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麻醉中存在连续性问题:EEG 的状态和反应熵。

Continuity with caveats in anesthesia: state and response entropy of the EEG.

机构信息

Department of Anesthesiology and Intensive Care, School of Medicine and Health, Technical University of Munich, Ismaningerstr. 22, 81675, Munich, Germany.

Abteilung für Anästhesiologie, Intensiv- und Schmerzmedizin, Hessing Stiftung, Hessingstraße 17, 86199, Augsburg, Germany.

出版信息

J Clin Monit Comput. 2024 Oct;38(5):1057-1068. doi: 10.1007/s10877-024-01130-9. Epub 2024 Apr 3.

Abstract

The growing use of neuromonitoring in general anesthesia provides detailed insights into the effects of anesthetics on the brain. Our study focuses on the processed EEG indices State Entropy (SE), Response Entropy (RE), and Burst Suppression Ratio (BSR) of the GE Entropy Module, which serve as surrogate measures for estimating the level of anesthesia. While retrospectively analyzing SE and RE index values from patient records, we encountered a technical anomaly with a conspicuous distribution of index values. In this single-center, retrospective study, we analyzed processed intraoperative electroencephalographic (EEG) data from 15,608 patients who underwent general anesthesia. We employed various data visualization techniques, including histograms and heat maps, and fitted custom non-Gaussian curves. Individual patients' anesthetic periods were evaluated in detail. To compare distributions, we utilized the Kolmogorov-Smirnov test and Kullback-Leibler divergence. The analysis also included the influence of the BSR on the distribution of SE and RE values. We identified distinct pillar indices for both SE and RE, i.e., index values with a higher probability of occurrence than others. These pillar index values were not age-dependent and followed a non-equidistant distribution pattern. This phenomenon occurs independently of the BSR distribution. SE and RE index values do not adhere to a continuous distribution, instead displaying prominent pillar indices with a consistent pattern of occurrence across all age groups. The specific features of the underlying algorithm responsible for this pattern remain elusive.

摘要

在全身麻醉中,神经监测的应用日益广泛,为我们深入了解麻醉药物对大脑的影响提供了详细信息。我们的研究重点是 GE 熵模块中经过处理的脑电图(EEG)指数状态熵(SE)、反应熵(RE)和爆发抑制比(BSR),它们可作为估计麻醉深度的替代指标。在对患者记录中的 SE 和 RE 指数值进行回顾性分析时,我们遇到了一个明显的指数值分布异常的技术问题。在这项单中心回顾性研究中,我们分析了 15608 名接受全身麻醉的患者的术中处理脑电图(EEG)数据。我们使用了各种数据可视化技术,包括直方图和热图,并拟合了自定义的非高斯曲线。详细评估了每位患者的麻醉期。为了比较分布,我们使用了 Kolmogorov-Smirnov 检验和 Kullback-Leibler 散度。分析还包括 BSR 对 SE 和 RE 值分布的影响。我们确定了 SE 和 RE 的两个明显的柱指标值,即比其他值出现概率更高的指数值。这些柱指标值与年龄无关,呈非等距分布模式。这种现象独立于 BSR 分布发生。SE 和 RE 指数值不遵循连续分布,而是呈现出突出的柱指标值,在所有年龄组中都以一致的模式出现。负责这种模式的基础算法的具体特征仍然难以捉摸。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0751/11427563/519ceecf15cf/10877_2024_1130_Fig1_HTML.jpg

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