Using AI to improve ultrasound assessment of difficult airways
Official title: Research on the Application of Artificial Intelligence Ultrasonic Recognition
Run by Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University · NCT05207254 · Data updated 2026-05-14
This study is no longer in our active list. It may have stopped recruiting or finished. The details below are as of 2026-05-14 and are kept for reference. Check ClinicalTrials.gov for its current status, or see similar studies below.
This study is testing whether using artificial intelligence to analyze ultrasound images can help doctors better predict and manage difficult airways during anesthesia.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 4000 (estimated) |
| Sponsor | Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University Academic / other |
| Locations | 1 site (Shanghai, Shanghai) |
| Trial ID | NCT05207254 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are adults aged 18 and older who are classified as ASA 1-3 and are scheduled for tracheal intubation under general anesthesia.
✕Probably not a fit
Patients with communication barriers, open head and neck trauma, cervical spine issues, or those requiring emergency surgery may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This study explores the use of artificial intelligence technology to analyze ultrasound features in patients undergoing tracheal intubation under general anesthesia. By evaluating the correlation between these ultrasound features and the occurrence of difficult airways, the researchers aim to develop diagnostic models that enhance early warning systems for difficult airway management. The approach is observational, focusing on extracting and analyzing data from ultrasound tests to improve clinical outcomes in anesthesia. The ultimate goal is to create a more intelligent and accurate method for predicting difficult airways.
Why it matters
Potential benefit: If successful, this could lead to more accurate predictions of difficult airways, improving patient safety during anesthesia.
How similar studies have gone: While this approach is novel, there is limited existing research on the use of AI in ultrasound assessments for difficult airways, indicating potential for groundbreaking advancements.
Who can join: the full rules
Show full inclusion / exclusion criteria
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.
Where it's running
-
Shanghai 9Th Hospital
Shanghai, Shanghai, China Recruiting
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.