Prediction of Difficult Mask Ventilation Using 3D-Facescan and Machine Learning

Completed

• Conditions: General Anesthesia; Mask Ventilation

• Registration Number: NCT05411406
• Lead Sponsor: Universitätsklinikum Hamburg-Eppendorf

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 (MASCAN algorithm), together with patient-specific meta-data for the prediction of difficult mask ventilation. A secondary aim of the study is to verify whether voice and breathing scans improve the performance of the algorithm. From the clinical point of view, we believe that an automated assessment would be beneficial, as it preserves time and health-care resources while acting observer-independent, thus providing a rational, reproducible risk estimation.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2022-06-06
• Study First Submitted QC: 2022-06-06
• Study First Posted: 2022-06-09
• Study Start: 2022-11-07
• Primary Completion: 2023-05-15
• Study Completion: 2023-05-15
• Status Verified: 2023-09
• Last Update Submitted: 2023-09-24
• Last Update Posted: 2023-09-26

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 423

Inclusion Criteria

• 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 Criteria

• Pregnant or breastfeeding woman
• Rapid sequence induction or other contraindications for facemask ventilation
• Planned awake tracheal intubation

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Difficult facemask ventilation	1 hour	Observed difficult facemask ventilation after induction of anesthesia

Secondary Outcome Measures

Name	Time	Method
Difficult mask ventilation alert	1 hour	Noted by the responsible anaesthesiologist after airway management
Time to sufficient mask ventilation	1 hour	Recorded during airwaymanagement
Failed direct laryngoscopy	1 hour	Observed during airwaymanagement
Difficult intubation alert	1 hour	Noted by the responsible anaesthesiologist after airway management
Classification of intubation difficulty	1 hour	VIDIAC score rating between -1 and 5 points
Percentage of glottis opening (POGO)	1 hour	Grading of the best view obtained during laryngoscopy (%)
Airway-related adverse events	1 hour	Laryngospasm, bronchospasm, larynx trauma, airway trauma, soft tissue trauma, oral bleeding, edema, dental damage, corticosteroid application, accidental esophageal intubation, aspiration, hypotension or hypoxia
Difficult laryngoscopy	1 hour	Observed difficult laryngoscopy after induction of anesthesia
Number of attempts	1 hour	Observed during tracheal intubation
Intubation time	1 hour	Recorded during airwaymanagement
Post-intubation recommendation for an intubation method	1 hour	Recommendation of the responsible anaesthesiologist after airwaymanagement
Difficult tracheal intubation	1 hour	Observed difficult intubation after induction of anesthesia
Cormack Lehane grade	1 hour	Grading of the best view obtained during laryngoscopy (I-IV)
Impossible facemask ventilation	1 hour	Observed impossible facemask ventilation after induction of anesthesia
Successful first attempt intubation	1 hour	Observed during airway management
Minimal peripheral oxygen saturation (SpO2)	1 hour	Observed after induction of anesthesia

Trial Locations

Locations (1)

University Medical Center Hamburg-Eppendorf; 🇩🇪 Hamburg, Germany