The impact of acoustic stimulation on the AEP monitor/2 derived composite auditory evoked potential index under awake and anesthetized conditions

Quantitative Electrophysiological Evaluation of the Analgesic Efficacy of Two Lappaconitine Derivatives: A Window into Antinociceptive Drug Mechanisms

Quantitative evaluation of analgesic efficacy improves understanding of the antinociceptive mechanisms of new analgesics and provides important guidance for their development. Lappaconitine (LA), a potent analgesic drug extracted from the root of natural Aconitum species, has been clinically used for years because of its effective analgesic and non-addictive properties. However, being limited to ethological experiments, previous studies have mainly investigated the analgesic effect of LA at the behavioral level, and the associated antinociceptive mechanisms are still unclear. In this study, electrocorticogram (ECoG) technology was used to investigate the analgesic effects of two homologous derivatives of LA, Lappaconitine hydrobromide (LAH) and Lappaconitine trifluoroacetate (LAF), on Sprague-Dawley rats subjected to nociceptive laser stimuli, and to further explore their antinociceptive mechanisms. We found that both LAH and LAF were effective in reducing pain, as manifested in the remarkable reduction of nocifensive behaviors and laser-evoked potentials (LEPs) amplitudes (N2 and P2 waves, and gamma-band oscillations), and significantly prolonged latencies of the LEP-N2/P2. These changes in LEPs reflect the similar antinociceptive mechanism of LAF and LAH, i.e., inhibition of the fast signaling pathways. In addition, there were no changes in the auditory-evoked potential (AEP-N1 component) before and after LAF or LAH treatment, suggesting that neither drug had a central anesthetic effect. Importantly, compared with LAH, LAF was superior in its effects on the magnitudes of gamma-band oscillations and the resting-state spectra, which may be associated with their differences in the octanol/water partition coefficient, degree of dissociation, toxicity, and glycine receptor regulation. Altogether, jointly applying nociceptive laser stimuli and ECoG recordings in rats, we provide solid neural evidence for the analgesic efficacy and antinociceptive mechanisms of derivatives of LA.

The Raw and Processed Electroencephalogram as a Monitoring and Diagnostic Tool

In this narrative review, different aspects of electroencephalogram (EEG) monitoring during anesthesia are approached, with a special focus on cardiothoracic and vascular anesthesia, from the basic principles to more sophisticated diagnosis and monitoring utilities. The available processed EEG-derived indexes of the depth of the hypnotic component of anesthesia have well-defined limitations and usefulness. They prevent intraoperative awareness with recall in specific patient populations and under a specific anesthetic regimen. They prevent intraoperative overdose, and they shorten recovery times. They also help to avoid lengthy intraoperative periods of suppression activity, which are known to be deleterious in terms of outcome. Other than those available indexes, the huge amount of information contained in the EEG currently is being used only partially. Several other areas of interest regarding EEG during anesthesia have emerged in terms of anesthesia mechanisms elucidation, nociception monitoring, and diagnosis or prevention of brain insults.

Consciousness fluctuation during general anesthesia: a theoretical approach to anesthesia awareness and memory modulation

With anesthesia awareness as a model of study we debate the both fascinating and dangerous phenomenon called consciousness fluctuation that takes place during surgical anesthesia. In accordance with current scientific knowledge this paradox is the consequence of our limits in both precise knowledge of anesthesia mechanisms and our inability to accurately assess the level of anesthesia with brain monitoring. We also focus on the relationships between memory and anesthesia, as well as the possibility of interfering with memory during general anesthesia.

Mechanisms underlying brain monitoring during anesthesia: limitations, possible improvements, and perspectives

Currently, anesthesiologists use clinical parameters to directly measure the depth of anesthesia (DoA). This clinical standard of monitoring is often combined with brain monitoring for better assessment of the hypnotic component of anesthesia. Brain monitoring devices provide indices allowing for an immediate assessment of the impact of anesthetics on consciousness. However, questions remain regarding the mechanisms underpinning these indices of hypnosis. By briefly describing current knowledge of the brain's electrical activity during general anesthesia, as well as the operating principles of DoA monitors, the aim of this work is to simplify our understanding of the mathematical processes that allow for translation of complex patterns of brain electrical activity into dimensionless indices. This is a challenging task because mathematical concepts appear remote from clinical practice. Moreover, most DoA algorithms are proprietary algorithms and the difficulty of exploring the inner workings of mathematical models represents an obstacle to accurate simplification. The limitations of current DoA monitors — and the possibility for improvement — as well as perspectives on brain monitoring derived from recent research on corticocortical connectivity and communication are also discussed.

Composite auditory evoked potentials index is not a good indicator of depth of anesthesia in propofol-fentanyl anesthesia: Randomized comparative study

Background:

The composite auditory evoked potentials index (cAAI) was considered a measure of overall balance between noxious stimulation, analgesia, and hypnosis; while bispectral index (BIS) shows only hypnosis, and auditory evoked potentials index (AAI) shows response to stimuli. The present study compared the performance of cAAI, BIS, and AAI in propofol-fentanyl anesthesia.

Materials and Methods:

Forty-five patients for abdominal surgery aged 30-65 years with ASA physical status I or II were randomly divided into three groups by an envelope method. Anesthesia was induced with midazolam, propofol, and fentanyl alongwith an epidural block. When hemodynamics were stable during surgery, propofol infusion rate was fixed at 4 mg/kg/h for 10 min, then increased to 6 mg/kg/h and kept it for 10 min. AAI (AEP version 1.4), cAAI (AEP version 1.6), or BIS (A-2000) was monitored in each 15 patients, and the performance of three indices was compared.

Results:

All three indices decreased significantly before intubation. Only the AAI increased significantly by intubation. During anesthesia except for at propofol 6 mg/kg/h, the cAAI was significantly higher than the AAI. Only the AAI was significantly lower at propofol 6 mg/kg/h than at 4 mg/kg/h. The cAAI had the largest and AAI had the smallest inter-individual variations. The cAAI was higher than the manufacturer's recommended range of general anesthesia.

Conclusion:

In propofol-fentanyl anesthesia, AAI might be better to discriminate anesthetic depth than cAAI and BIS.

Composite-, plain-auditory evoked potentials index and bispectral index to measure the effects of sevoflurane

The composite auditory evoked potentials index (cAAI) uses both cortical electroencephalogram (EEG) and response to auditory stimuli, while the bispectral index (BIS) uses only the cortical EEG and auditory evoked potentials index (AAI) uses only response to auditory stimuli. We expected that the cAAI was more useful to monitor anesthetic effect of sevoflurane than the BIS and AAI. The present study compared the changes of cAAI, AAI, and BIS in different sevoflurane concentration. Forty-five adult patients were anesthetized with sevoflurane in 50 % nitrous oxide. AAI (AEP version 1.4), cAAI (AEP version 1.6), and BIS (A-2000) were compared (each 15 patients in AAI, cAAI, and BIS groups) before induction, just before and after intubation, at 10 min since sevoflurane was set to 1.0, 1.5 and 2.0 %, and after extubation. All three indices decreased significantly before intubation. The cAAI was significantly higher than the AAI at sevoflurane 1.0 and 1.5 %. The AAI and BIS were significantly lower at sevoflurane 2.0 % than those at sevoflurane 1.0 %, but the cAAI did not. The cAAI had the largest and AAI had the smallest inter-individual variation. In sevoflurane-nitrous oxide anesthesia, cAAI was inferior to AAI and BIS to discriminate different anesthetic effect. The cAAI had larger inter-individual variation than the AAI and BIS.

[Measurement of the depth of anaesthesia]

One of the most important mandates of the anaesthesiologist is to control the depth of anaesthesia. An unsolved problem is that a straight definition of the depth of anaesthesia does not exist. Concerning this it is rational to separate hypnosis from analgesia, from muscle relaxation and from block of cardiovascular reactions. Clinical surrogate parameters such as blood pressure and heart rate are not well-suited for a valid statement about the depth of hypnosis. To answer this question the brain has become the focus of interest as the target of anaesthesia. It is possible to visualize the brain's electrical activity from anelectroencephalogram (EEG). The validity of the spontaneous EEG as an anesthetic depth monitor is limited by the multiphasic activity, especially when anaesthesia is induced (excitation) and in deep anaesthesia (burst suppression). Recently, various commercial monitoring systems have been introduced to solve this problem. These monitoring systems use different interpretations of the EEG or auditory-evoked potentials (AEP). These derived and calculated variables have no pure physiological basis. For that reason a profound knowledge of the algorithms and a validation of the monitoring systems is an indispensable prerequisite prior to their routine clinical use. For the currently available monitoring systems various studies have been reported. At this time it is important to know that the actual available monitors can only value the sedation and not the other components of anaesthesia. For example, they cannot predict if a patient will react to a painful stimulus or not. In the future it would be desirable to develop parameters which allow an estimate of the other components of anaesthesia in addition to the presently available monitoring systems to estimate sedation and muscle relaxation. These could be sensoric-evoked potentials to estimate analgesia and AEPs for the detection of awareness.

AEP-monitor/2 derived, composite auditory evoked potential index (AAI-1.6) and bispectral index as predictors of sevoflurane concentration in children

BACKGROUND

Level of anesthesia may be predicted with the auditory evoked potential or with passive processed electroencephalogram (EEG) parameters. Some previous reports suggest the passive EEG does not reliably predict level of anesthesia in infants. The AAI-1.6 is a relatively new index derived from the AEP/2 monitor. It combines auditory evoked potentials and passive EEG parameters into a single index. This study aimed to assess the AAI-1.6 as a predictor of level of anesthesia in infants and children.

METHODS

Four infants aged less than 1 year, and five older children aged between 2 and 11 years were enrolled. They all had uniform sevoflurane anesthesia for cardiac catheterization. The AAI-1.6 and bispectral index (BIS) were recorded after achieving equilibrium at 1.5%, 2% and 2.5% sevoflurane, and immediately prior to awakening. The prediction coefficient (Pk) for BIS and AAI-1.6 was calculated and compared within each age group.

RESULTS

The Pk for the AAI-1.6 was low in both 0-1 and 2-11 years age groups. In the 2-12 years group, the Pk for BIS was significantly higher than the Pk for the AAI-1.6 (Pk for BIS: 0.89, Pk for AAI-1.6: 0.53, P < 0.01). In contrast in the 0-1 year age group there was no evidence for a difference between the Pk for BIS and the Pk for the AAI-1.6 (Pk for BIS: 0.74, Pk for AAI-1.6: 0.53, P = 0.25).

CONCLUSIONS

This preliminary study suggests AAI-1.6 is a poor predictor of sevoflurane concentration in infants and children.

Performance of AEP Monitor/2-derived composite index as an indicator for depth of sedation with midazolam and alfentanil during gastrointestinal endoscopy

BACKGROUND AND OBJECTIVE

The A-Line auditory evoked potential index (AAI) (AEP Monitor/2, Danmeter A/S, Odense, Denmark) is a newly developed composite parameter representing the degree of hypnosis. We conducted a prospective, observational study to explore the performance and validity of the AAI during conventional sedation for gastrointestinal (GI) endoscopy.

METHODS

Thirty adults of either sex, age <65, scheduled for combined oesophagogastroduodenoscopy (OGD) and colonoscopy under sedation with intravenous (i.v.) midazolam and alfentanil were enrolled. The sedative end-point was set at the Observer's Assessment of Alertness/Sedation (OAA/S) score less than 4. An AEP Monitor/2 was used in all patients. AAI, sedation scores, heart rate (HR), blood pressure (BP) and SPO2 were recorded every 2 min up to the end of the procedure. Receiver operator characteristic analysis was used to test validity and to select optimal sedation.

RESULTS

There was a significantly positive correlation between AAI and OAA/S scores (rho = 0.886; P < 0.001). The AAI also showed significant differences between subsequent levels of sedation scores (P < 0.001). AAI greater than 54 indicated fully awake or minimal sedation and values between 54 and 42 were suggestive of moderate sedation. Values between 42 and 34 were associated with moderate to deep sedation and readings below 34 were associated with deep sedation. The relative risk of SPO2 < 95% for OAA/S = 2 compared with 3 was 15.98 (95% confidence interval (CI): 3.94-64.81).

CONCLUSIONS

AAI is an effective tool for monitoring sedation during GI endoscopy induced by i.v. midazolam and alfentanil.

Depth of Anesthesia Monitoring

Depth-of-anesthesia monitoring with EEG or EEG combined with mLAER is becoming widely used in anesthesia practice. Evidence shows that this monitoring improves outcome by reducing the incidence of intra-operative awareness while reducing the average amount of anesthesia that is administered, resulting in faster wake-up and recovery, and perhaps reduced nausea and vomiting. As with any monitoring device, there are limitations in the use of the monitors and the anesthesiologist must be able to interpret the data accordingly. The limitations include the following. The currently available monitoring algorithms do not account for all anesthetic drugs, including ketamine, nitrous oxide and halothane. EMG and other high-frequency electrical artifacts are common and interfere with EEG interpretation. Data processing time produces a lag in the computation of the depth-of-anesthesia monitoring index. Frequently the EEG effects of anesthetic drugs are not good predictors of movement in response to a surgical stimulus because the main site of action for anesthetic drugs to prevent movement is the spinal cord. The use of depth-of-anesthesia monitoring in children is not as well understood as in adults. Several monitoring devices are commercially available. The BIS monitor is the most thoroughly studied and most widely used, but the amount of information about other monitors is growing. In the future, depth-of-anesthesia monitoring will probably help in further refining and better understanding the process of administering anesthesia.