Clinical Trial

AI-Based Prediction of Difficult Airway in Bariatric Surgery

Study acronym: AI-Airway
Recruiting
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Summary
The aim of this prospective study is to evaluate the accuracy of artificial intelligence (AI) and machine learning algorithms in predicting difficult airways in patients undergoing bariatric surgery. Preoperative airway assessments, including the Upper Lip Bite Test (UBLT), Mallampati score, Body Mass Index (BMI), thyromental distance (TMD), and sternomental distance (SMD), will be recorded. The study investigates whether AI models can provide higher sensitivity and specificity in predicting difficult intubation compared to traditional clinical scoring systems in the obese patient population.
Trial Details
NCT Number NCT07666074
Lead Sponsor Elazıg Fethi Sekin Sehir Hastanesi
Conditions Obesity Difficult Airway Airway Management
Enrollment 340 participants
Start Date 2026-05-21
Primary Completion 2026-09-01 (estimated)
Study Completion 2026-10-15 (estimated)
Updated on ClinicalTrials.gov 2026-06-24