitätsmedizin Mannheim
Outcome results
None listed