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Analysis of respiratory properties using the low-frequency piezoelectric sensor in patients undergoing intravenous sedation: a prospective observational study

Patients who undergo general anesthesia may experience respiratory failure postoperatively because of respiratory depression or upper airway obstruction. We investigated whether a piezoelectric sensor (AYA-P sensor) can be used to detect upper airway obstruction in patients undergoing intravenous se...

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Published in:Trends in anaesthesia & critical care 2024-06, Vol.56, p.101357, Article 101357
Main Authors: Ando, Shinnosuke, Takagi, Saori, Harada, Tatsuya, Oono, Yuka, Maeda, Yuka, Kawakami, Ryudai, Hironaka, Tetsuo, Ishiguro, Takashi, Kohase, Hikaru
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container_title Trends in anaesthesia & critical care
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creator Ando, Shinnosuke
Takagi, Saori
Harada, Tatsuya
Oono, Yuka
Maeda, Yuka
Kawakami, Ryudai
Hironaka, Tetsuo
Ishiguro, Takashi
Kohase, Hikaru
description Patients who undergo general anesthesia may experience respiratory failure postoperatively because of respiratory depression or upper airway obstruction. We investigated whether a piezoelectric sensor (AYA-P sensor) can be used to detect upper airway obstruction in patients undergoing intravenous sedation. This prospective observational study included 26 patients who underwent dental treatment under sedation at a dental clinic. Participants were evaluated using a newly defined airway obstruction score (AOS). The AYA-P sensors were attached to the suprasternal notch and the midpoint between the umbilicus and xiphoid process. The patient's respiratory status was classified into four categories based on thoracic movements, capnography, and breathing sounds from recorded data (S1: no airflow, S2: hypoventilation, S3: normal breathing, and S4: artifact). The data obtained from the AYA-P sensors were processed using a 0.4-Hz low-pass filter, calculated using the moving standard deviation (MSD) method, and further processed using a 0.1-Hz low-pass filter (fMSD). Next, these data were differentiated (D-fMSD). We defined the positive predictive value (PPV) as fMSD or D-fMSD values higher than a threshold α in categories S1 and S2. PPV(αMAX) was defined as the maximum PPV, and the negative predictive value (NPV[αMAX]) was defined using the same αMAX. We compared each of the apnea-hypopnea time ratio (AHT%) and AOS with PPV(αMAX) and NPV(αMAX). The AHT% and AOS were correlated with PPV(αMAX) and NPV(αMAX) in the neck and abdomen, respectively. These findings suggest that an AYA-P sensor attached to the neck and abdomen can detect a patient's respiratory status. Processed data obtained from AYA-P sensors can predict upper airway obstruction in patients, and the predicted data may be dependent on individual anatomical differences. This study was registrated in the University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) clinical trial: Unique ID: UMIN000047007. [Display omitted] •Upper airway obstruction may cause severe respiratory failure.•Lightweight respiration recording devices may prevent adverse outcomes in wards.•Piezoelectric sensor AYA-P can discriminate respiratory motions.•Novel airway obstruction score categorizes patients to boost predictive sensor data.•AYA-P records respiratory events when attached to cervical notch and abdomen.
doi_str_mv 10.1016/j.tacc.2024.101357
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We defined the positive predictive value (PPV) as fMSD or D-fMSD values higher than a threshold α in categories S1 and S2. PPV(αMAX) was defined as the maximum PPV, and the negative predictive value (NPV[αMAX]) was defined using the same αMAX. We compared each of the apnea-hypopnea time ratio (AHT%) and AOS with PPV(αMAX) and NPV(αMAX). The AHT% and AOS were correlated with PPV(αMAX) and NPV(αMAX) in the neck and abdomen, respectively. These findings suggest that an AYA-P sensor attached to the neck and abdomen can detect a patient's respiratory status. Processed data obtained from AYA-P sensors can predict upper airway obstruction in patients, and the predicted data may be dependent on individual anatomical differences. This study was registrated in the University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) clinical trial: Unique ID: UMIN000047007. 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subjects Airway obstruction
Breath monitoring
Monitoring physiologic
Piezoelectric sensor
Postoperative complications
title Analysis of respiratory properties using the low-frequency piezoelectric sensor in patients undergoing intravenous sedation: a prospective observational study
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