Electroencephalographic characteristics of emergence from propofol/sufentanil total intravenous anesthesia

Effect of combinations of morphine, dexmedetomidine and maropitant on the electroencephalogram in response to acute electrical stimulation in anaesthetized dogs

This study was conducted to compare the efficacy of combinations of morphine, dexmedetomidine and maropitant in preventing the changes in electroencephalographic (EEG) indices of nociception in anaesthetized dogs subjected to a noxious electrical stimulus. In a crossover study, eight healthy adult dogs were randomly allocated to four groups: Mor: morphine 0.6 mg/kg; Dex + Mor: morphine 0.3 mg/kg + dexmedetomidine 5 μg/kg; Maro + Mor: morphine 0.3 mg/kg + maropitant 1 mg/kg; and Dex + Maro + Mor: morphine 0.2 mg/kg + dexmedetomidine 3 μg/kg + maropitant 0.7 mg/kg. Following intramuscular administration of test drugs in a minimal anaesthesia model, a supramaximal electrical stimulus (50 V at 50 Hz for 2 s) was applied and the EEG data were recorded. There were significant increases (p < .05) in the poststimulus median frequency (F50) only in groups Mor and Maro + Mor. Dex + Mor group had a significantly lower change in F50 and F95 compared to all other treatment groups. There was no correlation of the changes in EEG frequencies with blood plasma concentration of the drugs during and after noxious stimulation. Combination of dexmedetomidine and morphine was most effective in abolishing the changes in EEG indices in response to a noxious stimulus indicating a supra-additive interaction between these two drugs.

Electroencephalographic changes associated with antinociceptive actions of lidocaine, ketamine, meloxicam, and morphine administration in minimally anaesthetized dogs

Effects of ketamine and lidocaine on electroencephalographic (EEG) changes were evaluated in minimally anaesthetized dogs, subjected to electric stimulus. Six dogs were subjected to six treatments in a crossover design with a washout period of one week. Dogs were subjected to intravenous boluses of lidocaine 2 mg/kg, ketamine 3 mg/kg, meloxicam 0.2 mg/kg, morphine 0.2 mg/kg and loading doses of lidocaine 2 mg/kg followed by continuous rate infusion (CRI) of 50 and 100 mcg/kg/min, and ketamine 3 mg/kg followed by CRI of 10 and 50 mcg/kg/min. Electroencephalogram was recorded during electrical stimulation prior to any drug treatment (before treatment) and during electrical stimulation following treatment with the drugs (after treatment) under anaesthesia. Anaesthesia was induced with propofol and maintained with halothane at a stable concentration between 0.85 and 0.95%. Pretreatment median frequency was evidently increased (P < 0.05) for all treatment groups. Lidocaine, ketamine, and morphine depressed the median frequency resulting from the posttreatment stimulation. The depression of median frequency suggested evident antinociceptive effects of these treatments in dogs. It is therefore concluded that lidocaine and ketamine can be used in the analgesic protocol for the postoperative pain management in dogs.

Peak and averaged bicoherence for different EEG patterns during general anaesthesia

BACKGROUND

Changes in nonlinear neuronal mechanisms of EEG generation in the course of general anaesthesia have been extensively investigated in research literature. A number of EEG signal properties capable of tracking these changes have been reported and employed in anaesthetic depth monitors. The degree of phase coupling between different spectral components is a marker of nonlinear EEG generators and is claimed to be an important aspect of BIS. While bicoherence is the most direct measure of phase coupling, according to published research it is not directly used in the calculation of BIS, and only limited studies of its association with anaesthetic depth and level of consciousness have been published. This paper investigates bicoherence parameters across equal band and unequal band bifrequency regions, during different states of anaesthetic depth relating to routine clinical anaesthesia, as determined by visual inspection of EEG.

METHODS

41 subjects scheduled for day surgery under general anaesthesia were recruited into this study. EEG bicoherence was analysed using average and smoothed-peak estimates calculated over different regions on the bifrequency plane. Statistical analysis of associations between anaesthetic depth/state of consciousness and bicoherence estimates included linear regression using generalised linear mixed effects models (GLMs), ROC curves and prediction probability (Pk).

RESULTS

Bicoherence estimates for the δ_θ region on the bifrequency plane were more sensitive to anaesthetic depth changes compared to other bifrequency regions. Smoothed-peak bicoherence displayed stronger associations than average bicoherence. Excluding burst suppression and large transients, the δ_θ peak bicoherence was significantly associated with level of anaesthetic depth (z = 25.74, p < 0.001 and R2 = 0.191). Estimates of Pk for this parameter were 0.889(0.867-0.911) and 0.709(0.689-0.729) respectively for conscious states and anaesthetic depth levels (comparable BIS estimates were 0.928(0.905-0.950) and 0.801(0.786-0.816)). Estimates of linear regression and areas under ROC curves supported Pk findings. Bicoherence for eye movement artifacts were the most distinctive with respect to other EEG patterns (average |z| value 13.233).

CONCLUSIONS

This study quantified associations between deepening anaesthesia and increase in bicoherence for different frequency components and bicoherence estimates. Increase in bicoherence was also established for eye movement artifacts. While identified associations extend earlier findings of bicoherence changes with increases in anaesthetic drug concentration, results indicate that the unequal band bifrequency region, δ_θ, provides better predictive capabilities than equal band bifrequency regions.

A depth of anaesthesia index from linear regression of EEG parameters

OBJECTIVE

The field of Anaesthesia has recently witnessed numerous advances both in the drug administration and monitoring of anaesthetic state. This development has further boosted the efforts and interest of researchers in the automation of clinical Anaesthesia. The success in this direction is possible only when assessment of the depth of hypnotic component of anaesthesia is achieved accurately. This paper describes a technique to arrive at a reliable Depth of Hypnosis (DoH) index using electroencephalographic (EEG) parameters.

METHODS

EEG data from nine patients was recorded and processed to obtain a total of 21 EEG parameters. They were reduced to a set of best five parameters after applying graphical variance analysis which evaluates their power to discriminate between awake and unresponsive states. These five parameters were normalized with respect to awake state and used in a first order equation to give DoH index.

RESULTS

The value of computed DoH index varied from 0.37 to 0.58 for different patients during anesthetized state (awake value 1). For a single patient, the maximum variation in the index was observed as +/- 5% for different epochs at constant dose.

CONCLUSIONS

A combination of irregularity of EEG waveform in time-domain and band powers in frequency domain best describes the difference between awake and anesthetized states. To characterize these states, a set of optimum EEG parameters exists. These parameters must be normalized to reduce interpatient variability. The calculated graded index may be used to assist the anaesthetist in the operating theatre.

EEG complexity as a measure of depth of anesthesia for patients

A new approach for quantifying the relationship between brain activity patterns and depth of anesthesia (DOA) is presented by analyzing the spatio-temporal patterns in the electroencephalogram (EEG) using Lempel-Ziv complexity analysis. Twenty-seven patients undergoing vascular surgery were studied under general anesthesia with sevoflurane, isoflurane, propofol, or desflurane. The EEG was recorded continuously during the procedure and patients' anesthesia states were assessed according to the responsiveness component of the observer's assessment of alertness/sedation (OAA/S) score. An OAA/S score of zero or one was considered asleep and two or greater was considered awake. Complexity of the EEG was quantitatively estimated by the measure C(n), whose performance in discriminating awake and asleep states was analyzed by statistics for different anesthetic techniques and different patient populations. Compared with other measures, such as approximate entropy, spectral entropy, and median frequency, C(n) not only demonstrates better performance (93% accuracy) across all of the patients, but also is an easier algorithm to implement for real-time use. The study shows that C(n) is a very useful and promising EEG-derived parameter for characterizing the (DOA) under clinical situations.

Depth of anesthesia estimation and control

A fully automated system was developed for the depth of anesthesia estimation and control with the intravenous anesthetic, Propofol. The system determines the anesthesia depth by assessing the characteristics of the mid-latency auditory evoked potentials (MLAEP). The discrete time wavelet transformation was used for compacting the MLAEP which localizes the time and the frequency of the waveform. Feature reduction utilizing step discriminant analysis selected those wavelet coefficients which best distinguish the waveforms of those responders from the nonresponders. A total of four features chosen by such analysis coupled with the Propofol effect-site concentration were used to train a four-layer artificial neural network for classifying between the responders and the nonresponders. The Propofol is delivered by a mechanical syringe infusion pump controlled by Stanpump which also estimates the Propofol effect-site and plasma concentrations using a three-compartment pharmacokinetic model with the Tackley parameter set. In the animal experiments on dogs, the system achieved a 89.2% accuracy rate for classifying anesthesia depth. This result was further improved when running in real-time with a confidence level estimator which evaluates the reliability of each neural network output. The anesthesia level is adjusted by scheduled incrementation and a fuzzy-logic based controller which assesses the mean arterial pressure and/or the heart rate for decrementation as necessary. Various safety mechanisms are implemented to safeguard the patient from erratic controller actions caused by external disturbances. This system completed with a friendly interface has shown satisfactory performance in estimating and controlling the depth of anesthesia.

Clinical utility of EEG parameters to predict loss of consciousness and response to skin incision during total intravenous anaesthesia

We studied 30 female patients undergoing elective surgery, to assess the reliability of electroencephalogram spectral edge frequency and median frequency to predict loss of consciousness and movement in response to skin incision during total intravenous anaesthesia. Each patient received a different combination of propofol (1, 2, 3, 4, 5 or 6 micrograms.ml-1) and sufentanil (0.1, 0.2, 0.3, 0.5 or 1.0 ng.ml-1) target concentrations for induction of anaesthesia using target controlled infusions, assigned randomly. In a logistic regression model, spectral edge frequency was a significant determinant of both loss of consciousness (p = 0.0006) and movement to skin incision (p = 0.0044), whereas for median frequency no significant prediction model could be established. The probabilities of 50% and 95% no response for spectral edge frequency were 13.4 Hz and 6.8 Hz, respectively. The variability of the data limited the predictive value, so that spectral edge frequency was a poor predictor and median frequency was no predictor of response in the individual patient during total intravenous propofol/sufentanil anaesthesia.

Titration of propofol infusion using processed electroencephalogram during combined general and spinal anesthesia

PURPOSE

To determine the necessary mean infusion rate of propofol during combined nitrous oxide (N₂O) and propofol spinal anesthesia by using the processed electroencephalogram (pEEG).

METHODS

Twelve elective gynecological patients were monitored by a Dräger pEEG monitor under N₂O and propofol spinal anesthesia. To make it easier to detect an inadequate depth of anesthesia, muscle relaxants were not given and the patients breathed spontaneously through a laryngeal mask airway. Manual step-down infusion of propofol was employed to provide intraoperative hypnosis. Propofol infusion was titrated to maintain cardiorespiratory parameters within 20% of baseline and the 90th percentile of the spectral edge frequency (SEF 90) of the pEEG between 10 and 13.5 Hz.

RESULTS

The mean (SD) induction dose of propofol was 2.9 (0.4) mg·kg^-1. The mean (SD) maintenance infusion rate was 4.2 (0.5) mg·kg^-1·h^-1. The mean (SD) time from the end of propofol infusion to the opening of the patient's eyes was 5.4 (2.0) min. No gross movements or intraoperative awareness was recognized. The mean (SD) SEF 90 during the maintenance of anesthesia was 12.2 (1.5) Hz, which increased significantly to 16.2 (1.9) Hz at 1 min before the patients opened their eyes in reponse to verbal commands.

CONCLUSION

Titration of propofol infusion using SEF during combined general and spinal anesthesia provided a rapid recovery without any clinical signs of inadequate anesthesia.