Artificial Intelligence Evaluation for Predicting Difficult Airways in Adults Undergoing Bariatric Surgery

What this Trial Is About

Researchers are evaluating how well artificial intelligence AI and machine learning models can predict difficult airways in adults undergoing bariatric surgery. The study focuses on comparing AIs ability to predict challenging intubation with traditional clinical scoring methods in obese patients, addressing an important safety concern during anesthesia. Participants will have preoperative airway assessments including the Upper Lip Bite Test, Mallampati score, Body Mass Index BMI, thyromental distance, and sternomental distance recorded. During surgery, the airway view is graded using the Cormack-Lehane classification via direct laryngoscopy. This observational study collects these measurements to analyze AIs diagnostic accuracy in predicting difficult intubations. During the study, participants will undergo standard preoperative assessments and intraoperative airway evaluation. Researchers will measure how accurately the AI model predicts difficult intubation, count the number of intubation attempts needed, and record if alternative airway management techniques are used. Participation involves routine clinical procedures before and during surgery, with all data collected to improve airway management in obese patients.

AI-Based Prediction of Difficult Airway in Bariatric Surgery