AI-Based Prediction of Difficult Airway in Bariatric Surgery

NCT07666074 | Recruiting

• 1 other identifier: 2026/30-28
• Study Type: observational
• Target: 340
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Obesity Difficult Airway Airway Management

Keywords

Artificial Intelligence; Airway Management; Obesity; Machine Learning

Outcome Measures

Primary Outcomes (1)

• Diagnostic Accuracy of the Artificial Intelligence Model in Predicting Difficult Intubation

  The predictive performance of the AI model will be evaluated by comparing its preoperative difficult airway prediction against the actual intraoperative direct laryngoscopy view. The intraoperative view is graded using the Cormack-Lehane classification system. Grades 3 and 4 are clinically defined as difficult intubation, while Grades 1 and 2 are defined as easy intubation. The primary metric of diagnostic accuracy will be the Area Under the Receiver Operating Characteristic (AUC-ROC) curve.

  Intraoperative (assessed during the primary intubation attempt)

Secondary Outcomes (2)

• Number of Intubation Attempts

  Intraoperative

• Need for Alternative Airway Management Techniques

  Intraoperative

Study Arms (1)

Bariatric Surgery Patients

Patients scheduled for elective bariatric surgery under general anesthesia who undergo preoperative airway assessment using clinical and morphometric predictors.

Diagnostic Test: Preoperative Airway Assessment and Direct Laryngoscopy

Interventions

Preoperative Airway Assessment and Direct Laryngoscopy DIAGNOSTIC_TEST

Measurement of preoperative airway parameters including Upper Lip Bite Test (UBLT), Mallampati score, Body Mass Index (BMI), thyromental distance, and sternomental distance. Intraoperative airway view is graded using the Cormack-Lehane classification during standard direct laryngoscopy.

Also known as: Upper Lip Bite Test, Modified Mallampati Score, Thyromental Distance, Sternomental Distance, Cormack-Lehane Grading

Bariatric Surgery Patients

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population consists of adult obese patients (BMI ≥ 35 kg/m²) undergoing elective bariatric surgery under general anesthesia in a tertiary academic medical center. This population represents individuals at a higher baseline risk for difficult airway management and intubation.

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• Elazıg Fethi Sekin Sehir Hastanesi: lead

Study Sites (1)

Fethi Sekin City Hospital

Elâzığ, Elâzığ, 23100, Turkey (Türkiye)

RECRUITING

MeSH Terms

Conditions

Obesity

Condition Hierarchy (Ancestors)

Overweight; Overnutrition; Nutrition Disorders; Nutritional and Metabolic Diseases; Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Muhammed Başpınar, M.D.

CONTACT

+905395831141; bspnr.muhammed@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Specialist in Anesthesiology and Reanimation

Study Record Dates

• First Submitted: June 18, 2026
• First Posted: June 24, 2026
• Study Start: May 21, 2026
• Primary Completion (Estimated): September 1, 2026
• Study Completion (Estimated): October 15, 2026
• Last Updated: June 24, 2026

Record last verified: 2026-06

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP
• Access Criteria: Data will be shared upon reasonable request with qualified researchers who provide a methodologically sound proposal. Proposals should be directed to the corresponding author's email. To gain access, data requestors will need to sign a data access agreement.

Locations

TU (1)