AI-based prediction of difficult airway in bariatric patients
Official title: Artificial Intelligence-Based Prediction of Difficult Airway in Bariatric Surgery: A Prospective Evaluation of Preoperative Airway Predictors
Run by Elazıg Fethi Sekin Sehir Hastanesi · NCT07666074 · Data updated 2026-11-12
Aims to test whether artificial intelligence can better predict difficult airway in adults undergoing bariatric surgery than traditional preoperative tests.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years to 65 Years |
| Sex | All |
| Enrollment | 340 (estimated) |
| Sponsor | Elazıg Fethi Sekin Sehir Hastanesi Academic / other |
| Locations | 1 site (Elâzığ, Elâzığ) |
| Status | Recruiting |
| Started | May 21, 2026 |
| Main results expected | September 1, 2026 |
| Study ends | October 15, 2026 |
| Registry record updated | June 24, 2026 |
| Trial ID | NCT07666074 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults aged 18-65 with BMI ≥ 35 kg/m² scheduled for elective bariatric surgery and who consent to participate.
✕Probably not a fit
Patients with normal airways or cases not requiring intubation difficulty assessment may not see additional benefit from AI predictions.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study will collect preoperative airway assessments (UBLT, Mallampati, BMI, thyromental distance, sternomental distance) in adults with BMI ≥ 35 kg/m² scheduled for elective bariatric surgery. AI and machine learning models will be developed to predict difficult intubation and compared against standard clinical scoring methods for accuracy, sensitivity, and specificity. Direct laryngoscopy outcomes will serve as the reference standard for airway difficulty. The study is conducted at a single center in Elazığ, Turkey, led by Elazıg Fethi Sekin Sehir Hastanesi. Enrollment is limited to adults 18-65 without certain airway deformities or contraindications for the planned anesthesia approach.
Why it matters
Potential benefit: If successful, AI-based prediction could help anesthesiologists anticipate difficult intubations more reliably and tailor airway planning for bariatric patients.
How similar studies have gone: Previous research suggests AI approaches can improve prediction of clinical outcomes in airway management, but this specific application in bariatric patients is relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
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.
Where it's running
-
Fethi Sekin City Hospital
Elâzığ, Elâzığ, Turkey (Türkiye) Recruiting
Study contacts
- Study coordinator: Muhammed Başpınar, M.D.
- Email: bspnr.muhammed@gmail.com
- Phone: +905395831141
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.