不同年龄阶段人群1.0MAC七氟烷全麻下原始脑电图波形的比较

不同年龄阶段人群1.0MAC七氟烷全麻下原始脑电图波形的比较(论文16000字)
背景：对全麻状态下人群的原始脑电图波形的分析仍然具有挑战性及局限性。麻醉药物通过直接影响中枢神经系统，从而引起意识变化。这些都是全身麻醉中常见的临床征象改变，而这些变化可以通过表面脑电活动来监测和分析，也就是脑电图（EEG）。原始脑电图在记录大脑皮层的自发电活动方面具有优势，它也可以用来测量大脑内神经元内的离子电流引起的电压波动。而在全身麻醉状态下，原始脑电图会受麻醉药物浓度及种类的影响。麻醉深度的变化会引起脑电波形的改变，镇静程度越深，脑电波抑制则越多。因此，通过调控镇静深度减少脑损害显得尤为重要。现代麻醉中，对麻醉深度的评估是麻醉医师的基本技能。EEG可以用于监测麻醉深度及脑电活动，比如双频指数监测系统(BIS)及M熵系统。这些监测仪器具有处理过的算法和软件，可以实时评估这些原始脑电波并提供标准数值。如BIS数值在40-60之间就表示充分的麻醉深度及意识消失状态。但是在婴幼儿中，麻醉深度监测仪器所提供的数值与麻醉深度并不具有可靠的相关性。最新研究显示，BIS监测并不适用于儿童麻醉深度评估。脑电数值计算方法适用于成人，当应用于儿童时则会造成临床实际判断的失误。原始脑电图可以提供许多可靠的信息，但许多麻醉医师并不知道如何观察和解释这些波型。实际上，原始脑电图监测及其分析可以提示全身麻醉期间的镇静和镇痛水平。这是基于原始脑电图信号的频率会随着麻醉深度的改变而发生变化的潜在特征。既往研究证明，不同麻醉药，如吸入麻醉药和静脉麻醉药，会引起原始脑电波形的改变。本次研究中，我们通过对全身麻醉下原始脑电波形进行详细的分析和评估，希望能对原始脑电波及脑电指数的研究有所启示。本研究分析数据为手术开始前，患者1.0 MAC的七氟醚全身麻醉下的原始脑电图数据。

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目的：观察在1.0 MAC的吸入七氟醚麻醉下原始脑电波的频率（α，θ，γ和δ），以及脑电波频率在不同年龄组中的差异。
方法：随机选择入组135名患者。通过伦理及签署知情同意，ASA I-II级，年龄0-80岁，择期行小手术患者。135名患者根据年龄分为6组：1月-1岁（婴儿组，组1）；1-3岁（幼儿组，组2）；3-6岁（学龄前组，组3）；6-18岁（学龄组，组4）；18-65岁（成年组，组5）；65-80岁（老年组，组6）。手术时间＜2小时，全身麻醉过程中，七氟烷作为唯一镇静药物，插管时复合舒芬太尼或芬太尼及肌肉松弛药物。诱导开始后及气管插管后开始收集数据。手术开始前，稳定七氟烷在1.0MAC，并维持10分钟，采集并分析数据，包括无创血压、心率、呼吸频率、氧饱和度、呼气末七氟烷浓度、脑电图及BIS数值。用USB采集并记录原始脑电波图，用于后续分析。比较不同年龄阶段人群1.0MAC七氟烷全麻下原始脑电图波频率（α，θ，γ和δ）的差异。
结果：120名患者可用于数据分析。所有患者均插管顺利，在原始脑电图采集记录的十分钟内患者血流动力学均保持稳定。1-6组平均BIS值分别为52.2 ± 12.7, 55.0 ± 8.0, 44.5 ± 7.3, 43.8 ± 7.3, 44.2 ± 6.2 and 49.1 ± 6.2(P<0.01)，有明显统计学差异。Bonferroni校正后显示，BIS数值在组3、组4、组5与组1之间存在显著统计学差异（P＜0.05），组3、组4、组5与组2之间也存在显著统计学差异（P＜0.05）。六组均可见θ波，均无α和β波。六组脑电波频率分别为6.0 (5.5-6.0), 6.0 (5.5-6.0), 6.0 (5.5-6.0), 6.0 (6.0-7.0), 6.3 (6.0-7.0) 和6.0 (5.1-6.0)（P＜0.01）.Dunn的多重比较检验仅显示第4组与第6组（P = 0.0279）和第5组与第6组（P = 0.0202）之间的统计学显着性。采用正演方法的多元线性回归分析显示，只有BIS值与脑电波频率有统计学相关性（R2 = 0.063，标准化系数= 0.25，P <0.01）。 [资料来源：Doc163.com]

结论：在脑电数值不准确时，原始脑电波提供麻醉深度的实时监测。观测原始脑电波形可为不同年龄阶段麻醉深度分析提供准确可靠的数据，为减少全麻脑损害提供帮助。

关键词：脑电图，MAC、七氟烷、年龄、监测、吸入麻醉药、BIS

English Abstract
Comparing raw EEG waves among different age patients under general anesthesia with 1.0 MAC sevoflurane
BACKGROUND: Analyzing the raw electroencephalography (EEG) waves during anesthesia is still challenging and has not been widely demonstrated. Anesthetic agents are known to act directly on central nervous system; hence, causing alterations of consciousness. These alterations are major clinical endpoints of general anesthesia and can be analyzed and monitored throughout recordings of surface brain electrical activity, called electroencephalography (EEG). Raw EEG is a powerful tool that refers to the recording of the brain's spontaneous electrical activity along the scalp and it can be used to measure voltage fluctuations which result from ionic current flowing within neurons found in the brain. Under general anesthesia, these fluctuations vary spontaneously depending on the concentration and the type of anesthetic used. Different depth of anesthesia generate altering EEG waveforms and the deeper the level of hypnosis, the more suppressed the EEG waves are. Thus, it has become increasingly important to manipulate the hypnotic level accordingly to prevent brain damage. In modern practice, the assessment of the depth of anesthesia is fundamental to the anesthesiologist. Depth of anesthesia and electrical brain activity can be monitored using EEG indices such as theBispectral index monitoring system and M-entropy. These monitors have processed algorithms and software to assess these raw EEG waves in real time and give a standard numeric value. A BIS value of 40-60 indicates sufficient depth of anesthesia without any awareness. However, these EEG monitors is not reliable in young children and infants as the depth of anesthesia does not correlate with the numerical value generated by the monitors’ algorithms. Recent studies have demonstrated that the BIS monitor is not appropriate in assessing the depth of anesthesia in children. The EEG algorithm has been generated for adults and when extrapolated to children, it provides misleading information about the actual level of anesthesia. The raw EEG, in turn is presented with reliable information but many anesthesiologists do not know how to observe and interpret these waves. The raw electroencephalography monitoring and its analysis can indicate hypnotic and analgesic levels during general anesthesia. However, these are based on the underlying changes in the features of the raw EEG signal as the frequencies vary with the level of anesthesia. It has been known that different anesthetic agents such as intravenous or volatile agents have altered raw EEG waveforms. Using raw EEG data, we present a detailed analysis and assessment of the waveforms present under general anesthesia in the hope of shedding some lights on the raw EEG waves and the EEG indices. This study was conducted before any surgical stimulus in different age patients undergoing minor electrivesurgery under general anesthesia with sevoflurane concentration of 1.0 MAC. [资料来源：Doc163.com]
OBJECTIVE:  The aim of this study was to observe which raw EEG wave frequencies (alpha, theta, gamma and delta) are manifested under inhaled sevoflurane anesthesia of 1.0 MAC and how their frequencies differ in different age groups.
METHODS: A sample of 135 healthy patients were randomly selected and included in this study. After obtaining ethical approval and written informed consent, 135 patients (ASA I and II), aged 0-80 years of either gender undergoing minor elective surgery were enrolled. The selected patients were divided into 6 groups according to their age, 1 month -1 year old (infant period, group 1), 1-3 years old (toddler period, group 2), 3-6 years old (preschool age period, group 3), 6-18 years old (school age period, group 4), 18-65 years old (adults, group 5) and 65-80 years old (the elderly,  group 6).  The surgeries lasted less than two hours each and were performed under general anesthesia using sevoflurane as the sole hypnotic agent followed by sufentanil or fentanyl and muscle relaxant to facilitate intubation.Data collections started after induction and tracheal intubation. Data related to non-invasive blood pressure, heart rate, respiration rate, oxygen saturation, end tidal sevoflurane, EEG and bispectral index (BIS) values were recorded and analyzed for the 10 min of maintenance anesthesia with sevoflurane. The raw EEG wave was recorded by means of a Universal Serial Bus (USB) which was later on analyzed and processed offline. The different EEG wave frequencies (alpha, delta, theta and gamma) for all age patients under inhaled sevoflurane anesthesia of 1.0 MAC were analyzed and compared.

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RESULTS:  A total of 120 patients were included in the data analysis. All procedures of tracheal intubations were performed successfully, and hemodynamics was kept constant throughout the 10 minutes of raw EEG analysis. The average BIS value among group 1 to group 6 was 52.2 ± 12.7, 55.0 ± 8.0, 44.5 ± 7.3, 43.8 ± 7.3, 44.2 ± 6.2 and 49.1 ± 6.2 respectively (P<0.01).BIS values were statistically significant among the 6 groups, P<0.01. Bonferroni correction showed statistical significance in the BIS values only between groups 3, 4, 5 vs. group 1(P<0.05) and groups 3, 4, 5 vs. group 2 (P<0.05).Theta power was observed in all the 6 groups and there was no α and β waves present. The median EEG frequency among group 1 to group 6 was 6.0 (5.5-6.0), 6.0 (5.5-6.0), 6.0 (5.5-6.0), 6.0 (6.0-7.0), 6.3 (6.0-7.0) and 6.0 (5.1-6.0) respectively (P<0.01). Dunn’s multiple comparisons test showed statistical significance only between group 4 vs. group 6 (P=0.0279) and group 5 vs. group 6 (P=0.0202).Multiple linear regression with forward methods showed that only BIS value was statistically correlated to EEG wave frequency (R2=0.063, Standardized Coefficients=0.25, P<0.01).

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CONCLUSION:  Raw EEG provides real time information about the actual depth of anesthesia when standard monitors provide misleading values. Observing the raw EEG waveforms provides accurate reliable data which can be used to assess the depth of anesthesia in different age and can reduce brain injury during general anesthesia.
KEYWORDS:  EEG waves, Minimum alveolar concentration, sevoflurane, age, monitoring, anesthetics inhalation, BIS.
Clinical trial registration.ClinicalTrials.gov: identifier: NCT03559504.

目录
English Abstract    2
Introduction    5
Materials and methods    9
Statistical analysis    11
Results    12
Analysis and Discussion    13
Conclusion    17
Literature review    18