Development of an Artificial Intelligence-Based Model for Predicting Difficult Intubation Using Video Laryngoscopic Images and Cormack-Lehane Classification

Duzce University

Status: Completed

Conditions: Difficult Airway Intubation

Study type: Observational

Funder types: Other

Identifiers

NCT07152093

2025/183

Details and patient eligibility

About

This prospective observational study aims to develop an artificial intelligence model that can automatically determine the Cormack-Lehane classification from video laryngoscopy images in patients undergoing elective surgery. It also aims to predict the risk of difficult intubation based on this classification. The resulting data will evaluate the applicability of AI-supported decision support systems in clinical airway management.

Enrollment: 132 patients

Sex: All

Ages: 18 to 65 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• 18-65 years

Elective surgery

ASA I-II

No upper airway pathology

Exclusion criteria

• Known history of difficult intubation

Morbid obesity (BMI > 40)

Pregnancy

History of upper airway surgery

Trial design

132 participants in 2 patient groups

Group 1: Normal Intubation Group

Description:

Intubations in patients assessed as Cormack-Lehane (CL) Class 1-2.

Difficult Intubation Group

Description:

Intubations in patients evaluated as Cormack-Lehane Class 3-4.