AI-assisted Endotracheal Intubation

This study evaluates artificial intelligence (AI)-assisted videolaryngoscopy for endotracheal intubation in a simulated pediatric airway environment. Healthcare providers with varying levels of airway management experience will perform intubations on pediatric and neonatal mannequins using either AI-assisted videolaryngoscopy (larynGuide) or conventional videolaryngoscopy.

Participants will be randomized to perform intubation tasks using one of the two techniques. The primary outcome is the time required for successful intubation. Secondary outcomes include first-attempt success rate, number of attempts, airway visualization (POGO score), usability of the AI system measured by the System Usability Scale (SUS), and gaze tracking metrics evaluating user interaction with visual guidance.

This equivalence randomized controlled trial aims to determine whether AI-assisted videolaryngoscopy performs comparably to conventional videolaryngoscopy while potentially improving success rates and user experience.