Automated prediction of difficult intubation from face photos and short video
Official title: PrediSuisse: Automatized Assessment of Difficult Airway Using Three Videolaryngoscopes With the Help of Facial Recognition Techniques and Neural Network
Run by Centre Hospitalier Universitaire Vaudois · NCT06453525 · Data updated 2026-11-12
This project will test an AI tool that uses face photos and short videos taken at pre‑anesthesia visits to predict whether adults having elective general anesthesia will be difficult to intubate with three common videolaryngoscopes.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years to 100 Years |
| Sex | All |
| Enrollment | 1800 (estimated) |
| Sponsor | Centre Hospitalier Universitaire Vaudois Academic / other |
| Drugs / interventions | radiation |
| Locations | 1 site (Lausanne) |
| Status | Recruiting |
| Started | January 1, 2025 |
| Main results expected | November 15, 2026 |
| Study ends | January 31, 2027 |
| Registry record updated | March 27, 2026 |
| Trial ID | NCT06453525 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (≥18) presenting for elective general anesthesia requiring tracheal intubation at a participating Swiss pre‑anesthesia clinic who can give informed consent and speak the site's language (French or Italian) are ideal candidates.
✕Probably not a fit
Patients who are under 18, cannot consent, have prior airway surgery that altered anatomy, do not speak the required language, or present for emergency procedures are unlikely to benefit from participation.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
The PrediSuisse project will train and validate an AI/CNN software to predict endotracheal intubation difficulty by collecting facial photos and short video sequences during pre‑anesthesia consultations. A training set of 900 patients will be labeled for real intubation difficulty by three expert reviewers who examine recorded intubations using three commercially available videolaryngoscopes with different blade types. The model will then be applied prospectively to a separate set of 900 routine patients to validate prediction performance and produce a device‑specific difficulty score. The software aims to be ultra‑portable, radiation‑free, and to provide an objective, reproducible score to support airway management decisions.
Why it matters
Potential benefit: If successful, the tool could give anesthesiologists a quick, objective risk score to guide airway planning and reduce unexpected difficult intubations.
How similar studies have gone: Previous machine‑learning studies to predict difficult airways from clinical data or images have shown mixed results, so applying CNNs to photos with device‑specific labels is a relatively new and cautiously promising approach.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adult patients (≥ 18 years old) presenting at the pre-anesthesia consult for an elective general anesthesia necessitating a tracheal intubation * Signed informed consent. Exclusion Criteria: * Patients not speaking French (in Geneva and Lausanne) or Italian (in Lugano). * Patients previously operated on the airway with anatomical modifications (ENT Flaps, tracheotomies). * Patients unable to follow procedures or to give consent will also be excluded.
Where it's running
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University Hospital Lausanne CHUV
Lausanne, Switzerland Recruiting
Study contacts
- Principal investigator: Patrick Schoettker, PhD — Centre Hospitalier Universitaire Vaudois
- Study coordinator: Patrick Schoettker, PhD
- Email: patrick.schoettker@chuv.ch
- Phone: +41213142007
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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.