Automated assessment of difficult airway using facial recognition
Automatic Assessment of Difficult Ventilation and Intubation From Automatic Face Analysis and Artificial Intelligence
This study is testing a new software that uses facial recognition to help doctors identify patients who might have a hard time with breathing tubes during anesthesia, aiming to make surgeries safer.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 6000 (estimated) |
| Ages | 16 Years and up |
| Sex | All |
| Sponsor | University of Lausanne Hospitals Academic / other |
| Locations | 1 site (Lausanne, Canton of Vaud) |
| Trial ID | NCT02022397 on ClinicalTrials.gov |
What this trial studies
This project aims to enhance patient safety during general anesthesia by developing software that utilizes image and video-processing technologies to automatically recognize anatomical features indicative of difficult ventilation and intubation. Patients will undergo a 10-minute assessment where their morphological and dynamic features will be analyzed in real-time to classify them into categories based on their risk for difficult airway management. The software will compute relevant measures such as mouth opening, visibility of anatomical landmarks, and neck mobility, which are critical for pre-operative anesthesia management. By improving the accuracy of pre-operative assessments, the study seeks to reduce complications associated with difficult airways.
Who should consider this trial
Good fit: Ideal candidates for this study are adult patients aged 15 and older who require endotracheal intubation for general anesthesia.
Not a fit: Patients who refuse to participate in the assessment will not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could significantly improve the safety and outcomes of patients undergoing general anesthesia by enabling more accurate pre-operative assessments.
How similar studies have performed: While the use of automated assessment techniques in anesthesia is a novel approach, similar studies have shown promise in improving pre-operative evaluations.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * adult patient (15 years of age) * patients necessitating endotracheal intubation for general anesthesia Exclusion Criteria: -patient refusal
Where this trial is running
Lausanne, Canton of Vaud
- Dpt of Anesthesiology, University of Lausanne CHUV — Lausanne, Canton of Vaud, Switzerland (Recruiting)
Study contacts
- Principal investigator: Patrick Schoettker, Assoc Prof — University of Lausanne Hospitals
- Study coordinator: Patrick Schoettker, Assoc Prof
- Email: patrick.schoettker@chuv.ch
- Phone: +41795561043
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.