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AI-Based Prediction of Difficult Airway in Bariatric Surgery

Recruitingn/aAges 18 Years - 65 YearsAllElazıg Fethi Sekin Sehir Hastanesi
NCT07666074 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

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.

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📋 Eligibility rules (as published)
Inclusion Criteria: 1. Adult patients aged 18 to 65 years. 2. Scheduled for elective bariatric surgery under general anesthesia. 3. Body Mass Index (BMI) ≥ 35 kg/m². 4. Consenting to participate in the study. Exclusion Criteria: 1. Patients with known upper airway anatomical deformities, head and neck tumors, or a history of head/neck radiotherapy. 2. History of maxillofacial, airway, or cervical spine surgery. 3. Emergency surgeries. 4. Patients requiring planned awake fiberoptic intubation based on obvious preoperative clinical indicators.
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What it tests

  • Preoperative Airway Assessment and Direct Laryngoscopy
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Where

1 site
Fethi Sekin City Hospital
Elâzığ, Turkey (Türkiye)
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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