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通过基于脑电图(EEG)的频谱熵评估右美托咪定诱导镇静的深度。

Assessing the depth of dexmedetomidine-induced sedation with electroencephalogram (EEG)-based spectral entropy.

作者信息

Maksimow A, Snapir A, Särkelä M, Kentala E, Koskenvuo J, Posti J, Jääskeläinen S K, Hinkka-Yli-Salomäki S, Scheinin M, Scheinin H

机构信息

Turku PET Centre, University of Turku, Turku, Finland.

出版信息

Acta Anaesthesiol Scand. 2007 Jan;51(1):22-30. doi: 10.1111/j.1399-6576.2006.01174.x. Epub 2006 Nov 1.

Abstract

BACKGROUND

Adequate sedation of critically ill patients improves the outcome of intensive care. Maintaining an optimal level of sedation in the intensive care unit (ICU) is difficult because of a lack of appropriate monitoring methods to guide drug dosing. Dexmedetomidine, a selective alpha(2)-adrenoceptor agonist, has recently been introduced for the sedation of ICU patients. This study investigated the utility of electroencephalogram (EEG)-based spectral entropy monitoring (with M-ENTROPY, GE Healthcare, Helsinki, Finland) for the assessment of dexmedetomidine-induced sedation.

METHODS

Eleven healthy, non-smoking men, aged 23.9 +/- 2.5 years (mean +/- standard deviation), were recruited. Spectral entropy was recorded before and during low (0.5 ng/ml) and high (5 ng/ml) plasma concentrations of dexmedetomidine. At the end of the infusion, subjects were awakened by verbal command and light shaking.

RESULTS

Spectral entropy decreased from 84 +/- 5 to 66 +/- 16 (P= 0.029) during low dexmedetomidine levels and from 84 +/- 5 to 20 +/- 12 (P < 0.001) during high dexmedetomidine levels. Transitions during loss and regaining of consciousness were analysed separately. Entropy decreased from 76 +/- 8 before to 43 +/- 10 (P < 0.001) after loss of consciousness, and increased from 14 +/- 4 to 63 +/- 13 (P < 0.001) on regaining of consciousness. These changes were consistent across all subjects. Prediction probability and sensitivity values indicated a high predictive performance of the method.

CONCLUSION

The depth of dexmedetomidine-induced sedation can be monitored with EEG-based spectral entropy. These results should be confirmed in a clinical setting.

摘要

背景

对重症患者进行充分镇静可改善重症监护的预后。由于缺乏指导药物剂量的合适监测方法,在重症监护病房(ICU)维持最佳镇静水平具有一定难度。右美托咪定是一种选择性α₂肾上腺素能受体激动剂,最近已被用于ICU患者的镇静。本研究探讨了基于脑电图(EEG)的频谱熵监测(使用芬兰赫尔辛基通用电气医疗集团的M-ENTROPY)在评估右美托咪定诱导镇静方面的效用。

方法

招募了11名健康、不吸烟的男性,年龄为23.9±2.5岁(均值±标准差)。在右美托咪定血浆浓度低(0.5 ng/ml)和高(5 ng/ml)时,记录频谱熵。输注结束时,通过口头指令和轻轻摇晃唤醒受试者。

结果

在低右美托咪定水平时,频谱熵从84±5降至66±16(P = 0.029),在高右美托咪定水平时,从84±5降至20±12(P < 0.001)。分别分析意识丧失和恢复过程中的转变。意识丧失前熵从76±8降至意识丧失后43±10(P < 0.001),意识恢复时从14±4升至63±13(P < 0.001)。所有受试者的这些变化均一致。预测概率和敏感度值表明该方法具有较高的预测性能。

结论

基于EEG的频谱熵可用于监测右美托咪定诱导的镇静深度。这些结果应在临床环境中得到证实。

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