The Discriminant Power of Simultaneous Monitoring of Spontaneous Electroencephalogram and Evoked Potentials as a Predictor of Different Clinical States of General Anesthesia
Autor: | Bertram Scheller, Jürgen Schüttler, Christian Jeleazcov, M. Daunderer, Helmut Schwilden, Gerhard Schneider |
---|---|
Rok vydání: | 2006 |
Předmět: |
Male
Methyl Ethers Midazolam Anesthesia General Electroencephalography Remifentanil Sevoflurane Piperidines Evoked Potentials Somatosensory medicine Humans Prospective Studies Evoked potential Propofol Monitoring Physiologic Isoflurane medicine.diagnostic_test business.industry Brain Middle Aged Linear discriminant analysis Electrophysiology Anesthesiology and Pain Medicine Discriminant Somatosensory evoked potential Anesthesia Evoked Potentials Auditory Female Alfentanil business medicine.drug |
Zdroj: | Anesthesia & Analgesia. 103:894-901 |
ISSN: | 0003-2999 |
DOI: | 10.1213/01.ane.0000237231.73261.92 |
Popis: | 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. |
Databáze: | OpenAIRE |
Externí odkaz: |