The Effect of Electroencephalographic Trajectory During Anesthesia Emergence on the Indices Monitoring the Hypnotic Component.

David P Obert,Robin Taetow,Stephan Kratzer,Falk von Dincklage,Paul S García,Gerhard Schneider,Matthias Kreuzer
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Abstract

BACKGROUND Postoperative neurocognitive disorders (PNDs) are frequent and serious complications that cause an enormous social and economic burden. A previous study demonstrated that certain electroencephalographic (EEG) patterns during emergence from general anesthesia are associated with a higher risk for PND. Compared to patients demonstrating the most favorable trajectory (Traj Ref: delta-dominant slow-wave anesthesia (ddSWA)→spindle-dominant SWA (sdSWA)→non-SWA (nSWA)→wake), patients presenting Traj Abrupt (ddSWA→wake) had 4-fold increased odds to develop PND and patients with Traj High (nSWA→wake) had 8-fold increased odds of developing PND. We hypothesized that commonly used neuromonitoring devices (state entropy [SE], quantium consciousness index [qCON], bispectral index [BIS], and Patient State Index [PSI]) can differentiate between the various trajectories. METHODS From the original database of the study by Hesse et al, we analyzed 59 EEGs from patients emerging from general anesthesia. They were selected according to their trajectory. We included 19 patients who had shown the most favorable trajectory (Traj Ref), 20 who had demonstrated Traj Abrupt, and 20 who had followed Traj High. To evaluate the performance of the neuromonitoring devices, we replayed the patients' EEGs to the monitors using an EEG player. We compared the index values for the 3 different trajectories (Traj Ref, Traj Abrupt, and Traj High) generated by the different monitoring devices, respectively. Additionally, we evaluated the correlation between the monitoring devices. RESULTS SE and PSI were able to resolve significant differences between Traj Ref and Traj Abrupt during a major part of emergence. Traj Ref showed an almost linear increase of index values, whereas Traj Abrupt led to an episode of low index values followed by a sudden increase. However, when comparing Traj Ref vs Traj High, qCON, PSI, and BIS were the indices showing significant differences, especially at the beginning of emergence. Patients representing Traj Ref patterns had significantly lower index values than those depicting Traj High. Due to the Traj High cases starting in nSWA, their indices were already high at the start of emergence. CONCLUSIONS Our analysis revealed that the course of the different indices reflects spectral EEG patterns during the emergence from general anesthesia. Considering certain emergence trajectories associated with a higher risk of developing PND, our approach might enable the anesthetist to identify patients particularly susceptible to PND by observing the course of index values before admission to the postanesthesia care unit.
麻醉苏醒时脑电图轨迹对催眠成分监测指标的影响。
术后神经认知障碍(PNDs)是一种常见且严重的并发症,造成了巨大的社会和经济负担。先前的一项研究表明,全麻苏醒时的某些脑电图(EEG)模式与PND的高风险相关。与表现出最有利轨迹(Traj Ref: δ -显性慢波麻醉(ddSWA)→纺锤体显性SWA (sdSWA)→非SWA (nSWA)→清醒)的患者相比,Traj突变(ddSWA→清醒)的患者发生PND的几率增加了4倍,Traj高(nSWA→清醒)的患者发生PND的几率增加了8倍。我们假设常用的神经监测设备(状态熵[SE]、量子意识指数[qCON]、双谱指数[BIS]和患者状态指数[PSI])可以区分不同的轨迹。方法从Hesse等人研究的原始数据库中,我们分析了59例全身麻醉患者的脑电图。他们是根据他们的轨迹选择的。我们纳入了19名表现出最有利轨迹(Traj Ref)的患者,20名表现出Traj唐突的患者,20名表现出Traj High的患者。为了评估神经监测设备的性能,我们使用脑电图播放器将患者的脑电图重放到监视器上。我们分别比较了由不同监测设备产生的3种不同轨迹(Traj Ref、Traj唐突和Traj High)的指数值。此外,我们评估了监测设备之间的相关性。结果在出现的大部分时间内,se和PSI能够解决Traj Ref和Traj唐突之间的显著差异。Traj Ref表现为指标值几乎呈线性增长,而Traj唐突表现为指标值先低后骤上升。然而,当比较Traj Ref和Traj High时,qCON、PSI和BIS是显示显着差异的指标,特别是在出现之初。代表Traj Ref模式的患者的指数值明显低于Traj High模式的患者。由于Traj High病例始于nSWA,其指数在出现之初就已经很高。结论不同指标的变化过程反映了全麻苏醒时的脑电图谱。考虑到某些与PND发生风险较高相关的出现轨迹,我们的方法可能使麻醉师在进入麻醉后护理单元之前通过观察指标值的过程来识别特别容易发生PND的患者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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