Research on the Application of Artificial Intelligence Ultrasonic Recognition Technology in Difficult Airway Assessment

Recruiting

• Conditions: Difficult Airways

• Registration Number: NCT05207254
• Lead Sponsor: Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University

Brief Summary

Although there is no related research on the evaluation of difficult airways by ultrasound features based on artificial intelligence, the investigators guess that the evaluation of ultrasound features based on artificial intelligence can make further breakthroughs in difficult airway early warning systems. Therefore, this project intends to use AI technology to extract and analyze the ultrasound features of the subjects, evaluate the correlation between the ultrasound features of the subjects and the occurrence of difficult airways, and construct possible diagnostic models to evaluate AI ultrasound feature recognition in the prediction of difficult airways. The effect and application value of this method are expected to be more intelligent and accurate for early warning of difficult airways in clinical anesthesia.

Detailed Description

Not available

Study Timeline

• Status Verified: 2021-12
• Study Start: 2021-12-18
• Study First Submitted: 2021-12-23
• Study First Submitted QC: 2022-01-13
• Study First Posted: 2022-01-26
• Last Update Submitted: 2022-07-11
• Last Update Posted: 2022-07-13
• Primary Completion: 2025-12-01
• Study Completion: 2025-12-30

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 4000

Inclusion Criteria

• ASA classification is 1-3
• Patients who intend to undergo tracheal intubation under general anesthesia
• Age ≥ 18 years old

Exclusion Criteria

• Patients with speech communication and cooperation barriers;
• Patients with open head and neck trauma
• Patients with cervical spine fractures or cervical spine diseases;
• Emergency surgery;
• Patients who are allergic to related drugs.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Diagnosed as a difficult airway	0-10minutes after intubation	Cormack-Lehane was used for grading the best glottic view. In grade the entire glottis was visible; in grade 2 a portion of the glottis was visible; in grade 3 only the epiglottis could be seen; and in grade 4 the epiglottis was not visible. A score of 3-4 indicated difficult video laryngoscopy

Trial Locations

Locations (1)

Shanghai 9Th Hospital; 🇨🇳 Shanghai, Shanghai, China