Kumar A, Anand S, Yaddanapudi L N
Central Scientific Instruments Organization, Chandigarh, India.
Acta Anaesthesiol Scand. 2006 Oct;50(9):1139-44. doi: 10.1111/j.1399-6576.2006.01137.x.
Most of the research efforts to monitor the depth of anaesthesia using the mid-latency auditory evoked potential (MLAEP) signal in humans are based on the detection of the amplitudes and latencies of the signal peaks. Attempts have also been made to combine different time-domain and frequency-domain parameters. A comparison of different parameters is required to identify those which best discriminate the awake state from the anaesthetized state.
Although the sensitivity of MLAEP signal peaks is appreciable in awake and light anaesthesia states, it is reduced considerably at the moderate anaesthesia level, rendering this method unsuitable for predicting the surgical stage of anaesthesia. To overcome this problem, a numerically derived quantity--the morphology index--was used which does not require location of the peaks of the signal, but, at the same time, reflects the changes in both the latency and amplitude of the peaks. AEPs were recorded in the hospital for 18 patients during various states, i.e. awake, induction, unconscious and after regaining consciousness from halothane anaesthesia. The peak latencies, amplitudes, morphology index and peak power frequency (PPF) were calculated.
The sensitivity and specificity of PPF (89% and 95%, respectively) were found to be better than those for Pa and Nb peak amplitudes, their latencies and the morphology index. In addition, PPF showed minimum inter-patient variation. The mean value (standard deviation) of this parameter was 26.9 (0.67) during the awake state, decreased to 17.1 (1.2) during the anaesthetized state, and increased again to 26.1 (0.93) when the patients regained full consciousness.
PPF is the best of the four studied MLAEP parameters for the clinical characterization of the anaesthetized state during surgery.
大多数利用人类中潜伏期听觉诱发电位（MLAEP）信号监测麻醉深度的研究工作都是基于对信号峰值的幅度和潜伏期的检测。也有人尝试将不同的时域和频域参数结合起来。需要对不同参数进行比较，以确定那些能最好地区分清醒状态和麻醉状态的参数。
尽管MLAEP信号峰值在清醒和浅麻醉状态下的敏感性相当可观，但在中度麻醉水平时会大幅降低，这使得该方法不适合预测手术麻醉阶段。为克服这一问题，使用了一个数值推导量——形态学指数，它不需要确定信号峰值的位置，但同时能反映峰值潜伏期和幅度的变化。在医院对18名患者在不同状态下，即清醒、诱导、无意识以及从氟烷麻醉中恢复意识后，记录听觉诱发电位。计算峰值潜伏期、幅度、形态学指数和峰值功率频率（PPF）。
发现PPF的敏感性和特异性（分别为89%和95%）优于Pa和Nb峰值幅度、其潜伏期以及形态学指数。此外，PPF显示出患者间的差异最小。该参数在清醒状态下的平均值（标准差）为26.9（0.67），在麻醉状态下降至17.1（1.2），当患者完全恢复意识时又升至26.1（0.93）。
对于手术期间麻醉状态的临床特征描述，PPF是所研究的四个MLAEP参数中最佳的。
