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Southern African Journal of Anaesthesia and Analgesia

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A comparison of EEG spectral entropy with conventional quantitative EEG at varying depths of sevoflurane anaesthesia

PR Bartel, FJ Smith, PJ Becker

Abstract


Background and Aim: Recently an electroencephalographic (EEG) spectral entropy module (M-ENTROPY) for an anaesthetic monitor has become commercially available. We compared its performance as an indicator of the state of anaesthesia with that of an older conventional quantitative EEG (QEEG) module (M-EEG) by the same manufacturer (Datex-Ohmeda Division, Instrumentarium Corp., Helsinki, Finland). Methods: There were 40 ASA class I or II subjects, aged between 16-60 years, who underwent elective abdominal surgery. EEG data were collected from the printouts of the respective modules. The data presented here were related to four levels of anaesthesia: Pre-anaesthetic wakefulness (state A), 2% sevoflurane endtidal (ET) concentration after completion of surgery (state B), low ET sevoflurane concentrations (~ 0.5%) just prior to regaining responsiveness (state C), and post-anaesthetic responsiveness (state D). Results: In terms of the prediction probability (Pk statistic), response entropy (RE) and state entropy (SE) produced higher values (0.95-1.0) than the best performing QEEG variable, frontal amplitude (0.86-0.95). Only RE scores did not overlap between states A and B or between B and D. The misclassification of subjects between states C and D was far lower for RE (28%) than for any of the conventional QEEG measures (>90%). Conclusion: In on-line monitoring spectral entropy is superior in distinguishing states of anaesthesia and is also easier to use than conventional QEEG. It is speculated that the artefact rejection strategies accorded spectral entropy might significantly benefit conventional QEEG analysis.

Key words: EEG spectral entropy, conventional QEEG, sevoflurane anaesthesia

Southern African Journal of Anaesthesia & Analgesia Vol. 11 (3) 2005: 89-93



http://dx.doi.org/10.1080/22201173.2005.10872405
AJOL African Journals Online