Comparison of auditory evoked potential parameters for predicting clinically anaesthetized state
Article first published online: 20 SEP 2006
2006 Acta Anaesthesiol Scand
Acta Anaesthesiologica Scandinavica
Volume 50, Issue 9, pages 1139–1144, October 2006
How to Cite
Kumar, A., Anand, S. and Yaddanapudi, L. N. (2006), Comparison of auditory evoked potential parameters for predicting clinically anaesthetized state. Acta Anaesthesiologica Scandinavica, 50: 1139–1144. doi: 10.1111/j.1399-6576.2006.01137.x
- Issue published online: 20 SEP 2006
- Article first published online: 20 SEP 2006
- Accepted for publication 18 June 2006
- auditory evoked potentials;
- depth of anaesthesia;
- peak latencies and amplitudes;
- peak power frequency
Background: 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.
Methods: 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.
Results: 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.
Conclusion: PPF is the best of the four studied MLAEP parameters for the clinical characterization of the anaesthetized state during surgery.