Trial reportJournal of clinical monitoring and computing2026
AI-assisted videolaryngoscopy improves intubation success: results from a randomized simulation trial.
Trial report in Journal of clinical monitoring and computing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06657417 (A.I. Supported Laryngoscopy and Endotracheal Intubation), which is not on this map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A.I. Supported Laryngoscopy and Endotracheal Intubation: a Manikin Study
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0 citing papers in PubMed.
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Video laryngoscopy has become an integral part of today's airway management. Despite its advantages, loss of depth perception and increased cognitive load remain a challenge and not all airway scenarios can be successfully managed and resolved. This study aims to evaluate the efficacy of larynGuide, an AI-based software integrated with the C-MAC video laryngoscope, in improving tracheal intubation success rates. This prospective, randomized, 2 × 2 crossover, simulation-based study included 74 medical professionals, 35 experienced and 39 inexperienced participants. Each participant performed tracheal intubations using a C-MAC video laryngoscope with and without the larynGuide AI overlay in both easy and difficult airway scenarios. The primary outcome was the first attempt success rate. Secondary outcomes included overall success rate, time to intubation, procedural performance scores, and incidence of dental injury. Data were analyzed using mixed effects models with binomial response and non-parametric tests as appropriate. The overall first attempt success rate was 89% with larynGuide and 85% with standard C-MAC, the odds of successful intubation were 72% higher with larynGuide (OR = 1.72, 95%CI = 1.08, 2.73; p = 0.022). Among experienced participants, the benefit was more pronounced (OR = 3.37, 95%CI = 1.2, 8.9; p = 0.016). Time to intubation was longer with larynGuide (median = 29 s) compared to standard C-MAC (median = 23 s, p < 0.01). The incidence of dental damage was lower with larynGuide (22%) compared to C-MAC (27%), although not statistically significant (p = 0.095). The larynGuide AI-powered software improved tracheal intubation success rates compared to standard C-MAC videolaryngoscopy in this simulation-based study, highlighting the potential role of AI in enhancing airway management. Further clinical studies are needed to confirm these results and support broader integration into practice.
trial registrationClinicalTrials.gov ID NCT06657417.
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