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This prospective observational study evaluates the feasibility and clinical utility of AI-enhanced continuous respiratory sound monitoring during intravenous anesthesia with supraglottic airway placement. With the increasing volume of surgical procedures requiring anesthesia, continuous respiratory monitoring has become essential. While standard monitors track anesthetic depth, end-tidal CO₂, oxygen saturation, and respiratory rate, real-time respiratory sound analysis offers additional clinical value. This study aims to verify whether continuous respiratory sound monitoring using the Airmod electronic stethoscope can detect respiratory depression and airway obstruction before hypoxemia develops, thereby improving the safety of supraglottic airway anesthesia. The protocol involves collecting 60 patients undergoing elective breast surgery with supraglottic airway anesthesia (inclusion criteria: age ≥18 years, BMI <35; exclusion criteria: emergency cases, anticipated difficult airways, age <18, BMI >35). During surgery, an electronic stethoscope patch provides continuous respiratory sound recording, converted to spectral data and analyzed by artificial intelligence, while standard anesthetic monitoring includes blood pressure, heart rate, bispectral index (BIS), SpO₂, and EtCO₂. Researchers document specific intraoperative events including airway positioning, oxygen flow adjustments, ventilation parameter changes, oxygen desaturation episodes, and abnormalities detected via auscultation. Anesthetic records, surgical notes, and recovery records are compiled in Excel format integrated with electronic medical records, with statistical analysis performed using SigmaPlot software. This research builds upon the Airmod electronic stethoscope approved for marketing in February 2025, aiming to establish device-specific respiratory monitoring protocols while enhancing patient safety during non-intubated anesthesia procedures.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| respiratory monitoring group | Patients receiving intravenous anesthesia with supraglottic airways |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Standard Airmod Respiratory Monitoring | Device | An AI-powered respiratory monitoring device that continuously analyzes auscultated tracheal sounds to estimate respiratory rate and alert on apnea. The device's acoustic sensor is attached to the pretracheal region of a subject using a double-sided sticker, and the attachment is secured with 3M tape. |
| Measure | Description | Time Frame |
|---|---|---|
| Time interval from respiratory event to oxygen desaturation | Time interval (in seconds) between respiratory events (apnea and partial airway obstruction) indicated by Airmod and oxygen desaturation (SpO2 ≥3% decrease from baseline) detected by pulse oximetry. | Intraoperative period (from sedation induction to the end of procedure) |
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Inclusion Criteria:
Exclusion Criteria:
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Adult patients scheduled for elective breast surgery under total intravenous anesthesia with supraglottic airway at National Taiwan University Hospital, Taipei, Taiwan
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Yajung Cheng, PhD | Contact | +886223123456 | chengyj@ntu.edu.tw |
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| ID | Term |
|---|---|
| D053120 | Respiratory Aspiration |
| ID | Term |
|---|---|
| D012120 | Respiration Disorders |
| D012140 | Respiratory Tract Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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