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体外膜肺氧合昏迷患者脑电图反应性的定量评估。

Quantitative Assessment of Electroencephalogram Reactivity in Comatose Patients on Extracorporeal Membrane Oxygenation.

机构信息

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

出版信息

Int J Neural Syst. 2022 Jun;32(6):2250025. doi: 10.1142/S0129065722500253. Epub 2022 Apr 20.

Abstract

Objective assessment of the brain's responsiveness in comatose patients on Extracorporeal Membrane Oxygenation (ECMO) support is essential to clinical care, but current approaches are limited by subjective methodology and inter-rater disagreement. Quantitative electroencephalogram (EEG) algorithms could potentially assist clinicians, improving diagnostic accuracy. We developed a quantitative, stimulus-based algorithm to assess EEG reactivity features in comatose patients on ECMO support. Patients underwent a stimulation protocol of increasing intensity (auditory, peripheral, and nostril stimulation). A total of 129 20-s EEG epochs were collected from 24 patients (age [Formula: see text], 10 females, 14 males) on ECMO support with a Glasgow Coma Scale[Formula: see text]8. EEG reactivity scores ([Formula: see text]-scores) were calculated using aggregated spectral power and permutation entropy for each of five frequency bands ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text]. Parameter estimation techniques were applied to [Formula: see text]-scores to identify properties that replicate the decision process of experienced clinicians performing visual analysis. Spectral power changes from audio stimulation were concentrated in the [Formula: see text] band, whereas peripheral stimulation elicited an increase in spectral power across multiple bands, and nostril stimulation changed the entropy of the [Formula: see text] band. The findings of this pilot study on [Formula: see text]-score lay a foundation for a future prediction tool with clinical applications.

摘要

客观评估体外膜肺氧合 (ECMO) 支持下昏迷患者大脑的反应能力对临床护理至关重要,但目前的方法受到主观方法和评分者间差异的限制。定量脑电图 (EEG) 算法可能有助于临床医生提高诊断准确性。我们开发了一种基于刺激的定量 EEG 反应性算法,以评估 ECMO 支持下昏迷患者的 EEG 反应性特征。患者接受了递增强度的刺激方案(听觉、外周和鼻腔刺激)。从 24 名接受 ECMO 支持的昏迷患者(年龄 [Formula: see text],10 名女性,14 名男性)中收集了 129 个 20 秒 EEG 片段,格拉斯哥昏迷评分 [Formula: see text]8。使用五个频带([Formula: see text]、[Formula: see text]、[Formula: see text]、[Formula: see text]、[Formula: see text])的聚合谱功率和排列熵为每个 EEG 片段计算 EEG 反应性评分 ([Formula: see text]-scores)。应用参数估计技术对 [Formula: see text]-scores 进行分析,以识别出复制经验丰富的临床医生进行视觉分析的决策过程的属性。听觉刺激引起的谱功率变化集中在 [Formula: see text] 频段,而外周刺激引起多个频段的谱功率增加,鼻腔刺激改变了 [Formula: see text] 频段的熵。该 [Formula: see text]-score 初步研究结果为具有临床应用的未来预测工具奠定了基础。

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