Study on Predicting Videolaryngoscopy Intubation Success Using Clinical and Ultrasound Data in Adults Undergoing Surgery

What this Trial Is About

Researchers are conducting a unicentric observational study to collect clinical, demographic, and airway ultrasound data from patients undergoing videolaryngoscopy during general anesthesia. The study aims to analyze these variables using machine learning to understand their relationship with videolaryngoscopy outcomes, such as blade performance and the need for additional tools. The goal is to develop a predictive model to assist in planning videolaryngoscopy strategies, intended for research and decision support without replacing clinician judgment. Participants undergoing scheduled surgery that requires orotracheal intubation will have various clinical airway assessments and point-of-care ultrasound measurements performed. These include distances measured with linear and convex ultrasound probes, alongside clinical tests like the Modified Mallampati Score, thyromental and sternomental distances, interincisor distance, upper lip bite test, and neck circumference. Data are collected during the intubation procedure for analysis. During the study, participants will undergo ultrasound and clinical airway evaluations taking a few minutes each. Researchers will measure distances to airway structures and perform bedside airway tests. These measures will be monitored to develop a model predicting videolaryngoscopy challenges. Participation involves data collection only, with no experimental treatments. The study runs until June 2026, with no additional follow-up specified.

Airway Coach Project: Prediction of Videolaryngoscopy Strategy With Clinical and Ultrasound Parameters (Unicentric)