This prospective observational study aims to develop and evaluate artificial intelligence-based models for the assessment of laryngeal mask airway (LMA) placement in adult patients undergoing elective surgery under general anesthesia. Following LMA insertion, standardized airway ultrasound images will be obtained and fiberoptic assessment will be performed as the anatomical reference standard. Fiberoptic findings will be classified as optimal (Brimacombe grades 3-4) or suboptimal (grades 1-2). Clinical and quantitative airway ultrasound variables will also be recorded. The predictive performance of tabular, image-only, and multimodal artificial intelligence models will be evaluated for identifying optimal versus suboptimal LMA placement.
Eligibility
Sex
ALL
Min age
18 Years
Max age
—
Healthy volunteers
No
Inclusion Criteria:
* Adults undergoing elective surgery under general anesthesia in whom LMA use is clinically planned; ASA physical status I-III; ability to provide written informed consent.
Exclusion Criteria:
* Emergency surgery; pregnancy; anticipated difficult airway; major upper airway or neck anatomical abnormality or previous major neck surgery; clinically significant aspiration risk or contraindication to LMA use; inability to obtain adequate ultrasound images or fiberoptic assessment.
Primary outcome measure(s)
Discrimination of Optimal Versus Suboptimal LMA Placement by the Multimodal Artificial Intelligence Model — During the intraoperative assessment following LMA insertion, approximately within 15 minutes after placement The ability of the multimodal artificial intelligence model combining post-placement ultrasound images with prespecified clinical and quantitative ultrasound variables to discriminate optimal from suboptimal LMA placement, using fiberoptic assessment as the reference standard. Optimal placement will be defined as Brimacombe grades 3-4 and suboptimal placement as grades 1-2. Model discrimination will primarily be quantified using the area under the receiver operating characteristic curve (AUROC).
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
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