Using artificial intelligence to predict difficult airways in weight loss surgery
Tests whether artificial intelligence can predict difficult breathing tube placement in adults having bariatric surgery.
Plain-language title generated from the registry record
Registry title: AI-Based Prediction of Difficult Airway in Bariatric Surgery
Key facts
- Where
- Elâzığ, TürkiyeSee the site
AI summary: who the study is looking for
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The trial is looking for adults aged 18 to 65 with obesity who are scheduled for elective weight-loss (bariatric) surgery under general anesthesia. It tests whether AI can predict a difficult airway.
- Age
- 18 to 65 years
- Sex
- All sexes can join.
- Disease stage
- Body Mass Index (BMI) of 35 kg/m² or more, scheduled for elective bariatric surgery under general anesthesia.
- Earlier treatment
- No history of surgery on the face and jaw, airway, or neck spine. No history of head or neck radiotherapy.
Main reasons for not taking part
- Known upper airway shape problems or head and neck tumors
- History of head or neck radiotherapy
- Past surgery on the face and jaw, airway, or neck spine
- Emergency surgery
- Planned awake fiberoptic intubation because of obvious signs before surgery
Read by machine on 13 November 2026.
Could this be for you?
Answer for yourself. This is not a decision: only the study team can say whether you can take part.
- Are you between 18 and 65 years old?
Source: NCT07666074, who can take part
Where in Türkiye
- Fethi Sekin City HospitalElâzığ, TürkiyeContact: Muhammed Başpınar, M.D.Taking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Contact the study team: see the registry record → Contacts and Locations
Print a page for my doctorTrial details
- Who runs it
- Elazıg Fethi Sekin Sehir Hastanesi
- Trial code
- NCT07666074
- Record updated
- 24 June 2026
- Original description
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.Read full original descriptionShow less
Artificial Intelligence-Based Prediction of Difficult Airway in Bariatric Surgery: A Prospective Evaluation of Preoperative Airway Predictors
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.
Inclusion: Adult patients aged 18 to 65 years; Scheduled for elective bariatric surgery under general anesthesia; Body Mass Index (BMI) ≥ 35 kg/m²; Consenting to participate in the study.
Exclusion: Patients with known upper airway anatomical deformities, head and neck tumors, or a history of head/neck radiotherapy; History of maxillofacial, airway, or cervical spine surgery; Emergency surgeries; Patients requiring planned awake fiberoptic intubation based on obvious preoperative clinical indicators.