T Katoh1, A Suzuki, K Ikeda. 1. Department of Anesthesiology and Intensive Care, Hamamatsu University School of Medicine, Japan. tackatoh@hama-med.ac.jp
Abstract
BACKGROUND: The electroencephalogram (EEG) has been evaluated as a tool for measuring depth of anesthesia, but the use of the EEG monitoring is still controversial. The current study was designed to evaluate the accuracy of three EEG parameters and anesthetic concentration for predicting depth of sedation and anesthesia during sevoflurane anesthesia METHODS: One low and one high equilibrated concentration ranging from 0.2-1.8% were assigned randomly and administered consecutively to 69 patients. The bispectral index (BIS; version 3.2), 95% spectral edge frequency (SEF), and median power frequency (MPF) were obtained from a bipolar frontomastoid (Fp1-A1, Fp2-A2) montage using an EEG monitor. Sedation was assessed using the responsiveness portion of the observer's assessment of alertness-sedation scale. In the second phase of the study, the 47 patients who were scheduled to have skin incisions were observed for purposeful movement in response to skin incision at sevoflurane concentrations between 1.6% and 2.4%. The relation among BIS, 95% SEF, MPF, sevoflurane concentration, sedation score, and movement or no movement after skin incision, was determined. Prediction probability values for EEG parameters and sevoflurane concentration to predict depth of sedation and anesthesia were also calculated. RESULTS: The BIS and sevoflurane concentration correlated closely with the sedation score. Both 95% SEF and MPF changed significantly but biphasically with increasing sedation. The prediction probability values for BIS and sevoflurane concentration were 0.966 and 0.945, respectively, indicating a high predictive performance for depth of sedation. No EEG parameters predicted movement after skin incision better than chance alone. CONCLUSIONS: Parameters derived from EEG, such as BIS, and 95% SEF are reliable guides to the depth of sedation, but not to the adequacy of anesthesia level for preventing movement during sevoflurane anesthesia.
RCT Entities:
BACKGROUND: The electroencephalogram (EEG) has been evaluated as a tool for measuring depth of anesthesia, but the use of the EEG monitoring is still controversial. The current study was designed to evaluate the accuracy of three EEG parameters and anesthetic concentration for predicting depth of sedation and anesthesia during sevoflurane anesthesia METHODS: One low and one high equilibrated concentration ranging from 0.2-1.8% were assigned randomly and administered consecutively to 69 patients. The bispectral index (BIS; version 3.2), 95% spectral edge frequency (SEF), and median power frequency (MPF) were obtained from a bipolar frontomastoid (Fp1-A1, Fp2-A2) montage using an EEG monitor. Sedation was assessed using the responsiveness portion of the observer's assessment of alertness-sedation scale. In the second phase of the study, the 47 patients who were scheduled to have skin incisions were observed for purposeful movement in response to skin incision at sevoflurane concentrations between 1.6% and 2.4%. The relation among BIS, 95% SEF, MPF, sevoflurane concentration, sedation score, and movement or no movement after skin incision, was determined. Prediction probability values for EEG parameters and sevoflurane concentration to predict depth of sedation and anesthesia were also calculated. RESULTS: The BIS and sevoflurane concentration correlated closely with the sedation score. Both 95% SEF and MPF changed significantly but biphasically with increasing sedation. The prediction probability values for BIS and sevoflurane concentration were 0.966 and 0.945, respectively, indicating a high predictive performance for depth of sedation. No EEG parameters predicted movement after skin incision better than chance alone. CONCLUSIONS: Parameters derived from EEG, such as BIS, and 95% SEF are reliable guides to the depth of sedation, but not to the adequacy of anesthesia level for preventing movement during sevoflurane anesthesia.
Authors: Kristin K Sellers; Davis V Bennett; Axel Hutt; James H Williams; Flavio Fröhlich Journal: J Neurophysiol Date: 2015-04-01 Impact factor: 2.714
Authors: Heidi Yppärilä; Ikka Korhonen; Mika Tarvainen; Tadeusz Musialowicz; Stephan M Jakob; Juhani Partanen Journal: J Clin Monit Comput Date: 2004-06 Impact factor: 2.502