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麻醉医生的临床脑电图:第一部分:背景与基本特征

Clinical Electroencephalography for Anesthesiologists: Part I: Background and Basic Signatures.

作者信息

Purdon Patrick L, Sampson Aaron, Pavone Kara J, Brown Emery N

机构信息

From the Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, and Department of Anesthesia, Harvard Medical School, Boston, Massachusetts (P.L.P.); Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts (A.S., K.J.P.); and Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts; Department of Anesthesia, Harvard Medical School, Boston, Massachusetts; Institute for Medical Engineering and Science and Harvard-Massachusetts Institute of Technology, Health Sciences and Technology Program; and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts (E.N.B.).

出版信息

Anesthesiology. 2015 Oct;123(4):937-60. doi: 10.1097/ALN.0000000000000841.

Abstract

The widely used electroencephalogram-based indices for depth-of-anesthesia monitoring assume that the same index value defines the same level of unconsciousness for all anesthetics. In contrast, we show that different anesthetics act at different molecular targets and neural circuits to produce distinct brain states that are readily visible in the electroencephalogram. We present a two-part review to educate anesthesiologists on use of the unprocessed electroencephalogram and its spectrogram to track the brain states of patients receiving anesthesia care. Here in part I, we review the biophysics of the electroencephalogram and the neurophysiology of the electroencephalogram signatures of three intravenous anesthetics: propofol, dexmedetomidine, and ketamine, and four inhaled anesthetics: sevoflurane, isoflurane, desflurane, and nitrous oxide. Later in part II, we discuss patient management using these electroencephalogram signatures. Use of these electroencephalogram signatures suggests a neurophysiologically based paradigm for brain state monitoring of patients receiving anesthesia care.

摘要

广泛用于麻醉深度监测的基于脑电图的指标假定,相同的指标值对所有麻醉药都定义相同的无意识水平。相比之下,我们发现不同的麻醉药作用于不同的分子靶点和神经回路,以产生在脑电图中易于观察到的不同脑状态。我们进行了一个分为两部分的综述,以指导麻醉医生如何使用未处理的脑电图及其频谱图来追踪接受麻醉护理患者的脑状态。在第一部分中,我们回顾了脑电图的生物物理学以及三种静脉麻醉药(丙泊酚、右美托咪定和氯胺酮)和四种吸入麻醉药(七氟烷、异氟烷、地氟烷和氧化亚氮)脑电图特征的神经生理学。在第二部分中,我们将讨论如何利用这些脑电图特征进行患者管理。这些脑电图特征的应用为接受麻醉护理患者的脑状态监测提出了一种基于神经生理学的范例。

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