Using EEG markers to make inferences about anaesthetic-induced altered states of arousal

Electroencephalographic spectrogram-guided total intravenous anesthesia using dexmedetomidine and propofol prevents unnecessary anesthetic dosing during craniotomy: a propensity score-matched analysis

BACKGROUND

The bispectral index (BIS) may be unreliable to gauge anesthetic depth when dexmedetomidine is administered. By comparison, the electroencephalogram (EEG) spectrogram enables the visualization of the brain response during anesthesia and may prevent unnecessary anesthetic consumption.

METHODS

This retrospective study included 140 adult patients undergoing elective craniotomy who received total intravenous anesthesia using a combination of propofol and dexmedetomidine infusions. Patients were equally matched to the spectrogram group (maintaining the robust EEG alpha power during surgery) or the index group (maintaining the BIS score between 40 and 60 during surgery) based on the propensity score of age and surgical type. The primary outcome was the propofol dose. Secondary outcome was the postoperative neurological profile.

RESULTS

Patients in the spectrogram group received significantly less propofol (1585 ± 581 vs. 2314 ± 810 mg, P < 0.001). Fewer patients in the spectrogram group exhibited delayed emergence (1.4% vs. 11.4%, P = 0.033). The postoperative delirium profile was similar between the groups (profile P = 0.227). Patients in the spectrogram group exhibited better in-hospital Barthel's index scores changes (admission state: 83.6 ± 27.6 vs. 91.6 ± 17.1; discharge state: 86.4 ± 24.3 vs. 85.1 ± 21.5; group-time interaction P = 0.008). However, the incidence of postoperative neurological complications was similar between the groups.

CONCLUSIONS

EEG spectrogram-guided anesthesia prevents unnecessary anesthetic consumption during elective craniotomy. This may also prevent delayed emergence and improve postoperative Barthel index scores.

Phase-amplitude coupling during maintenance of general anaesthesia: towards a better understanding of anaesthetic-induced brain dynamics in children

Electroencephalogram signatures associated with anaesthetic-induced loss of consciousness have been widely described in adult populations. A recent study helps verify our understanding of brain dynamics induced by anaesthetics in a paediatric population by describing a specific pattern in terms of an interaction of the phase of delta oscillations and the amplitude of alpha oscillations. This feature has potential translational implications for optimising future monitoring technologies.

[Accidental Awareness during General Anaesthesia]

Accidental awareness during general anaesthesia (AAGA) is a rare but severe complication. The reported incidence of AAGA may depend on the assessment of intraoperative awareness with explicit recall and there are substantial variations between subspecialties and groups of patients. The majority of prospective studies using structured interviews reported an incidence of AAGA at 0.1-0.2% during general anaesthesia, however, higher values were observed in paediatric (0.2-1.2%) and obstetric patients (0.47%). Risk factors that predispose to AAGA are patient conditions, ASA status, female gender, patient age, history of AAGA, surgical procedure, anaesthetic drug type, muscle relaxation, dosages of hypnotic or analgesic drugs, monitoring and malfunction of anaesthesia systems. Preventive strategies include careful assessment of risk factors, avoidance of underdosages of hypnotics and analgetics during general anaesthesia and monitoring of depth of anaesthesia in risk patients. The health-related consequences can be serious and psychopharmacological and psychotherapeutic interventions are indicated in patients who have experienced AAGA.

State space methods for phase amplitude coupling analysis

Phase amplitude coupling (PAC) is thought to play a fundamental role in the dynamic coordination of brain circuits and systems. There are however growing concerns that existing methods for PAC analysis are prone to error and misinterpretation. Improper frequency band selection can render true PAC undetectable, while non-linearities or abrupt changes in the signal can produce spurious PAC. Current methods require large amounts of data and lack formal statistical inference tools. We describe here a novel approach for PAC analysis that substantially addresses these problems. We use a state space model to estimate the component oscillations, avoiding problems with frequency band selection, nonlinearities, and sharp signal transitions. We represent cross-frequency coupling in parametric and time-varying forms to further improve statistical efficiency and estimate the posterior distribution of the coupling parameters to derive their credible intervals. We demonstrate the method using simulated data, rat local field potentials (LFP) data, and human EEG data.

Biophysical Model: A Promising Method in the Study of the Mechanism of Propofol: A Narrative Review

The physiological and neuroregulatory mechanism of propofol is largely based on very limited knowledge. It is one of the important puzzling issues in anesthesiology and is of great value in both scientific and clinical fields. It is acknowledged that neural networks which are comprised of a number of neural circuits might be involved in the anesthetic mechanism. However, the mechanism of this hypothesis needs to be further elucidated. With the progress of artificial intelligence, it is more likely to solve this problem through using artificial neural networks to perform temporal waveform data analysis and to construct biophysical computational models. This review focuses on current knowledge regarding the anesthetic mechanism of propofol, an intravenous general anesthetic, by constructing biophysical computational models.

Developing a Real-Time Electroencephalogram-Guided Anesthesia-Management Curriculum for Educating Residents: A Single-Center Randomized Controlled Trial

BACKGROUND

Different anesthetic drugs and patient factors yield unique electroencephalogram (EEG) patterns. Yet, it is unclear how best to teach trainees to interpret EEG time series data and the corresponding spectral information for intraoperative anesthetic titration, or what effect this might have on outcomes.

METHODS

We developed an electronic learning curriculum (ELC) that covered EEG spectrogram interpretation and its use in anesthetic titration. Anesthesiology residents at a single academic center were randomized to receive this ELC and given spectrogram monitors for intraoperative use versus standard residency curriculum alone without intraoperative spectrogram monitors. We hypothesized that this intervention would result in lower inhaled anesthetic administration (measured by age-adjusted total minimal alveolar concentration [MAC] fraction and age-adjusted minimal alveolar concentration [aaMAC]) to patients ≥60 old during the postintervention period (the primary study outcome). To study this effect and to determine whether the 2 groups were administering similar anesthetic doses pre- versus postintervention, we compared aaMAC between control versus intervention group residents both before and after the intervention. To measure efficacy in the postintervention period, we included only those cases in the intervention group when the monitor was actually used. Multivariable linear mixed-effects modeling was performed for aaMAC fraction and hospital length of stay (LOS; a non-prespecified secondary outcome), with a random effect for individual resident. A multivariable linear mixed-effects model was also used in a sensitivity analysis to determine if there was a group (intervention versus control group) by time period (post- versus preintervention) interaction for aaMAC. Resident EEG knowledge difference (a prespecified secondary outcome) was compared with a 2-sided 2-group paired t test.

RESULTS

Postintervention, there was no significant aaMAC difference in patients cared for by the ELC group (n = 159 patients) versus control group (N = 325 patients; aaMAC difference = -0.03; 95% confidence interval [CI], -0.09 to 0.03; P =.32). In a multivariable mixed model, the interaction of time period (post- versus preintervention) and group (intervention versus control) led to a nonsignificant reduction of -0.05 aaMAC (95% CI, -0.11 to 0.01; P = .102). ELC group residents (N = 19) showed a greater increase in EEG knowledge test scores than control residents (N = 20) from before to after the ELC intervention (6-point increase; 95% CI, 3.50-8.88; P < .001). Patients cared for by the ELC group versus control group had a reduced hospital LOS (median, 2.48 vs 3.86 days, respectively; P = .024).

CONCLUSIONS

Although there was no effect on mean aaMAC, these results demonstrate that this EEG-ELC intervention increased resident knowledge and raise the possibility that it may reduce hospital LOS.

Using Electroencephalography (EEG) to Guide Propofol and Sevoflurane Dosing in Pediatric Anesthesia

Sevoflurane and propofol-based anesthetics are dosed according to vital signs, movement, and expired sevoflurane concentrations, which do not assess the anesthetic state of the brain and, therefore, risk underdose and overdose. Electroencephalography (EEG) measures cortical brain activity and can assess hypnotic depth, a key component of the anesthetic state. Application of sevoflurane and propofol pharmacology along with EEG parameters can more precisely guide dosing to achieve the desired anesthetic state for an individual pediatric patient. This article reviews the principles underlying EEG use for sevoflurane and propofol dosing in pediatric anesthesia and offers case examples to illustrate their use in individual patients.

Use of Processed Electroencephalography in the Clinical Setting

Purpose of Review

Processed electroencephalography (pEEG) is widely used in clinical practice. Few clinicians utilize the full potential of these devices. This brief review will address the improvements in patient management available from the utilization of all pEEG data.

Recent Findings

Anesthesiologists easily learn to recognize raw pEEG patterns that are consistent with an appropriate level of hypnotic effect. Power distribution within the waveform can be displayed in a visual format that identifies signatures of the principal anesthetic hypnotics. Opinion on the benefit of pEEG data in the mitigation of postoperative neurological impairment remains divided.

Summary

Looking beyond the index number can aid clinical decision making and improve confidence in the benefits of this monitoring modality.

Broadband slow-wave modulation in posterior and anterior cortex tracks distinct states of propofol-induced unconsciousness

A controversy has developed in recent years over the roles of frontal and posterior cortices in mediating consciousness and unconsciousness. Disruption of posterior cortex during sleep appears to suppress the contents of dreaming, yet activation of frontal cortex appears necessary for perception and can reverse unconsciousness under anesthesia. We used anesthesia to study how regional cortical disruption, mediated by slow wave modulation of broadband activity, changes during unconsciousness in humans. We found that broadband slow-wave modulation enveloped posterior cortex when subjects initially became unconscious, but later encompassed both frontal and posterior cortex when subjects were more deeply anesthetized and likely unarousable. Our results suggest that unconsciousness under anesthesia comprises several distinct shifts in brain state that disrupt the contents of consciousness distinct from arousal and awareness of those contents.

The (Un)Conscious Mouse as a Model for Human Brain Functions: Key Principles of Anesthesia and Their Impact on Translational Neuroimaging

In recent years, technical and procedural advances have brought functional magnetic resonance imaging (fMRI) to the field of murine neuroscience. Due to its unique capacity to measure functional activity non-invasively, across the entire brain, fMRI allows for the direct comparison of large-scale murine and human brain functions. This opens an avenue for bidirectional translational strategies to address fundamental questions ranging from neurological disorders to the nature of consciousness. The key challenges of murine fMRI are: (1) to generate and maintain functional brain states that approximate those of calm and relaxed human volunteers, while (2) preserving neurovascular coupling and physiological baseline conditions. Low-dose anesthetic protocols are commonly applied in murine functional brain studies to prevent stress and facilitate a calm and relaxed condition among animals. Yet, current mono-anesthesia has been shown to impair neural transmission and hemodynamic integrity. By linking the current state of murine electrophysiology, Ca2+ imaging and fMRI of anesthetic effects to findings from human studies, this systematic review proposes general principles to design, apply and monitor anesthetic protocols in a more sophisticated way. The further development of balanced multimodal anesthesia, combining two or more drugs with complementary modes of action helps to shape and maintain specific brain states and relevant aspects of murine physiology. Functional connectivity and its dynamic repertoire as assessed by fMRI can be used to make inferences about cortical states and provide additional information about whole-brain functional dynamics. Based on this, a simple and comprehensive functional neurosignature pattern can be determined for use in defining brain states and anesthetic depth in rest and in response to stimuli. Such a signature can be evaluated and shared between labs to indicate the brain state of a mouse during experiments, an important step toward translating findings across species.

Towards a Comprehensive Understanding of Anesthetic Mechanisms of Action: A Decade of Discovery

Significant progress has been made in the 21st century towards a comprehensive understanding of the mechanisms of action of general anesthetics, coincident with progress in structural biology and molecular, cellular, and systems neuroscience. This review summarizes important new findings that include target identification through structural determination of anesthetic binding sites, details of receptors and ion channels involved in neurotransmission, and the critical roles of neuronal networks in anesthetic effects on memory and consciousness. These recent developments provide a comprehensive basis for conceptualizing pharmacological control of amnesia, unconsciousness, and immobility.