Altered Frequency Distribution in the Electroencephalogram is Correlated to the Analgesic Effect of Remifentanil

The effect of sedation and time after cardiac arrest on coma outcome prognostication based on EEG power spectra

Early prognostication of long-term outcome of comatose patients after cardiac arrest remains challenging. Electroencephalography-based power spectra after cardiac arrest have been shown to help with the identification of patients with favourable outcome during the first day of coma. Here, we aim at comparing the power spectra prognostic value during the first and second day after coma onset following cardiac arrest and to investigate the impact of sedation on prognostication. In this cohort observational study, we included comatose patients (N = 91) after cardiac arrest for whom resting-state electroencephalography was collected on the first and second day after cardiac arrest in four Swiss hospitals. We evaluated whether the average power spectra values at 4.6-15.2 Hz were predictive of patients' outcome based on the best cerebral performance category score at 3 months, with scores ranging from 1 to 5 and dichotomized as favourable (1-2) and unfavourable (3-5). We assessed the effect of sedation and its interaction with the electroencephalography-based power spectra on patient outcome prediction through a generalized linear mixed model. Power spectra values provided 100% positive predictive value (95% confidence intervals: 0.81-1.00) on the first day of coma, with correctly predicted 18 out of 45 favourable outcome patients. On the second day, power spectra values were not predictive of patients' outcome (positive predictive value: 0.46, 95% confidence intervals: 0.19-0.75). On the first day, we did not find evidence of any significant contribution of sedative infusion rates to the patient outcome prediction (P > 0.05). Comatose patients' outcome prediction based on electroencephalographic power spectra is higher on the first compared with the second day after cardiac arrest. Sedation does not appear to impact patient outcome prediction.

Systematic Review of the Effectiveness of Machine Learning Algorithms for Classifying Pain Intensity, Phenotype or Treatment Outcomes Using Electroencephalogram Data

Recent attempts to utilize machine learning (ML) to predict pain-related outcomes from Electroencephalogram (EEG) data demonstrate promising results. The primary aim of this review was to evaluate the effectiveness of ML algorithms for predicting pain intensity, phenotypes or treatment response from EEG. Electronic databases MEDLINE, EMBASE, Web of Science, PsycINFO and The Cochrane Library were searched. A total of 44 eligible studies were identified, with 22 presenting attempts to predict pain intensity, 15 investigating the prediction of pain phenotypes and seven assessing the prediction of treatment response. A meta-analysis was not considered appropriate for this review due to heterogenos methods and reporting. Consequently, data were narratively synthesized. The results demonstrate that the best performing model of the individual studies allows for the prediction of pain intensity, phenotypes and treatment response with accuracies ranging between 62 to 100%, 57 to 99% and 65 to 95.24%, respectively. The results suggest that ML has the potential to effectively predict pain outcomes, which may eventually be used to assist clinical care. However, inadequate reporting and potential bias reduce confidence in the results. Future research should improve reporting standards and externally validate models to decrease bias, which would increase the feasibility of clinical translation. PERSPECTIVE: This systematic review explores the state-of-the-art machine learning methods for predicting pain intensity, phenotype or treatmentresponse from EEG data. Results suggest that machine learning may demonstrate clinical utility, pending further research and development. Areas for improvement, including standardized processing, reporting and the need for better methodological assessment tools, are discussed.

Effects of isoflurane, remifentanil and dexmedetomidine on selected EEG parameters derived from a Narcotrend Monitor before and after nociceptive stimulation at different MAC multiples in cats

Background

The aim of this prospective and complete cross-over study was to evaluate the effects of isoflurane, remifentanil and dexmedetomidine on EEG parameters derived from the Narcotrend® Monitor before and after nociceptive stimulation at different isoflurane MAC (minimal alveolar concentration) multiples. Seven adult European Domestic Short Hair cats were used. Each cat went through 3 experimental treatments. Group I received isoflurane, group IR received isoflurane and a constant rate infusion (CRI) of remifentanil (18 μg/kg/h IV), and group ID received isoflurane and a CRI of dexmedetomidine (3 μg/kg/h IV). The isoflurane MAC in each group was determined via supramaximal electrical stimulation. The EEG parameters were derived by a Narcotrend Monitor at specific time points before and after nociceptive stimulation at 0.75, 1.0 and 1.5 MAC.

The depth of anaesthesia was also assessed by a clinical score.

Results

The mean MAC sparing effects in group IR and group ID were 9.8 and 55.2%, respectively. The best correlation of EEG and MAC multiples was found for the Narcotrend Index (NI) in group I (r = − 0.67). The NI was also able to differentiate between 0.75 MAC and 1.5 MAC in group IR. Spectral edge frequency had a lower correlation with MAC multiples in group I (r = − 0.62) but was able to differentiate between 0.75 MAC and 1.5 MAC in groups I and IR, and between 1.0 MAC and 1.5 MAC in group IR. Narcotrend Index, SEF 95 and MF increased significantly after nociceptive stimulation at 1.0 MAC in group I, and SEF 95 increased significantly at 0.75 MAC in group ID. The clinical score correlated closer than any of the EEG parameters with MAC in all groups, with highest correlation values in group I (r = − 0.89). Noxious stimulation led to a significant increase of the clinical score at 0.75 MAC and 1.0 MAC in group I.

Conclusions

The EEG parameters derived from the Narcotrend Monitor show correlation to isoflurane MAC multiples in cats, but the anaesthetic protocol and especially the addition of dexmedetomidine have great influence on the reliability. The Narcotrend Monitor can be used as an additional tool to assess anesthetic depth in cats.

Differences in Characteristics of Error-Related Potentials Between Individuals With Spinal Cord Injury and Age- and Sex-Matched Able-Bodied Controls

Background: Non-invasive brain-computer interfaces (BCI) represent an emerging technology for enabling persons with impaired or lost grasping and reaching functions due to high spinal cord injury (SCI) to control assistive devices. A major drawback of BCIs is a high rate of false classifications. The robustness and performance of BCIs might be improved using cerebral electrophysiological correlates of error recognition (error-related potentials, ErrPs). As ErrPs have never been systematically examined in subjects with SCI, this study compares the characteristics of ErrPs in individuals with SCI with those of able-bodied control subjects. Methods: ErrPs at FCz and Cz were analyzed in 11 subjects with SCI (9 male, median age 28 y) and in 11 sex- and age-matched controls. Moving a shoulder joystick according to a visual cue, subjects received feedback about the match/mismatch of the performed movement. ErrPs occurring after "error"-feedback were evaluated by comparing means of voltage values within three consecutive time windows after feedback (wP1, wN1, wP2 containing peak voltages P1, N1, P2) using repeated-measurement analysis of variance. Results: In the control group, mean voltage values for the "error" and "correct" feedback condition differed significantly around N1 (FCz: 254 ms, Cz: 252 ms) and P2 (FCz: 347 ms, Cz: 345 ms), but not around P1 (FCz: 181 ms, Cz: 179 ms). ErrPs of the control and the SCI group showed similar morphology, however mean amplitudes of ErrPs were significantly smaller in individuals with SCI compared to controls for wN1 (FCz: control = -1.55 μV, SCI = -0.27 μV, p = 0.02; Cz: control = -1.03 μV, SCI = 0.11 μV, p = 0.04) and wP2 (FCz: control = 2.79 μV, SCI = 1.29 μV, p = 0.011; Cz: control = 2.12 μV, SCI = 0.81 μV, p = 0.003). Mean voltage values in wP1, wN1, and wP2 did not correlate significantly with either chronicity after or level of injury. Conclusion: The morphology of ErrPs in subjects with and without SCI is comparable, however, with reduced mean amplitude in wN1 and wP2 in the SCI group. Further studies should evaluate whether ErrP-classification can be used for online correction of false BCI-commands in individuals with SCI.

Objective methods for the assessment of the spinal and supraspinal effects of opioids

BACKGROUND AND PURPOSE

Opioids are potent analgesics. Opioids exert effects after interaction with opioid receptors. Opioid receptors are present in the peripheral- and central nervous system (CNS), but the analgesic effects are primarily mediated via receptors in the CNS. Objective methods for assessment of opioid effects may increase knowledge on the CNS processes responsible for analgesia. The aim of this review was to provide an overview of the most common objective methods for assessment of the spinal and supraspinal effects of opioids and discuss their advantages and limitations.

METHOD

The literature search was conducted in Pub Med (http://www.ncbi.nlm.nih.gov/pubmed) from November 2014 to June 2016, using free-text terms: "opioid", "morphine" and "oxycodone" combined with the terms "pupillometry," "magnetic resonance spectroscopy," "fMRI," "BOLD," "PET," "pharmaco-EEG", "electroencephalogram", "EEG," "evoked potentials," and "nociceptive reflex". Only original articles published in English were included.

RESULTS

For assessment of opioid effects at the supraspinal level, the following methods are evaluated: pupillometry, proton magnetic resonance spectroscopy, functional resonance magnetic imaging (fMRI), positron emission tomography (PET), spontaneous electroencephalogram (EEG) and evoked potentials (EPs). Pupillometry is a non-invasive tool used in research as well as in the clinical setting. Proton magnetic resonance spectroscopy has been used for the last decades and it is a non-invasive technique for measurement of in vivo brain metabolite concentrations. fMRI has been a widely used non-invasive method to estimate brain activity, where typically from the blood oxygen level-dependent (BOLD) signal. PET is a nuclear imaging technique based on tracing radio labeled molecules injected into the blood, where receptor distribution, density and activity in the brain can be visualized. Spontaneous EEG is typically quantified in frequency bands, power spectrum and spectral edge frequency. EPs are brain responses (assessed by EEG) to a predefined number of short phasic stimuli. EPs are quantified by their peak latencies and amplitudes, power spectrum, scalp topographies and brain source localization. For assessment of opioid effects at the spinal level, the following methods are evaluated: the nociceptive withdrawal reflex (NWR) and spinal EPs. The nociceptive withdrawal reflex can be recorded from all limbs, but it is standard to record the electromyography signal at the biceps femoris muscle after stimulation of the ipsilateral sural nerve; EPs can be recorded from the spinal cord and are typically recorded after stimulation of the median nerve at the wrist.

CONCLUSION AND IMPLICATIONS

The presented methods can all be used as objective methods for assessing the centrally mediated effects of opioids. Advantages and limitations should be considered before implementation in drug development, future experimental studies as well as in clinical settings. In conclusion, pupillometry is a sensitive measurement of opioid receptor activation in the CNS and from a practical and economical perspective it may be used as a biomarker for opioid effects in the CNS. However, if more detailed information is needed on opioid effects at different levels of the CNS, then EEG, fMRI, PET and NWR have the potential to be used. Finally, it is conceivable that information from different methods should be considered together for complementary information.

Feasibility of Non-invasive Brain Modulation for Management of Pain Related to Chemoradiotherapy in Patients with Advanced Head and Neck Cancer

Patients with head and neck cancer often experience a significant decrease in their quality of life during chemoradiotherapy (CRT) due to treatment-related pain, which is frequently classified as severe. Transcranial direct current stimulation (tDCS) is a method of non-invasive brain stimulation that has been frequently used in experimental and clinical pain studies. In this pilot study, we investigated the clinical impact and central mechanisms of twenty primary motor cortex (M1) stimulation sessions with tDCS during 7 weeks of CRT for head and neck cancer. From 48 patients screened, seven met the inclusion criteria and were enrolled. Electroencephalography (EEG) data were recorded before and after tDCS stimulation as well as across the trial to monitor short and long-term impact on brain function. The compliance rate during the long trial was extremely high (98.4%), and patients mostly reported mild side effects in line with the literature (e.g., tingling). Compared to a large standard of care study from our institution, our initial results indicate that M1-tDCS stimulation has a pain relief effect during the CRT that resulted in a significant attenuation of weight reduction and dysphagia normally observed in these patients. These results translated to our patient cohort not needing feeding tubes or IV fluids. Power spectra analysis of EEG data indicated significant changes in α, β, and γ bands immediately after tDCS stimulation and, in addition, α, δ, and θ bands over the long term in the seventh stimulation week (p < 0.05). The independent component EEG clustering analysis showed estimated functional brain regions including precuneus and superior frontal gyrus (SFG) in the seventh week of tDCS stimulation. These areas colocalize with our previous positron emission tomography (PET) study where there was activation in the endogenous μ-opioid system during M1-tDCS. This study provides preliminary evidence demonstrating the feasibility and safety of M1-tDCS as a potential adjuvant neuromechanism-driven analgesic therapy for head and neck cancer patients receiving CRT, inducing immediate and long-term changes in the cortical activity and clinical measures, with minimal side-effects.

Stochastic Pharmacokinetic-Pharmacodynamic Analysis of the Effect of Transdermal Buprenorphine on Electroencephalogram and Analgesia

BACKGROUND

The analgesic effect of opioids is often based on subjective one dimensional measurements. Electroencephalography (EEG) offers a possibility to objectively quantify the brain's activity before and after the administration of opioids. The aim of this study was to investigate the pharmacokinetic-pharmacodynamic (PKPD) properties of the buprenorphine transdermal patch on resting EEG and pain tolerance.

METHOD

Twenty-two healthy male subjects (mean age 23.1 ± 3.8 years) were studied. They received a 144-hour buprenorphine (20 μg/h) or placebo transdermal patch in this experimental, randomized, crossover, double-blind study. Skin heat pain tolerance was measured on the arm before the recordings of resting EEG. From the EEG, the ratio of slow and fast oscillations was calculated for further analysis. A population PKPD model with a stochastic differential equation for drug absorption from the patch was used to analyze the PK and PD data simultaneously by use of the statistical analysis package NONMEM.

RESULTS

Buprenorphine increased EEG ratio (P = 0.0006) and skin pain tolerance (P = 0.0008) compared with placebo. The stochastic model adequately characterized the concentration-time and effect-time courses for both the skin heat stimulation and the resting EEG outcomes with variations in the drug's absorption rate during the 144-hour treatment period. As measured by the potency parameter, the EEG effect was 10 ± 3 (median ± SE) times more sensitive to buprenorphine than the skin pain test.

CONCLUSIONS

Using a stochastic PKPD analysis, the effect of a 144-hour buprenorphine patch application on resting EEG and skin pain tolerance was quantified successfully. Both end points were affected by buprenorphine, although the resting EEG was more sensitive to buprenorphine. The stochastic PKPD analysis allowed the computation of a time-dependent variability in drug absorption from patch to blood. The data suggest that the resting EEG is an attractive and objective alternative for assessing opioid effect.

The Effect of Oral Morphine on Pain-Related Brain Activation - An Experimental Functional Magnetic Resonance Imaging Study

Knowledge about cerebral mechanisms underlying pain perception and effect of analgesic drugs is important for developing methods for diagnosis and treatment of pain. The aim was to explore altered brain activation before and after morphine treatment using functional magnetic resonance imaging recorded during experimental painful heat stimulation. Functional magnetic resonance imaging data were recorded and analysed in 20 healthy volunteers (13 men and 7 women, 24.9 ± 2.6 years) in a randomized, double-blind, placebo-controlled, cross-over study. Painful stimulations were applied to the right forearm using a contact heat evoked potential stimulator (CHEPS) before and after treatment with 30 mg oral morphine and placebo. CHEPS stimulations before treatment induced activation in the anterior cingulate cortex, secondary somatosensory cortex/insula, thalamus and cerebellum (n = 16, p < 0.05). In response to morphine treatment, the spatial extent of these pain-specific areas decreased (n = 20). Reduced pain-induced activation was seen in the right insula, anterior cingulate cortex and inferior parietal cortex after morphine treatment compared to before treatment (n = 16, p < 0.05), and sensory ratings of pain perception were significantly reduced after morphine treatment (p = 0.02). No effect on pain-induced brain activation was seen after placebo treatment compared to before treatment (n = 12, p > 0.05). In conclusion, heat stimulation activated areas in the 'pain matrix' and a clinically relevant dose of orally administered morphine revealed significant changes in brain areas where opioidergic pathways are predominant. The method may be useful to investigate the mechanisms of analgesics.