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脑电图分析能否用于确定重症患者的镇静水平?

Can electroencephalographic analysis be used to determine sedation levels in critically ill patients?

作者信息

Roustan Jean-Paul, Valette Sarah, Aubas Pierre, Rondouin Gérard, Capdevila Xavier

机构信息

Department of Anesthesiology and Intensive Care Medicine, Neurologic Explorations Laboratory and Department of Biostatistics, Lapeyronie University hospital, Montpellier, France.

出版信息

Anesth Analg. 2005 Oct;101(4):1141-1151. doi: 10.1213/01.ane.0000167782.47957.e1.

DOI:10.1213/01.ane.0000167782.47957.e1
PMID:16192535
Abstract

UNLABELLED

Prolonged use of sedative drugs frequently leads to oversedation of intensive care patients. Clinical assessment scales are not reliable in deeply sedated patients. Parameters obtained from spectral and bispectral analysis of electroencephalogram (EEG) records have been combined to create an index (BIS) to monitor anesthesia depth. The role of such parameters in monitoring the depth of the sedation in intensive care unit (ICU) patients has yet to be determined. We designed the present prospective study to redefine and calculate available spectral and bispectral parameters from raw EEG records and estimate their clinical relevance for the diagnosis of under- or oversedation levels in ICU patients. Forty adult patients receiving continuous midazolam and morphine sedation were included. We obtained 167 clinical evaluations of sedation level using Ramsay and COMFORT scales along with an EEG record of 300 s. Six spectral parameters-relative power of 4 frequency bands (beta, alpha, Theta, and delta), 95th percentile of the power spectrum (SEF95), and 50th percentile of the power spectrum (SEF50) and four bispectral parameters, real triple product, bispectrum (Bispectrum), bicoherence, and ratio 10-were calculated. The relevance of each of these parameters and combinations in predicting too light (Ramsay 1 and 2) or deep (Ramsay 5 and 6) sedation levels was assessed. These calculations were performed before and after exclusion of the agitated patients, whose COMFORT 4 score was above 2. The most relevant parameters for predicting levels of deep sedation (Ramsay 5 and 6) were ratio 10 (area under the curve = 0.763; 95% confidence interval, 0.679-0.833) and SEF95 (area under the curve = 0.687; 95% confidence interval, 0.597-0.767). The most relevant parameters for predicting light levels of sedation (Ramsay 1 and 2) were also ratio 10 (area under the curve = 0.829; 95% confidence interval, 0.695-0.917) and SEF95 (area under the curve = 0.798; 95% confidence interval, 0.650-0.898). There is a modest improvement in relevance of their linear combination in predicting sedation level. Results were similar after exclusion of agitated patients. We conclude that various calculated EEG descriptive parameters exhibited large interindividual variability. There was a strong correlation between EEG spectral and bispectral parameters. Bispectral analysis slightly improves the predictive power of simple spectral analysis in distinguishing too light or deep sedation levels in ICU patients.

IMPLICATIONS

Spectral edge frequency 95 and Ratio 10 are the most relevant electroencephalogram (EEG) indexes for monitoring the level of sedation in intensive care unit patients but calculated EEG values exhibited large interindividual variability. Bispectral analysis of EEG provides a slight improvement over simple spectral analysis.

摘要

未标注

长期使用镇静药物常常导致重症监护患者过度镇静。临床评估量表在深度镇静患者中并不可靠。从脑电图(EEG)记录的频谱和双频谱分析中获得的参数已被整合以创建一个指数(脑电双频指数,BIS)来监测麻醉深度。此类参数在监测重症监护病房(ICU)患者镇静深度中的作用尚未确定。我们设计了本前瞻性研究,以从原始EEG记录中重新定义并计算可用的频谱和双频谱参数,并评估它们对诊断ICU患者镇静不足或过度镇静水平的临床相关性。纳入了40例接受持续咪达唑仑和吗啡镇静的成年患者。我们使用Ramsay和COMFORT量表对镇静水平进行了167次临床评估,并同时记录了300秒的EEG。计算了6个频谱参数——4个频段(β、α、θ和δ)的相对功率、功率谱的第95百分位数(SEF95)和功率谱的第50百分位数(SEF50),以及4个双频谱参数,即实三重积、双谱(双谱)、双相干和比值10。评估了这些参数及其组合在预测过浅(Ramsay 1和2级)或过深(Ramsay 5和6级)镇静水平方面的相关性。在排除躁动患者(其COMFORT 4评分高于2分)之前和之后进行了这些计算。预测深度镇静(Ramsay 5和6级)水平最相关的参数是比值10(曲线下面积 = 0.763;95%置信区间,0.679 - 0.833)和SEF95(曲线下面积 = 0.687;95%置信区间,0.597 - 0.767)。预测浅镇静水平(Ramsay 1和2级)最相关的参数也是比值10(曲线下面积 = 0.829;95%置信区间,0.695 - 0.917)和SEF95(曲线下面积 = 0.798;95%置信区间,0.650 - 0.898)。它们的线性组合在预测镇静水平方面的相关性有适度提高。排除躁动患者后结果相似。我们得出结论,各种计算出的EEG描述性参数表现出较大的个体间变异性。EEG频谱和双频谱参数之间存在很强的相关性。双频谱分析在区分ICU患者过浅或过深镇静水平方面比简单频谱分析的预测能力略有提高。

启示

频谱边缘频率95和比值10是监测重症监护病房患者镇静水平最相关的脑电图(EEG)指标,但计算出的EEG值表现出较大的个体间变异性。EEG的双频谱分析比简单频谱分析略有改进。

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