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脑电图衍生参数在预测兔模型麻醉深度中的性能。

Performance of electroencephalogram-derived parameters in prediction of depth of anaesthesia in a rabbit model.

机构信息

Veterinary Sciences Department, Universidade de Trás-os-Montes e Alto Douro, Vila Real, Portugal.

出版信息

Br J Anaesth. 2011 Apr;106(4):540-7. doi: 10.1093/bja/aeq407. Epub 2011 Feb 3.

Abstract

BACKGROUND

The index of consciousness (IoC), the permutation entropy (PE), and the approximate entropy are recent EEG-derived indices of anaesthetic depth. In this study, a rabbit model under fentanyl and isoflurane anaesthesia was used to compare the performance of these indices and also the classic median and spectral edge frequency 95%.

METHODS

EEG recordings were obtained from six rabbits. Animals received fentanyl for premedication, followed by induction with propofol and maintenance with isoflurane. Anaesthetic depth was evaluated according to a clinical scale from 1 (awake) to 4 (surgical anaesthesia). Animals were submitted to surgical implantation of a small device in the lumbar muscles. A correction factor for the EEG suppression ratio was applied to the spectral parameters and to the PE. The correlation of the indices with the clinical scale of anaesthesia was analysed using prediction probability. Repeated-measures analysis of variance or its non-parametric equivalent was used to analyse the indices values at the study times and to compare their variability.

RESULTS

The IoC showed the best mean prediction probability value [0.94 (0.01)] followed by burst suppression-corrected PE [0.91(0.03)]. Both parameters also showed less variability than the others.

CONCLUSIONS

The IoC and PE are promising indices for anaesthetic depth monitoring. The PE might benefit from the application of a burst suppression correction at deeper stages of anaesthesia. The rabbit is useful as a translational research animal model for the validation of clinical indices.

摘要

背景

意识指数(IoC)、排列熵(PE)和近似熵是最近的脑电衍生麻醉深度指数。在这项研究中,使用芬太尼和异氟醚麻醉的兔模型比较了这些指数的性能,以及经典的中位数和频谱边缘频率 95%。

方法

从六只兔子中获取脑电记录。动物接受芬太尼进行术前用药,然后用异丙酚诱导,用异氟醚维持麻醉。根据从 1(清醒)到 4(手术麻醉)的临床量表评估麻醉深度。动物接受腰椎肌肉小型装置的手术植入。对频谱参数和 PE 应用 EEG 抑制比的校正因子。使用预测概率分析了与麻醉临床量表相关的指数。使用重复测量方差分析或其非参数等效方法分析了研究时间点的指数值,并比较了它们的变异性。

结果

IoC 显示出最佳的平均预测概率值[0.94(0.01)],其次是爆发抑制校正后的 PE[0.91(0.03)]。这两个参数的变异性也比其他参数小。

结论

IoC 和 PE 是有前途的麻醉深度监测指数。PE 可能受益于在麻醉深度更深的阶段应用爆发抑制校正。兔是验证临床指数的转化研究动物模型的有用模型。

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