【罂粟摘要】接受氙气和七氟烷全身麻醉的患者额叶脑电图频谱特征的比较

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接受氙气和七氟烷全身麻醉的患者额叶脑电图频谱特征的比较

贵州医科大学  麻醉与心脏电生理课题组

翻译：王璐   编辑：王婷婷  审校：曹莹

背景：麻醉深度监测通常用于接受氙气麻醉的患者。处理脑电图(EEG)麻醉深度监测在很大程度上依赖于额叶脑电图的频域分析，有证据表明麻醉下观察到的频谱特征在不同麻醉剂之间存在显著差异。手术过程中氙气麻醉的脑电图频谱特征以前没有被描述过。

方法：24名计划全身麻醉进行碎石术的参与者随机接受氙气麻醉或七氟醚麻醉。通过脑麻醉反应监测仪(BARM)获得每位参与者的额叶脑电图记录。22个脑电图记录适合分析:接受七氟醚的参与者有11个，接受氙气的参与者有11个。为每个参与者制作麻醉发作期间的频谱图。计算两个30秒脑电图的组水平谱分析:一个记录在清醒基线时，另一个记录在维持麻醉时。采用线性混合效应模型比较两组患者从基线到维持期间5个频带的变化。

结果：七氟醚参与者的频谱图显示，在维持麻醉期间，额波δ (0.5 - 4hz)、θ (4 - 8hz)和α (8 - 13hz)波段功率增加。相比之下，氙气参与者的光谱图并没有显示阿尔法能量的增加。线性混合效应模型的结果表明，这两种药物都与从基线到维持的δ功率显著增加有关。在两种药物之间观察到的这种增加的幅度没有显著差异。相比之下，与氙气麻醉相比，七氟醚麻醉在θ、α和β (13-30 Hz)波段的绝对功率明显更大。就相对功率而言，与七氟烷相比，氙气与δ功率的显著增加有关，而七氟烷与δ、α和β功率的相对增加有关。

结论：氙气麻醉和七氟烷麻醉均与δ功率的显著增加相关。七氟烷麻醉还与 θ、α 和 β 功率的增加相关，而氙气麻醉与 δ 波段功率的更大巩固相关。氙气麻醉和七氟烷麻醉与不同的光谱特征相关。这些发现表明，适当的麻醉深度监测可能需要开发针对麻醉剂的无意识光谱测量方法。

原始文献来源：Steven McGuigan,Lisbeth Evered,BrendanSilbert,etal. Comparison of the Spectral Features of the Frontal Electroencephalogram in Patients Receiving Xenon and Sevoflurane General Anesthesia[J].Anesthesia&Analgesia.2021;133(5):1269-1279.

Comparison of the Spectral Features of the Frontal Electroencephalogram in Patients Receiving Xenon and Sevoflurane General Anesthesia

Backgrand:Depth-of-anesthesia monitoring is often utilized for patients receiving xenon anesthesia. Processed electroencephalogram (EEG) depth-of-anesthesia monitoring relies to a significant extent on frequency domain analysis of the frontal EEG, and there is evidence that the spectral features observed under anesthesia vary significantly between anesthetic agents. The spectral features of the EEG during xenon anesthesia for a surgical procedure have not previously been described.

Methods: Twenty-four participants scheduled for general anesthesia for lithotripsy were randomized to receive either xenon anesthesia or sevoflurane anesthesia. Frontal EEG recordings were obtained from each participant via the Brain Anesthesia Response Monitor (BARM). Twenty-two EEG recordings were suitable for analysis: 11 in participants who received sevoflurane and 11 in participants who received xenon. Spectrograms for the duration of the anesthetic episode were produced for each participant. Group-level spectral analysis was calculated for two 30-second EEG epochs: one recorded at awake baseline and the other during maintenance anesthesia. A linear mixed-effects model was utilized to compare the changes in 5 frequency bands from baseline to maintenance between the 2 groups.

Results: The spectrograms of sevoflurane participants illustrate an increase in frontal delta (0.5–4 Hz), theta (4–8 Hz), and alpha (8–13 Hz) band power during maintenance anesthesia. In contrast, spectrograms of the xenon participants did not illustrate an increase in alpha power. The results of the linear mixed-effects model indicate that both agents were associated with a significant increase in delta power from baseline to maintenance. There was no significant difference in the magnitude of this increase observed between the agents. In contrast, sevoflurane anesthesia was associated with significantly greater absolute power in the theta, alpha, and beta (13–30 Hz) bands when compared to xenon. In terms of relative power, xenon was associated with a significant increase in delta power compared to sevoflurane, while sevoflurane was associated with greater increases in relative theta, alpha, and beta power.

Conclusion: Both xenon anesthesia and sevoflurane anesthesia were associated with significant increases in delta power. Sevoflurane anesthesia was also associated with increases in theta, alpha, and beta power, while xenon anesthesia was associated with greater consolidation of power in the delta band. Xenon anesthesia and sevoflurane anesthesia are associated with distinct spectral features. These findings suggest that appropriate depth-of-anesthesia monitoring may require the development of agent-specific spectral measures of unconsciousness

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