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

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.

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Key information

Conditions

Difficult Airway Intubation

Age range

18 year–65 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Duzce University Faculty of Medicine, Department of Anesthesiology and Reanimation

Düzce, Merkez, Turkey (Türkiye)

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Primary outcomes

Accuracy of Machine Learning Model in Predicting Difficult Intubation Based on Video Laryngoscopy Images

Time frame: Immediately after data collection and model training

The primary outcome is the classification accuracy of the machine learning algorithm in identifying difficult intubation cases (Cormack-Lehane grade 3-4) from video laryngoscopy images, compared with expert anesthesiologists' consensus. Accuracy will be reported as a percentage.

Sponsors and collaborators

Lead sponsor

Duzce University

Other

Registry information

Important dates

Study start: 2025
Primary completion: 2025
Study completion: 2025
First posted: Sep 3, 2025
Registry last updated: Nov 18, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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Completed