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TECHNOLOGY, COMPUTING, AND SIMULATION

The Discriminant Power of Simultaneous Monitoring of Spontaneous Electroencephalogram and Evoked Potentials as a Predictor of Different Clinical States of General Anesthesia

Christian Jeleazcov, MD^*, Gerhard Schneider, MD, Michael Daunderer, MD, Bertram Scheller, MD, Jürgen Schüttler, MD^*, and Helmut Schwilden, MD, PhD^*

From the *Department of Anesthesiology, Universität Erlangen-Nürnberg, Erlangen; Department of Anesthesiology, Technische Universität München; Department of Anesthesiology, Universität München, Munich; and Department of Anesthesiology, Universität Frankfurt am Main, Frankfurt am Main, Germany.

Address correspondence and reprint requests to Dr. Christian Jeleazcov, Department of Anesthesiology, Universität Erlangen-Nürnberg, Krankenhausstr. 12, 91054 Erlangen, Germany. Address e-mail to christian.jeleazcov{at}kfa.imed.uni-erlangen.de.

Spontaneous or evoked electrical brain activity is increasingly used to monitor general anesthesia. Previous studies investigated the variables from spontaneous electroencephalogram (EEG), acoustic (AEP), or somatosensory evoked potentials (SSEP). But, by monitoring them separately, the available information from simultaneous gathering could be missed. We investigated whether the combination of simultaneous information from EEG, AEP, and SSEP shows a more discriminant power to differentiate between anesthesia states than from information derived from each measurement alone. Therefore, we assessed changes of 30 EEG, 21 SSEP, and 29 AEP variables recorded from 59 patients during four clinical states of general anesthesia: "awake," "light anesthesia," "surgical anesthesia," and "deep surgical anesthesia." The single and combined discriminant powers of EEG, AEP, and SSEP variables as predictors of these states were investigated by discriminant analysis. EEG variables showed a higher discriminant power than AEP or SSEP variables: 85%, 46%, and 32% correctly classified cases, respectively. The frequency of correctly classified cases increased to 90% and 91% with information from EEG + AEP and EEG + AEP + SSEP, respectively. Thus, future anesthesia monitoring should consider combined information simultaneously distributed on different electrophysiological measurements, rather than single variables or their combination from EEG or AEP or SSEP.

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Anesthesia & Analgesia® is published for the International Anesthesia Research Society® by Lippincott Williams & Wilkins with the assistance of Stanford University Libraries' HighWire Press®. Copyright 2006 by the International Anesthesia Research Society. Online ISSN: 1526-7598   Print ISSN: 0003-2999