Gastric ultrasound: Enhancing preoperative risk assessment and patient safety

Perioperative pulmonary aspiration is a critical complication linked to significant morbidity and mortality, particularly in high-risk populations such as patients with diabetes, obesity, gastroparesis, or those using Glucagon-Like-Peptide-1 receptor agonists (GLP-1 RAs). Standard fasting protocols may not be appropriate for these patients, as they have increased propensity of delayed gastric emptying, hence increasing the complex of the preoperative risk assessment. Gastric ultrasound (GUS) provides a non-invasive, reliable method for assessing gastric content and volume, enabling anaesthesia professionals to make informed decisions regarding aspiration risk, airway management, and surgical scheduling. By identifying patients with elevated gastric volumes, GUS has the potential to reduce aspiration-related complications and unnecessary surgical cancellations.Despite its clear clinical benefits, the adoption of GUS in anaesthetic practice remains limited, primarily due to the technical skill required for accurate quantitative assessments. Qualitative evaluations of gastric contents are simpler for beginners, but precise volume measurements, essential for risk stratification, demand more extensive training. Recent studies demonstrate that with structured training, even novice operators can achieve high diagnostic accuracy. Artificial intelligence (AI) can further enhance GUS utility by automating volume calculations, guiding probe placement, and providing real-time feedback. These capabilities could significantly shorten the learning curve and improve consistency in risk assessment.Incorporating GUS and AI tools into anaesthesia training can overcome adoption barriers, enabling clinicians to more accurately assess aspiration risk and enhance patient safety in perioperative care.