Abstract

BackgroundIn this study, we aimed to analyse survey data to explore two different hypotheses; and for this purpose, we distributed an online survey to Chinese anaesthesiologists. The hypothetical questions in this survey include: (1) Chinese anaesthesiologists mainly use the depth of anaesthesia (DoA) monitors to prevent intraoperative awareness and (2) the accuracy of these monitors is the most crucial performance factor during the clinical daily practice of Chinese anaesthesiologists.MethodsWe collected and statistically analysed the response of a total of 12,750 anesthesiologists who were invited to participate in an anonymous online survey. The Chinese Society of Anaesthesiologists (CSA) trial group provided the email address of each anaesthesiologist, and the selection of respondents was random from the computerized system.ResultsThe overall response rate was 32.0% (4037 respondents). Only 9.1% (95% confidence interval, 8.2-10.0%) of the respondents routinely used DoA monitors. Academic respondents (91.5, 90.3-92.7%) most frequently used DoA monitoring to prevent awareness, whereas nonacademic respondents (88.8, 87.4-90.2%) most frequently used DoA monitoring to guide the delivery of anaesthetic agents. In total, the number of respondents who did not use a DoA monitor and whose patients experienced awareness (61.7, 57.8-65.6%) was significantly greater than those who used one or several DoA monitors (51.5, 49.8-53.2%). Overall, the crucial performance factor during DoA monitoring was considered by 61.9% (60.4-63.4%) of the respondents to be accuracy. However, most respondents (95.7, 95.1-96.3%) demanded improvements in the accuracy of the monitors for DoA monitoring. In addition, broad application in patients of all ages (86.3, 85.2-87.4%), analgesia monitoring (80.4, 79.2-81.6%), and all types of anaesthetic agents (75.6, 74.3-76.9%) was reported. In total, 65.0% (63.6-66.5%) of the respondents believed that DoA monitors should be combined with EEG and vital sign monitoring, and 53.7% (52.1-55.2%) believed that advanced DoA monitors should include artificial intelligence.ConclusionsAcademic anaesthesiologists primarily use DoA monitoring to prevent awareness, whereas nonacademic anaesthesiologists use DoA monitoring to guide the delivery of anaesthetics. Anaesthesiologists demand high-accuracy DoA monitors incorporating EEG signals, multiple vital signs, and antinociceptive indicators. DoA monitors with artificial intelligence may represent a new direction for future research on DoA monitoring.

Highlights

  • In this study, we aimed to analyse survey data to explore two different hypotheses; and for this pur‐ pose, we distributed an online survey to Chinese anaesthesiologists

  • Academic anaesthesiologists primarily use depth of anaesthesia (DoA) monitoring to prevent awareness, whereas nonaca‐ demic anaesthesiologists use DoA monitoring to guide the delivery of anaesthetics

  • DoA monitors with artificial intelligence may represent a new direction for future research on DoA monitoring

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Summary

Introduction

We aimed to analyse survey data to explore two different hypotheses; and for this pur‐ pose, we distributed an online survey to Chinese anaesthesiologists. The hypothetical questions in this survey include: (1) Chinese anaesthesiologists mainly use the depth of anaesthesia (DoA) monitors to prevent intraoperative aware‐ ness and (2) the accuracy of these monitors is the most crucial performance factor during the clinical daily practice of Chinese anaesthesiologists. Rapid advances in brain function monitoring technology have promoted the extensive application of electroencephalography (EEG) depth of anaesthesia (DoA) monitors in modern clinical practice. DoA monitoring for brain function monitoring was published previously [1,2,3]. Patients should undergo brain function monitoring, such as DoA monitoring, to reduce postoperative neurocognitive dysfunction [1]. Due to the limitations of DoA monitors based on current EEG technology, the role of these monitors in clinical practice is still controversial. Several proprietary algorithms analyse the data and provide a dimensionless number that is intended to reflect DoA [8]

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