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Tracheal sounds accurately detect apnea in patients recovering from anesthesia

  • Jing Liu
  • Chunyu Ai
  • Bowen Zhang
  • Yun Wang
  • Lara M. Brewer
  • Chien-Kun Ting
  • Desheng Huang
  • Lu Yu
Original Research
  • 41 Downloads

Abstract

Apnea should be monitored continuously in the post anesthesia care unit (PACU) to avoid serious complications. It has been confirmed that tracheal sounds can be used to detect apnea during sedation in healthy subjects, but the performance of this acoustic method has not been evaluated in patients with frequent apnea events in the PACU. Tracheal sounds were acquired from the patients in the PACU using a microphone encased in a plastic bell. Concurrently, a processed nasal pressure signal was used as a reference standard to identify real respiratory events. The logarithm of the tracheal sound variance (log-var) was used to detect apnea, and the results were compared to the reference method. Sensitivity, specificity, positive likelihood ratios (PLR), and negative likelihood ratios (NLR) were calculated. One hundred and twenty-one patients aged 55.5 ± 13.2 years (mean ± SD) with a body mass index of 24.6 ± 3.7 kg/m2 were included in data analysis. The total monitoring time was 52.6 h. Thirty-four patients experienced 236 events of apnea lasting for a total of 122.2 min. The log-var apnea detection algorithm detected apnea with 92% sensitivity, 98% specificity, 46 PLR and 0.08 NLR. The performance of apnea detection in the PACU using the log-var tracheal sounds method proved to be reliable and accurate. Tracheal sounds could be used to minimize the potential risks from apnea in PACU patients.

Keywords

Tracheal sounds Acoustic monitoring Apnea detection Recovery from anesthesia 

Notes

Funding

This study was funded by the National Natural Science Foundation of China, Beijing, P.R. China (Grant No. 81401485).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Department of Biomedical Engineering, School of Fundamental SciencesChina Medical UniversityShenyangPeople’s Republic of China
  2. 2.Department of Anesthesiology, The First Affiliated HospitalChina Medical UniversityShenyangPeople’s Republic of China
  3. 3.Department of AnesthesiologyUniversity of UtahSalt Lake CityUSA
  4. 4.Department of AnesthesiologyTaipei Veterans General Hospital and National Yang-Ming UniversityTaipeiTaiwan, ROC
  5. 5.Department of Mathematics, School of Fundamental SciencesChina Medical UniversityShenyangPeople’s Republic of China

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