基于脑电图的麻醉深度监测研究进展

Ibrain Pub Date : 2024-12-06 DOI:10.1002/ibra.12186
Xiaolan He, Tingting Li, Xiao Wang
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引用次数: 0

摘要

全身麻醉通常包括三个关键组成部分:健忘症、镇痛和固定。在手术过程中监测麻醉深度(DOA)对于个性化麻醉方案和确保精确给药至关重要。由于全身麻醉药主要作用于大脑,因此该器官成为监测DOA的目标。脑电图(EEG)可以记录各种脑组织产生的电活动,使麻醉师能够通过手术期间患者大脑活动的实时变化来监测DOA。这种监测有助于优化麻醉用药,防止术中意识不清,减少心血管等不良事件的发生,有利于麻醉安全。不同的麻醉药物对脑电图特征的影响不同,这在常用的麻醉药物中得到了广泛的研究。然而,由于对意识的生物学基础和麻醉药物作用于大脑的机制了解有限,加上现有脑电图监测仪受到各种因素的影响,无法通过脑电图准确表达DOA。患者在全麻过程中缺乏反应性并不一定意味着无意识,这突出了在监测围手术期麻醉深度时区分意识机制和意识连接的重要性。虽然EEG是监测DOA的重要手段,但从EEG中提取特征信息进行DOA监测需要不断优化,基于人工智能分析的EEG监测技术是一个新兴的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Research progress on the depth of anesthesia monitoring based on the electroencephalogram

Research progress on the depth of anesthesia monitoring based on the electroencephalogram

General anesthesia typically involves three key components: amnesia, analgesia, and immobilization. Monitoring the depth of anesthesia (DOA) during surgery is crucial for personalizing anesthesia regimens and ensuring precise drug delivery. Since general anesthetics act primarily on the brain, this organ becomes the target for monitoring DOA. Electroencephalogram (EEG) can record the electrical activity generated by various brain tissues, enabling anesthesiologists to monitor the DOA from real-time changes in a patient's brain activity during surgery. This monitoring helps to optimize anesthesia medication, prevent intraoperative awareness, and reduce the incidence of cardiovascular and other adverse events, contributing to anesthesia safety. Different anesthetic drugs exert different effects on the EEG characteristics, which have been extensively studied in commonly used anesthetic drugs. However, due to the limited understanding of the biological basis of consciousness and the mechanisms of anesthetic drugs acting on the brain, combined with the effects of various factors on existing EEG monitors, DOA cannot be accurately expressed via EEG. The lack of patient reactivity during general anesthesia does not necessarily indicate unconsciousness, highlighting the importance of distinguishing the mechanisms of consciousness and conscious connectivity when monitoring perioperative anesthesia depth. Although EEG is an important means of monitoring DOA, continuous optimization is necessary to extract characteristic information from EEG to monitor DOA, and EEG monitoring technology based on artificial intelligence analysis is an emerging research direction.

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