AI-assisted Endotracheal Intubation

AI-assisted Endotracheal Intubation in Children and Neonates: A Prospective Randomized Controlled Simulation Trial

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Intubation Performance Using AI Versus Conventional Videolaryngoscope in a Mannikin
• Intervention / Treatment: Other: AI-assisted videolaryngoscopy; Other: Conventional Intubation

Detailed Description

Artificial intelligence is increasingly being applied in clinical medicine, including airway management. Machine vision algorithms have recently been developed to recognize airway anatomy and provide guidance during endotracheal intubation.

LarynGuide is an AI-based system designed to guide endotracheal tube placement using real-time visual prompts during videolaryngoscopy. This study aims to evaluate whether AI-assisted intubation is equivalent to conventional videolaryngoscopy in terms of time required for intubation and whether AI guidance improves success rates or usability.

This prospective randomized controlled simulation trial will recruit healthcare providers with varying levels of airway management experience. Participants will receive a short training session with the AI system and then will be randomized to perform intubations using either AI-assisted videolaryngoscopy or conventional videolaryngoscopy.

Each participant will perform intubations on both pediatric and neonatal airway mannequins in a simulation setting. Outcomes including intubation time, success rate, number of attempts, POGO score, gaze tracking metrics, and user satisfaction will be collected.

The study will be conducted at the Hospital for Sick Children Simulation Centre in Toronto, Canada.

• Study Type: Interventional
• Enrollment (Estimated): 40
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Clyde Matava; Phone Number: 4168137445; Email: clyde.matava@sickkids.ca

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Any healthcare worker or trainee

Exclusion Criteria:

• refusal to participate

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Crossover Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: AI-assisted videolaryngoscopy; Participants perform simulated endotracheal intubation using videolaryngoscopy integrated with the AI guidance system	Other: AI-assisted videolaryngoscopy; Participants perform simulated endotracheal intubation using videolaryngoscopy integrated with the AI guidance system
Active Comparator: Conventional videolaryngoscopy; Participants perform simulated endotracheal intubation using standard videolaryngoscopy without AI assistance.	Other: Conventional Intubation; Traditional intubation

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
Time required for intubation	baseline, pre-intervention/procedure/surgery

Secondary Outcome Measures

Outcome Measure	Time Frame
First-attempt success rate	baseline, pre-intervention/procedure/surgery
POGO score	baseline, pre-intervention/procedure/surgery

Other Outcome Measures

Outcome Measure	Time Frame
SUS score	baseline, pre-intervention/procedure/surgery
Translated POGO score	baseline, pre-intervention/procedure/surgery
Intubation status (good vs bad vs not started)	baseline, pre-intervention/procedure/surgery
Intubation instructions (push forward, pull back, etc)	baseline, pre-intervention/procedure/surgery
Laryngoscopy status & instructions (need to move right, need to move back	baseline, pre-intervention/procedure/surgery
Gaze duration	baseline, pre-intervention/procedure/surgery

Collaborators and Investigators

• Sponsor: The Hospital for Sick Children

Publications and helpful links

General Publications

• Nemani S, Goyal S, Sharma A, Kothari N. Artificial intelligence in pediatric airway - A scoping review. Saudi J Anaesth. 2024 Jul-Sep;18(3):410-416. doi: 10.4103/sja.sja_110_24. Epub 2024 Jun 4.
• Matava C, Pankiv E, Ahumada L, Weingarten B, Simpao A. Artificial intelligence, machine learning and the pediatric airway. Paediatr Anaesth. 2020 Mar;30(3):264-268. doi: 10.1111/pan.13792. Epub 2020 Jan 2.

Study record dates

Study Major Dates

• Study Start (Estimated): April 1, 2026
• Primary Completion (Estimated): September 30, 2026
• Study Completion (Estimated): November 30, 2026

Study Registration Dates

• First Submitted: March 25, 2026
• First Submitted That Met QC Criteria: March 30, 2026
• First Posted (Actual): April 2, 2026

Study Record Updates

• Last Update Posted (Actual): April 2, 2026
• Last Update Submitted That Met QC Criteria: March 30, 2026
• Last Verified: March 1, 2026

More Information

Terms related to this study

• Keywords: children; simulation; infants; artificial intelligence; neonates; intubation; mannikin; larynguide
• Other Study ID Numbers: 1000082159

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No