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Development of a Pharyngeal Residue Level Assessment Index Using Artificial Intelligence (AI) Acoustic Analysis: A
Yoshitaka Shimizu1, Tamayo Takahashi2, Aya Oda2
1Department of Dental Anesthesiology, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, JPN.
Abstract:
The swallowing function is often compromised immediately after general anesthesia owing to the effects of anesthetic agents. Consequently, pharyngeal residue may accumulate, which increases the risk of aspiration during the perioperative period. Therefore, we designed a single-arm, open-label study, developing an artificial intelligence (AI)-based acoustic analyzer for quantifying pharyngeal residues and evaluating its efficacy. A sample of 30 patients aged ≥18 years scheduled for jaw deformity surgery will be enrolled in this study. Immediately after tracheal tube extubation, adventitious sounds from pharyngeal residues, such as saliva and blood, will be measured and quantified using an AI acoustic analysis system. Subsequently, the residual pharyngeal fluid will be suctioned and quantified by measuring the change in container weight before and after collection. The primary outcome measure will be the comparison of adventitious sounds before and after pharyngeal suction, and the secondary outcome will be the correlation between pharyngeal residue volume and adventitious sounds. The results of this study are expected to be drawn by 2025 upon its completion. This study will demonstrate the feasibility of AI-based acoustic monitoring for quantifying increased pharyngeal residues during perioperative management. This approach has the potential to reduce the risk of postoperative aspiration with a simple and inexpensive method.
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