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

Research on the Application of Artificial Intelligence Ultrasonic Recognition

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.

Study Overview

• Status: Recruiting
• Conditions: Difficult Airways
• Intervention / Treatment: Diagnostic test: Ultrasonic test

• Study Type: Observational
• Enrollment (Anticipated): 4000

Contacts and Locations

Study Locations

• China
  • Shanghai
    • Shanghai, Shanghai, China, 200000
      • Recruiting
      • Shanghai 9Th Hospital
      • Contact: Hong Jiang; Phone Number: +8615121007303; Email: jianghongjiuyuan@163.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

adults who intend to undergo tracheal intubation under general anesthesia

Description

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 Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
difficult airway; C-L≥3 grade	Diagnostic test: Ultrasonic test; Ultrasonic test to the patient's head, neck and jaw area.
none difficult airway; C-L<3 grade	Diagnostic test: Ultrasonic test; Ultrasonic test to the patient's head, neck and jaw area.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnosed as a difficult airway	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	0-10minutes after intubation

Collaborators and Investigators

• Sponsor: Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University

Study record dates

Study Major Dates

• Study Start (Actual): December 18, 2021
• Primary Completion (Anticipated): December 1, 2025
• Study Completion (Anticipated): December 30, 2025

Study Registration Dates

• First Submitted: December 23, 2021
• First Submitted That Met QC Criteria: January 13, 2022
• First Posted (Actual): January 26, 2022

Study Record Updates

• Last Update Posted (Actual): July 13, 2022
• Last Update Submitted That Met QC Criteria: July 11, 2022
• Last Verified: December 1, 2021

More Information

Terms related to this study

• Other Study ID Numbers: SH9H-2021-T356-2

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No