AI-based Prediction Model of Difficult Tracheal Intubation Using Medical Image Parameters

Difficult airway is a life-threatening event during anesthesia. Prediction model is helpful to detect high-risk patients and decrease the risk of un-anticipated difficult airway. Present models are usually based on Mallampati grade and the width of mouth open. However, the prediction accuracy is only about 0.7-0.8 in different populations. Present study is designed to investigate if AI-based prediction model using medical imaging parameters (such as CT and MRI) can increase the accuracy of prediction model.

NCT Number	NCT06982144
Lead Sponsor	Mu Dong Liang
Conditions	Difficult Airway
Enrollment	228 participants
Start Date	2025-05-20
Primary Completion	2026-03-01 (estimated)
Study Completion	2026-05-30 (estimated)
Updated on ClinicalTrials.gov	2025-05-21