Status:
COMPLETED
Prediction of Difficult Mask Ventilation Using 3D-Facescan and Machine Learning
Lead Sponsor:
Universitätsklinikum Hamburg-Eppendorf
Collaborating Sponsors:
Institute of Medical Technology and Intelligent Systems at Hamburg University of Technology
Conditions:
Mask Ventilation
General Anesthesia
Eligibility:
All Genders
18+ years
Brief Summary
The aim of this study is to prove feasibility and assess the diagnostic performance of a machine learning algorithm that relies on data from 3D-face scans with predefined motion-sequences and scenes (...
Eligibility Criteria
Inclusion
- Patients scheduling for ENT or OMS surgery in general anaesthesia, who require facemask ventilation and tracheal intubation after induction of anesthesia
- Patients aged at least 18 years
- Ability to understand the patient information and to personally sign and date the informed consent to participate in the study
- The patient is co-operative and available for the entire study
- Provided informed consent/patient representative
Exclusion
- Pregnant or breastfeeding woman
- Rapid sequence induction or other contraindications for facemask ventilation
- Planned awake tracheal intubation
Key Trial Info
Start Date :
November 7 2022
Trial Type :
OBSERVATIONAL
Allocation :
ACTUAL
End Date :
May 15 2023
Estimated Enrollment :
423 Patients enrolled
Trial Details
Trial ID
NCT05411406
Start Date
November 7 2022
End Date
May 15 2023
Last Update
September 26 2023
Active Locations (1)
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1
University Medical Center Hamburg-Eppendorf
Hamburg, Germany, 20246