Middle latency auditory evoked potential anaesthesia correlates of consciousness: Practicality & constraints

The hypothesis of this study is that significant differentiation of consciousness (CO) and unconsciousness (UNCO) is possible, using individual ML+AEP (10-140 msec) latency measures, within the context of a practical routine clinical depth of anaesthesia monitoring device. We have assessed individual latency band measures of the middle-latency auditory evoked potential (ML+AEP) as candidates to measure depth of CO or UNCO amongst a group of anaesthetised surgical patients. We have also compared ML+AEP correlates with conventional auditory evoked potential (AEP) index and bispectral index (BIS). This study investigates amplitude measures, limits and the practicality of using a single EEG channel ML+AEP recording system. ML+AEP amplitude-related correlates were assessed against CO and UNCO events during anaesthesia. ML+AEP measures were computed for each of the following AEP component-related latency time bins (LTB): Na;15-25msec, Pa;25-35 msec, TP41;35-45 msec; Pb/P1;45-55 msec, N1;80-100 msec, <N1;0-80 msec, >N1;80-140 msec, and ML+AEP;0-140 msec. Twenty patients (aged 28-68 yrs) undergoing day surgery had their electroencephalography (EEG) monitored during binaural auditory stimulus presentation (6.8 clicks per second). The AEP grand mean waveform (AEP _gmw) was computed for each consecutive stimulus AEP event, by way of averaging the previous 256 AEPs. The mean and SD amplitude associated with each of the ML+AEP ranges were computed for the whole study period and also for the predetermined events 1 to 13 (CO:1;2;3;12;13 and UNCO:4-11). Results included BIS data, measures derived from the AEP_gmw across both the ML+AEP range (0-140 msec), and also individual LTB segments. For each respective AEP LTB the mean and SD for AEP power distribution (AEP_PD) and AEP Differential analysis (AEP_DA) was computed. Two-sample t-tests were performed in order to test the hypothesis that AEP_DA and AEP _pA indices measured across ML+AEP LTB (during surgical procedure) present significant differences between CO and UNCO. Significant (P<0.05) values were derived for all computed AEP LTB correlates, and also for all AEP_PD LTB except Pa, TP41 and N1. Overall the P-values resulting from the application of the AEP_DA method were much lower than those of the AEP_PD method. Conclusion: While the practical limitations and constraints of AEP-based anaesthesia monitoring cannot be overlooked, individual AEP component-related correlates and particularly those related to waveform deflection or AEP Differential analysis (AEP_DA) were shown to be candidates for depth of consciousness measures.