PrediSuisse: Automatized Assessment of Difficult Airway

NCT ID: NCT06453525

Last Updated: 2024-11-07

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

1800 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-12-01

Study Completion Date

2027-01-31

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Anesthesia Intubation; Difficult or Failed Airway Complication of Anesthesia

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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C-mac

Intubation performed with a C-Mac videolaryngoscope

intubation

Intervention Type OTHER

Tracheal intubation using one of the three existing videolaryngoscopes

MacGrath

Intubation performed with a MacGrath videolaryngoscope

intubation

Intervention Type OTHER

Tracheal intubation using one of the three existing videolaryngoscopes

Airtraq

Intubation performed with an Airtraq videolaryngoscope

intubation

Intervention Type OTHER

Tracheal intubation using one of the three existing videolaryngoscopes

Interventions

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intubation

Tracheal intubation using one of the three existing videolaryngoscopes

Intervention Type OTHER

Eligibility Criteria

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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.
Minimum Eligible Age

18 Years

Maximum Eligible Age

100 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Centre Hospitalier Universitaire Vaudois

OTHER

Sponsor Role lead

Responsible Party

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Patrick Schoettker

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Patrick Schoettker, PhD

Role: PRINCIPAL_INVESTIGATOR

Centre Hospitalier Universitaire Vaudois

Locations

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University Hospital Lausanne CHUV

Lausanne, , Switzerland

Site Status

Countries

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Switzerland

Central Contacts

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Patrick Schoettker, PhD

Role: CONTACT

+41213142007

Facility Contacts

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Patrick Schoettker, PhD

Role: primary

+41213142007

Other Identifiers

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04062024

Identifier Type: -

Identifier Source: org_study_id

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