近似熵和复杂度分析在麻醉深度监测中的应用

目的探讨麻醉药物作用下脑电非线性动力学特性的变化规律,以及应用近似熵和复杂度非线性指数实时监测手术中麻醉深度变化情况.方法 65名手术患者随机分为异氟醚、七氟醚、地氟醚（每组15例）和异丙酚组（20例）,对所有患者全身麻醉过程进行全程脑电监测,包括安静闭眼、麻醉诱导、手术中、复苏、觉醒过程,并利用近似熵和复杂度非线性指数进行了麻醉过程的实时监测.结果近似熵和复杂度非线性指数安静闭眼状态最高,并随诱导过程迅速降低,手术中保持低水平、相对稳定的数值,以后随复苏过程逐渐升高,最后在觉醒恢复较高水平.结论近似熵和复杂度非线性指数能够实时监测全麻过程中脑电活动的变化,准确反映麻醉深度.

Application of approximate entropy and complexity analysis in monitoring depth of anesthesia

Objective The present study was undertaken to investigate the properties of nonlinear dynamics of EEG and the changes in depth of anesthesia with real-time approximate entropy (ApEn) and complexity (Cx) nonlinear indexes monitoring during anesthesia. Methods EEG was recorded in 65 in-patients. They were randomly divided into 4 groups: isoflurane, sevoflurane, desflurane (n=15, respectively), and propofol intravenous anesthesia (n=20) groups. The EEG derived parameters ApEn and Cx non-linear indexes were calculated simultaneously during the whole operation including rest state with eyes closed, anesthetic induction, intraoperation, recovery, post-operation awaking. Results ApEn and Cx nonlinear indexes remained the highest during rest state. Both of them kept decreasing during anesthetic induction. They dropped to a relative lower value and leveled off in the intra-operation period. Both of them rose gradually during recovery period and returned to a high level in the post-operation awaking period (correspondingly, ApEn: 0.87, 0.78, 0.55, 0.64 and 0.83. Cx: 0.58, 0.54, 0.38, 0.46 and 0.57). Conclusions With ApEn and Cx non-linear indexes, changes in depth of anesthesia from EEG signal could be real-timely monitored and precisely measured. Nonlinear dynamic analysis might provide us with more information about consciousness and cognition during general anesthesia.