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

What this Trial Is About

Researchers are investigating how clinical and ultrasound measurements can help predict the best videolaryngoscopy strategy for adults undergoing intubation during anesthesia or critical care. This observational, multicenter study aims to analyze data using artificial intelligence, including statistical and machine-learning methods, to understand how these measurements relate to videolaryngoscopy outcomes. The goal is to develop decision-support tools to assist clinicians, though these tools will not replace medical judgment. The study collects clinical parameters, demographic information, and point-of-care airway ultrasound measurements from adult patients undergoing general anesthesia with videolaryngoscopy intubation. Various ultrasound measurements, such as distances from skin to anatomical landmarks and tongue thickness, are taken immediately before anesthesia induction. Additional clinical airway assessments like the Modified Mallampati Score and neck circumference are also recorded. Participants will undergo ultrasound and clinical airway evaluations before anesthesia induction. Researchers will measure specific distances and thicknesses with ultrasound probes and record physical airway assessment scores. The study will analyze these results to predict difficult videolaryngoscopy. Data collection supports the creation of predictive models, and participant involvement lasts through the scheduled surgery requiring intubation, with no treatment or intervention changes required.

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