Comparison of Endotracheal Intubation Performance Using Video Laryngoscopy With and Without AI-Based Visual Assistance: A Manikin Pilot Study
This study investigated whether artificial intelligence (AI)-based visual assistance in video laryngoscopy (VL) could be a solution to reduce the technique's learning curve. Twenty volunteers with no prior intubation experience were randomly assigned to 2 equal groups: standard VL or AI-enhanced VL (AI-VL). Participants performed 10 consecutive intubations. The AI-VL group showed a trend toward steeper learning curves for intubation time (P > .05). The AI system functioned as a real-time virtual instructor, which provided visual feedback that helped maintain Cormack-Lehane (C-L) views.
Authors
- Thomas M. Hemmerling (ORCID: https://orcid.org/0000-0002-1447-0703)
- Pascal Laferrière-Langlois (ORCID: https://orcid.org/0000-0003-3347-1581)
- Sean Jeffries
- Éric Pelletier (ORCID: https://orcid.org/0000-0003-4228-1712)
- Oliver Cafferty
- Georgiy Danylenko
- Emma Rispler
Institutions
- McGill University Health Centre (CA)
- McGill University (CA)
- Université de Montréal (CA)
Publication Details
- Journal
- A&A Practice
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1213/xaa.0000000000002110
- Primary Topic
- Airway Management and Intubation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00