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Clinical Trial Details — Status: Not yet recruiting

Administrative data

NCT number NCT06453525
Other study ID # 04062024
Secondary ID
Status Not yet recruiting
Phase
First received
Last updated
Start date June 15, 2024
Est. completion date January 31, 2027

Study information

Verified date June 2024
Source Centre Hospitalier Universitaire Vaudois
Contact Patrick Schoettker, PhD
Phone +41213142007
Email patrick.schoettker@chuv.ch
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

In the "PrediSuisse" research project, the investigators aim to create a reliable, reproducible, ultra-portable and radiation-free automatized software, able to identify automatically collected features, facial characteristics, and range of movements, to predict intubation difficulty. The software will generate a difficulty intubation score tailored to three commercially available videolaryngoscopes with different type of blades, corresponding to the predicted endotracheal intubation difficulty while providing the anaesthesiologist a reliable and non-subjective tool to assess individual patient's risks with regards to airway management.


Description:

The Swiss multi-institutional research project "PrediSuisse" aims to automatically predict and classify the difficulty of intubation and airway management using three commercially available videolaryngoscopes (VL) by acquiring face/profiles photos and sequences on a training set of 900 patients during the pre-anaesthesia consultation. For each patient, with the help of recently developed Machine Learning (ML), Artificial Intelligence (AI) and Convolutional Neural Network (CNN) techniques, a specially developed software will be trained to provide a predicted airway management difficulty index. This will be performed by correlating those photos/sequences and the real difficulty level of intubation, determined by three experts by reviewing the recordings of the intubations of the training set patients. The software will then be used in routine on a set of 900 other patients to validate the prediction performance.


Recruitment information / eligibility

Status Not yet recruiting
Enrollment 1800
Est. completion date January 31, 2027
Est. primary completion date December 31, 2026
Accepts healthy volunteers No
Gender All
Age group 18 Years to 100 Years
Eligibility 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.

Study Design


Related Conditions & MeSH terms


Intervention

Other:
intubation
Tracheal intubation using one of the three existing videolaryngoscopes

Locations

Country Name City State
Switzerland University Hospital Lausanne CHUV Lausanne

Sponsors (1)

Lead Sponsor Collaborator
Centre Hospitalier Universitaire Vaudois

Country where clinical trial is conducted

Switzerland, 

Outcome

Type Measure Description Time frame Safety issue
Primary Software creation The primary outcome is to create a reliable, reproducible, ultra-portable and radiation-free automated software, capable of identifying automatically collected features such as facial characteristics, mouth opening, range of motion while moving the neck and thyromental distance to predict intubation difficulty.
The identification of the difficult intubation score will be compared by the one goven independantly by three airway experts.
18 months
Secondary Team Communication The secondary outcome is to evaluate the impact of streaming images of the intubations acquired by the videolaryngoscopy directly to the screens located in the operating room (OR) on communication between healthcare professionals in the OR with the help of a dedicated questionnaire. 18 months
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