Actively Recruiting
PrediSuisse: Automatized Assessment of Difficult Airway Using Three Videolaryngoscopes with Facial Recognition and Neural Network Techniques
Led by Centre Hospitalier Universitaire Vaudois · Updated on 2026-03-27
1800
Participants Needed
1
Research Sites
11 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
Researchers are investigating an automated software tool to predict the difficulty of tracheal intubation by analyzing facial features and movements. This study aims to create a reliable, reproducible, ultra-portable, and radiation-free system using machine learning and artificial intelligence techniques. The software will generate a difficulty score tailored to three different videolaryngoscopes and help anesthesiologists assess airway management risks objectively. The project involves collecting face and profile photos and video sequences from 900 patients during pre-anesthesia consultations. These images will be analyzed with neural networks to train the software to predict intubation difficulty, as determined by expert review of actual intubation procedures. The software will then be validated on an additional 900 patients undergoing intubation with one of three videolaryngoscopes: C-Mac, MacGrath, or Airtraq. Participants will have their facial data collected during routine pre-anesthesia visits, followed by real intubations using the designated videolaryngoscope. Researchers will evaluate the software's performance in predicting intubation difficulty and assess team communication over an 18-month period. The study does not involve any experimental treatments, and participation includes photo and video capture, data analysis, and observation of clinical intubation procedures.
CONDITIONS
Brief Title
PrediSuisse: Automatized Assessment of Difficult Airway
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Adult patients (≥ 18 years old) presenting at the pre-anesthesia consult for an elective general anesthesia necessitating a tracheal intubation
- Signed informed consent
You will not qualify if you...
- 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
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
Duration - Up to 18 months
Participants undergo face and profile photo acquisition and sequences using three videolaryngoscopes during the pre-anesthesia consultation to assess airway management difficulty.
1 visit (in-person)
Duration - Up to 18 months
Participants who undergo routine care are observed to validate the prediction performance of the developed software for airway management difficulty.
Trial Site Locations
Total: 1 location
1
University Hospital Lausanne CHUV
Lausanne, Switzerland, 1011
Actively Recruiting
Research Team
P
Patrick Schoettker, PhD
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
3
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