Continuing professional development module : An updated introduction to electroencephalogram-based brain monitoring during intended general anesthesia.

The electroencephalogram (EEG) provides a reliable reflection of the brain's electrical state, so it can reassure us that the anesthetic agents are actually reaching the patient's brain, and are having the desired effect. In most patients, the EEG changes somewhat predictably in response to propofol and volatile agents, so a frontal EEG channel can guide avoidance of insufficient and excessive administration of general anesthesia. Persistent alpha-spindles (around 10 Hz) phase-amplitude coupled with slow delta waves (around 1 Hz) are commonly seen during an "appropriate hypnotic state of general anesthesia". Such patterns can be appreciated from the EEG waveform or from the spectrogram (a colour-coded display of how the power in the various EEG frequencies changes with time). Nevertheless, there are exceptions to this. For example, administration of ketamine and nitrous oxide is generally not associated with the aforementioned alpha-spindle coupled with delta wave pattern. Also, some patients, including older adults and those with neurodegenerative disorders, are less predisposed to generate a strong electroencephalographic "alpha-spindle" pattern during general anesthesia. There might also be some rare instances when the frontal EEG shows a pattern suggestive of general anesthesia, while the patient has some awareness and is able to follow simple commands, albeit this is typically without obvious distress or memory formation. Thus, the frontal EEG alone, as currently analyzed, is an imperfect but clinically useful mirror, and more scientific insights will be needed before we can claim to have a reliable readout of brain "function" during general anesthesia.

RéSUMé: L'électroencéphalogramme (EEG) procure une image fiable de l'état électrique du cerveau, de telle sorte qu'il peut nous rassurer que les agents anesthésiques atteignent bien le cerveau du patient et ont l'effet désiré. Chez la plupart des patients, le tracé de l'EEG change de façon relativement prévisible en réponse au propofol et aux agents volatils; ainsi, une analyse d'EEG frontal peut prévenir l'administration insuffisante ou excessive d'anesthésique générale. Pendant « un état hypnotique adéquat de l'anesthésie générale ¼, on remarquera fréquemment une phase-amplitude de fuseaux alpha (alpha-spindles phase amplitude) (d'environ 10 Hz) couplée à des ondes lentes delta (d'environ 1 Hz). De tels tracés peuvent être observés à partir de l'EEG ou sur un spectrogramme (un affichage par code couleur de la façon dont la puissance dans les diverses fréquences d'EEG se modifie au fil du temps). Toutefois, il existe des exceptions. Par exemple, l'administration de kétamine et de protoxyde d'azote n'est généralement pas associée au tracé de fréquence alpha couplé à l'onde delta susmentionné. En outre, certains patients, notamment des personnes plus âgées et les personnes souffrant de maladies neurodégénératives, sont moins prédisposés à générer un fort tracé électroencéphalographique de 'fréquence alpha' pendant une anesthésie générale. Dans de rares cas, le tracé de l'EEG frontal pourrait évoquer une anesthésie générale alors que le patient est encore quelque peu conscient et capable de suivre des ordres simples, mais ces situations surviennent habituellement sans détresse ni rétention de mémoire évidente. Par conséquent, l'EEG frontal seul tel qu'il est analysé à l'heure actuelle est un miroir clinique utile mais imparfait, et des recherches scientifiques seront nécessaires avant de pouvoir affirmer que nous disposons d'une mesure fiable de la « fonction ¼ cérébrale pendant l'anesthésie générale.

Transient electroencephalographic alpha power loss during maintenance of general anaesthesia.

BACKGROUND: EEG activity in the extended alpha frequency range (7-17 Hz) during maintenance of general anaesthesia is primarily determined by effect-site concentrations of the hypnotic and analgesic drugs used. Intermittent alpha loss during surgery, unexplained by changes in anaesthetic or opioid concentrations, could represent arousal of the cortex as a result of increased surgical stimulation. METHODS: A generalised linear model was fitted to alpha power recorded from patients undergoing general anaesthesia from induction until waking using three explanatory variables: age-adjusted volatile anaesthetic effect-site concentration, and estimated effect-site propofol and opioid concentrations. Model residuals were decomposed into uncorrelated white noise and a fluctuating auto-correlated trend. Deviations of this local trend were classified as 'unexpected alpha dropout events'. To investigate whether these alpha dropouts might be explained by the effect of noxious stimulation, we related their occurrence to whether a patient was undergoing surgery involving the body cavity or not. RESULTS: Alpha power dropouts occurred in 73 of the 237 patients included in the final analysis (31%, median amplitude of -3.5 dB, duration=103 s). They showed a bimodal or broadly skewed distribution, being more probable soon after initial incision (32%), dropping to around 10% at 1 h, and then again increasing to >30% in operations lasting >3 h. Multivariate analysis showed that alpha dropouts were significantly associated with body cavity surgery (P=0.003) and with longer operations (P<0.001). CONCLUSIONS: A loss of alpha power, unexplained by changes in anaesthetic or opioid concentrations, is suggestive of thalamocortical depolarisation induced by body cavity noxious stimuli, and could provide a measure of nociception during surgery.

Electromyographic activation reveals cortical and sub-cortical dissociation during emergence from general anesthesia.

During emergence from anesthesia patients regain their muscle tone (EMG). In a typical population of surgical patients the actual volatile gas anesthetic concentrations in the brain (CeMAC) at which EMG activation occurs remains unknown, as is whether EMG activation at higher CeMACs is correlated with subsequent severe pain, or with cortical activation. Electroencephalographic (EEG) and EMG activity was recorded from the forehead of 273 patients emerging from general anesthesia following surgery. We determined CeMAC at time of EMG activation and at return of consciousness. Pain was assessed immediately after return of consciousness using an 11 point numerical rating scale. The onset of EMG activation during emergence was associated with neither discernible muscle movement nor with the presence of exogenous stimulation in half the patients. EMG activation could be modelled as two distinct processes; termed high- and low-CeMAC (occurring higher or lower than 0.07 CeMAC). Low-CeMAC activation was typically associated with simultaneous EMG activation and consciousness, and the presence of a laryngeal mask. In contrast, high-CeMAC EMG activation occurred independently of return of consciousness, and was not associated with severe post-operative pain, but was more common in the presence of an endotracheal tube. Patients emerging from general anesthesia with an endotracheal tube in place are more likely to have an EMG activation at higher CeMAC concentrations. These activations are not associated with subsequent high-pain, nor with cortical arousal, as evidenced by continuing delta waves in the EEG. Conversely, patients emerging from general anesthesia with a laryngeal mask demonstrate marked neural inertia-EMG activation occurs at a low CeMAC, and is closely temporally associated with return of consciousness.

Emergence EEG pattern classification in sevoflurane anesthesia.

OBJECTIVE: Significant spectral electroencephalogram (EEG) pattern characteristics exist in individual patients during the re-establishment of consciousness after general anesthesia. However, these EEG patterns cannot be quantitatively identified using commercially available depth of anesthesia (DoA) monitors. This study proposes an effective classification method and indices to classify these patterns among patients. APPROACH: Four types of emergence EEG patterns were identified based on the EEG data set from 52 patients undergoing sevoflurane general anesthesia from two hospitals. Then, the relative power spectrum density (RPSD) of five frequency sub-bands of clinical interest (delta, theta, alpha, beta and gamma) were selected for emergence state analysis. Finally, a genetic algorithm support vector machine (GA-SVM) was used to identify the emergence EEG patterns. The performance was reported in terms of sensitivity (SE), specificity (SP) and accuracy (AC). MAIN RESULTS: The combination of the mean and mode of RPSD in the delta and alpha band (P (delta)/P (alpha) performed the best in the GA-SVM classification. The AC indices obtained by GA-SVM across the four patterns were 90.64 ± 7.61, 81.79 ± 5.84, 82.14 ± 7.99 and 72.86 ± 11.11 respectively. Furthermore, the emergence time of the patients with EEG emergence patterns I and III increased as the patients' age increased. However, for patients with EEG emergence pattern IV, the emergence time positively correlates with the patients' age when they are under 50, and negatively correlates with it when they are over 50. SIGNIFICANCE: The mean and mode of P (delta)/P (alpha) is a useful index to classify the different emergence EEG patterns. In addition, these patterns may correlate with an underlying neural substrate which is related to the patients' age. Highlights ► Four emergence EEG patterns were found in γ-amino-butyric acid (GABA)-ergic anesthetic drugs. ► A genetic algorithm combined with a support vector machine (GA-SVM) was proposed to identify the emergence EEG patterns. ► The relative power spectrum density (RPSD) was used as a feature to classify the emergence EEG patterns and good accuracy was achieved. ► The statistics shows that the emergence EEG patterns are age-related and may have value in assessing postoperative brain states.

Inattentive Delirium vs. Disorganized Thinking: A New Axis to Subcategorize PACU Delirium.

Background: Assessment of patients for delirium in the Post Anesthesia Care Unit (PACU) is confounded by the residual effects of the varied anesthetic and analgesic regimens employed during surgery and by the physiological consequences of surgery such as pain. Nevertheless, delirium diagnosed at this early stage has been associated with adverse clinical outcomes. The last decade has seen the emergence of the confusion assessment method-intensive care unit (CAM-ICU) score as a quick practical method of detecting delirium in clinical situations. Nonetheless, this tool has not been specifically designed for use in this immediate postoperative setting. Methods: Patients enrolled in a larger observational study were administered the CAM-ICU delirium screening tool 15 min after the latter of return of responsiveness to command or arrival in the post-anesthesia care unit. Numerical pain rating scores were also recorded. In addition, we reviewed additional behavioral observations suggestive of disordered thinking, such as hallucinations, a non-reactive eyes-open state, or an inability to state a pain score. Results: Two-hundred and twenty-nine patients underwent CAM-ICU testing in PACU. 33 patients (14%) were diagnosed with delirium according to CAM-ICU criteria; 25 of these were inattentive with low arousal, seven were inattentive with high arousal, and one was inattentive and calm and with disordered thinking. Using our extended criteria an additional eleven patients showed signs of disordered thinking. CAM-ICU delirium was associated with increased length of operation (p = 0.028), but a positive CAM-PACU designation was associated with both increased operation length and age (p = 0.003 and 0.010 respectively). Two of the CAM-ICU positive patients with inattention and high arousal reported high pain scores and were not classified as CAM-PACU positive. Conclusion: Disordered thinking is correlated with older patients and longer operations. The sensitivity of the existing CAM-ICU score in diagnosing delirium or disordered thinking in PACU patients is improved by the inclusion of a few extra criteria, namely: patients having perceptual hallucinations, in an unreactive eyes-open state, or who cannot state a pain score. We present this alternative screening tool for use in the post-anesthetic period, which we have named CAM-PACU.

Emergence from general anesthesia and the sleep-manifold.

The electroencephalogram (EEG) during the re-establishment of consciousness after general anesthesia and surgery varies starkly between patients. Can the EEG during this emergence period provide a means of estimating the underlying biological processes underpinning the return of consciousness? Can we use a model to infer these biological processes from the EEG patterns? A frontal EEG was recorded from 84 patients. Ten patients were chosen for state-space analysis. Five showed archetypal emergences; which consisted of a progressive decrease in alpha power and increase peak alpha frequency before return of responsiveness. The five non-archetypal emergences showed almost no spectral EEG changes (even as the volatile general anesthetic decreased) and then an abrupt return of responsiveness. We used Bayesian methods to estimate the likelihood of an EEG pattern corresponding to the position of the patient on a 2-dimensional manifold in a state space of excitatory connection strength vs. change in intrinsic resting neuronal membrane conductivity. We could thus visualize the trajectory of each patient in the state-space during their emergence period. The patients who followed an archetypal emergence displayed a very consistent pattern; consisting of progressive increase in conductivity, and a temporary period of increased connection strength before return of responsiveness. The non-archetypal emergence trajectories remained fixed in a region of phase space characterized by a relatively high conductivity and low connection strength throughout emergence. This unexpected progressive increase in conductivity during archetypal emergence may be due to an abating of the surgical stimulus during this period. Periods of high connection strength could represent forays into dissociated consciousness, but the model suggests all patients reposition near the fold in the state space to take advantage of bi-stable cortical dynamics before transitioning to consciousness.