Relationship between Bispectral Index Values and Volatile Anesthetic Concentrations during the Maintenance Phase of Anesthesia in the B-Unaware Trial
Division of Cardiothoracic Anesthesiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA. Anesthesiology
(Impact Factor: 5.88).
12/2011; 115(6):1209-18. DOI: 10.1097/ALN.0b013e3182395dcb
Hypnotic depth during anesthesia affects electroencephalography waveforms and electroencephalogram-derived indices, such as the bispectral index (BIS). Titrating anesthetic administration against the BIS assumes reliable relationships between BIS values, electroencephalogram waveforms, and effect site concentration, beyond loss of responsiveness. Associations among BIS, end-tidal anesthetic concentrations (ETAC), and patient characteristics were examined during anesthetic maintenance, using B-Unaware trial data.
Pharmacokinetically stable ETAC epochs during intraoperative anesthetic maintenance were analyzed. A generalized estimating equation determined independent relationships among BIS, ETAC (in age-adjusted minimum alveolar concentration equivalents), patient characteristics, and 1-yr mortality. Further individual and population characteristics were explored graphically.
A total of 3,347,523 data points from 1,100 patients were analyzed over an ETAC range from 0.42 to 1.51 age-adjusted minimum alveolar concentration. A generalized estimating equation yielded a best predictive equation: BIS = 62.9-1.6 (if age younger than 60 yr) -1.6 (if female) -2.5 (if American Society of Anesthesiologists physical status more than 3) -2.6 (if deceased at 1 yr) -2.5 (if N2O was not used) -1.4 (if midazolam dose more than 2 mg) -1.3 (if opioid dose more than 50 morphine equivalents) -15.4 × age-adjusted minimum alveolar concentration. Although a population relationship between ETAC and BIS was apparent, interindividual variability in the strength and reliability of this relationship was large. Decreases in BIS with increasing ETAC were not reliably observed. Individual-patient linear regression yielded a median slope of -8 BIS/1 age-adjusted minimum alveolar concentration (interquartile range -30, 0) and a median correlation coefficient of -0.16 (interquartile range -0.031, -0.50).
Independent of pharmacokinetic confounding, BIS frequently correlates poorly with ETAC, is often insensitive to clinically significant changes in ETAC, and is vulnerable to interindividual variability. BIS is therefore incapable of finely guiding volatile anesthetic titration during anesthetic maintenance.
Available from: Kazuko Hayashi
- "Over the past several decades, various anesthesia monitors have been introduced into clinical practice and employed different electroencephalogram (EEG) indices as a means to assess the depth of anesthesia, such as bispectral analysis (BIS), auditory-evoked potential (AEP), cerebral state index (CSI) and spectral entropy. However, these anesthesia monitoring systems are sometimes inadequate in preventing perioperative awakening (Whitlock et al., 2011; Zanner et al., 2009; Pilge et al., 2006; Fritz et al., 2013; Avidan et al., 2011; Rehberg et al., 2008; Mashour et al., 2011). One possible reason for their insufficiencies is the time delay that inevitably occurs when calculating anesthesia depth. "
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The Poincaré plot is a two-dimensional state-space approach, where a timed signal is plotted against itself after a time delay, enabling determination of the dynamic nature of signals. Quantification of the Poincaré plot is a candidate for estimating anaesthesia-dependent changes in the electroencephalogram (EEG).
In 20 patients, at four different states of anesthesia (0.5%, 1%, 2% and 3% sevoflurane), frontal EEG signals (10 seconds) were used to construct Poincaré plots. The plot pattern was quantified by the standard deviation of the voltage dispersion along the line of identity (SD2), the standard deviation perpendicular to the line of identity (SD1) and their ratio (SD1/SD2), and compared using spectral EEG features.
A significant stepwise decrease in the SD1/SD2 ratio was observed with each stepwise increase in sevoflurane concentration (p < 0.001 for each). From 0.5% to 3% sevoflurane anesthesia, the ratio of relative β power to δ power (β / δ) was highly correlated with SD1/SD2 (R = 0.92).
The Poincaré plot of the frontal EEG can detect the significant changes in the depth of anesthesia induced by different sevoflurane concentrations.
The Poincaré plot is a useful technique for detecting the EEG changes induced by anesthesia.
Clinical Neurophysiology 06/2014; 126(2). DOI:10.1016/j.clinph.2014.04.019 · 3.10 Impact Factor
Available from: PubMed Central
- "Other trials, however, failed to show benefit of processed EEG-guided anesthesia. In a large trial of 1,100 patients and over 3.3 million data points, processed EEG failed to correlate with end-tidal anesthetic concentration and was insensitive to changes in end-tidal anesthetic concentration.61 Another large-scale prospective study of over 6,000 subjects comparing processed EEG-guided protocols and end-tidal anesthetic concentration-guided protocols for maintenance of anesthesia found no difference in the amount of anesthesia used or the rate of awareness between the groups.62 "
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ABSTRACT: Anesthesiologists are unique among most physicians in that they routinely use technology and medical devices to carry out their daily activities. Recently, there have been significant advances in medical technology. These advances have increased the number and utility of medical devices available to the anesthesiologist. There is little doubt that these new tools have improved the practice of anesthesia. Monitoring has become more comprehensive and less invasive, airway management has become easier, and placement of central venous catheters and regional nerve blockade has become faster and safer. This review focuses on key medical devices such as cardiovascular monitors, airway equipment, neuromonitoring tools, ultrasound, and target controlled drug delivery software and hardware. This review demonstrates how advances in these areas have improved the safety and efficacy of anesthesia and facilitate its administration. When applicable, indications and contraindications to the use of these novel devices will be explored as well as the controversies surrounding their use.
Medical Devices: Evidence and Research 03/2014; 7(1):45-53. DOI:10.2147/MDER.S43428
Available from: J. Farquhar
- "These monitors do not measure signs of consciousness but instead a pharmacodynamic effect of anesthetic drugs on the spontaneous EEG. Even worse, their ability to help titrating anesthetic drugs during general anesthesia has been questioned recently . We therefore propose a completely new paradigm to detect intraoperative awareness, based on movement-related BCIs. "
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ABSTRACT: During 0.1-0.2% of operations with general anesthesia, patients become aware during surgery. Unfortunately, pharmacologically paralyzed patients cannot seek attention by moving. Their attempted movements may however induce detectable EEG changes over the motor cortex. Here, methods from the area of movement-based brain-computer interfacing are proposed as a novel direction in anesthesia monitoring. Optimal settings for development of such a paradigm are studied to allow for a clinically feasible system. A classifier was trained on recorded EEG data of ten healthy non-anesthetized participants executing 3-second movement tasks. Extensive analysis was performed on this data to obtain an optimal EEG channel set and optimal features for use in a movement detection paradigm. EEG during movement could be distinguished from EEG during non-movement with very high accuracy. After a short calibration session, an average classification rate of 92% was obtained using nine EEG channels over the motor cortex, combined movement and post-movement signals, a frequency resolution of 4 Hz and a frequency range of 8-24 Hz. Using Monte Carlo simulation and a simple decision making paradigm, this translated into a probability of 99% of true positive movement detection within the first two and a half minutes after movement onset. A very low mean false positive rate of <0.01% was obtained. The current results corroborate the feasibility of detecting movement-related EEG signals, bearing in mind the clinical demands for use during surgery. Based on these results further clinical testing can be initiated.
PLoS ONE 09/2012; 7(9):e44336. DOI:10.1371/journal.pone.0044336 · 3.23 Impact Factor
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