State Of Deep Anesthesia Research Articles

Age-dependent Electroencephalogram Characteristics During Different Levels of Anesthetic Depth.

Objective The monitoring of anesthetic depth based on electroencephalogram derivation is not currently adjusted for age. Here we analyze the influence of age factors on electroencephalogram characteristics. Methods Frontal electroencephalogram recordings were obtained from 80 adults during routine clinical anesthesia. The characteristics of electroencephalogram with age and anesthesia were observed during four kinds of anesthesia. Results The slow wave power, δ power, Bispectral Index (BIS) and approximate entropy can be used to distinguish different states of anesthesia (P < 0.05). In the deep and very deep anesthesia states, δ power decreased with age (P < 0.0001). In the very deep anesthesia state, θ power decreased with age (P < 0.05). In the deep and very deep anesthesia states, α power decreased with age (P = 0.0002). In the light and deep anesthesia states, β power decreased with age (P = 0.003). In the deep anesthesia state, γ power decreased with age (P = 0.002). In the very deep anesthesia state, permutation entropy increased significantly with age (P = 0.0001). In the very deep anesthesia state, BIS value increased with age (P = 0.006). The slow wave power, approximate entropy, and sample entropy did not show age-dependent changes. Conclusions The influence of age should be considered when using BIS and δ power to monitor the depth of anesthesia, while the influence of age should not be considered when using slow wave power and approximate entropy to monitor the depth of anesthesia.

Meta-Analysis of the Prognostic Value of Narcotrend Monitoring of Different Depths of Anesthesia and Different Bispectral Index (BIS) Values for Cognitive Dysfunction after Tumor Surgery in Elderly Patients.

To study the effect of Narcotrend monitoring on the incidence of early postoperative cognitive dysfunction (POCD) under different bispectral index (BIS) conditions and the effect of different depths of anesthesia on the incidence of POCD. We performed a literature search of PubMed, Embase, OVID (database system made by Ovid Technologies, USA), CBM (Chinese Biomedical Literature database), CNKI (China National Knowledge Infrastructure), Wanfang, and VIP databases (full-text database of Chinese sci-tech journals), etc., from the date of the establishment of the database until December 31, 2020. Our meta-analysis was focused on the collection and study of Narcotrend monitoring of different depths of anesthesia. We carefully read the abstracts and full texts of randomized controlled trials on the incidence of POCD in the early postoperative period, and their references were tracked. Data extraction and quality evaluation of the included literature were also performed, and RevMan 5.3 software was used for analysis. In the end, eight articles were included, with a total of 714 patients. The meta-analysis results showed that four articles (255 patients) compared the state of deep anesthesia (BIS 30-40) with conventional anesthesia (BIS 40-60 earlier) after POCD. Also, the incidence of POCD on the first day after deep anesthesia (Narcotrend stage (NTS): negative correlation is currently the most appropriate EEG description; Nd can subdivide the original EEG into six stages and 15 levels (Nd Sg, NTS), namely, A (state of wakefulness) state, B0 B2 (sedated state), C0 C2 (light anesthetic state), D0 D2 (general anesthesia), and E0-E1) was significantly lower than that of conventional anesthesia (NTS DO-D1) (odds ratio (OR) = 0.21, 95% confidence interval (CI): 0.13-0.35, P < 0.00001). Moreover, the incidence of POCD in deep anesthesia (NTS E1) at 7 days after surgery was significantly lower than that of conventional anesthesia (NTS D0) (OR (odds ratio) = 0.45, 95% CI: 0.23-0.91, P=0.03), while the incidence of POCD 7 days after NTS D2 in conventional anesthesia was significantly lower than that of NTS D0 (OR = 0.42, 95% CI: 0.24-0.71, P=0.001). Discussion. Deep anesthesia can reduce the incidence of POCD (OR = 0.40, 95% CI: 0.22-0.73, P=0.002). This meta-analysis included three studies (216 patients) that compared the early postoperative POCD incidence of BIS 40-50 under conventional anesthesia and BIS 50-60; the BIS 40-50 did not significantly reduce the incidence of POCD (OR = 1.11, 95% CI: 0.24-5.24, P=0.9). The incidence of POCD under deep anesthesia with Narcotrend monitoring was lower than that under conventional anesthesia.

Systematic review and meta-analysis of the prognostic value of Narcotrend monitoring of different depths of anesthesia and different Bispectral Index (BIS) values for cognitive dysfunction after tumor surgery in elderly patients.

BackgroundTo study the effect of Narcotrend monitoring on the incidence of early postoperative cognitive dysfunction (POCD) under different Bispectral Index (BIS) conditions and the effect of different depths of anesthesia on the incidence of POCD.MethodsWe performed a literature search of the PubMed, Embase, OVID (database system made by Ovid Technologies, USA), Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CNKI), VIP Chinese Sci-tech Journals Database, Wanfang Data, etc. from the date of establishment of the database until December 31, 2020.ResultsIn the end, eighty articles were included, with a total of 714 patients. The meta-analysis results showed that four articles (255 patients) compared the state of deep anesthesia (BIS 30–40) with conventional anesthesia (BIS 40–60 earlier) after POCD. Also, the incidence of POCD on the first day after deep anesthesia [Narcotrend stage (NTS): negative correlation is currently the most appropriate egg description; Nd can subdivide the original electroencephalogram (EEG) into six stages 15 levels (Nd Sg, NTS), or A (state of wakefulness), state B0–B2 (sedated state), state C0–C2 (light anesthetic state), state D0–D2 (general anesthesia), state E0–E2 (deep anesthesia state), and state F0–F2 (burst suppression state)] was significantly lower than that of conventional anesthesia (NTS D0–D1) [odds ratio (OR) =0.21, 95% confidence interval (CI): 0.13–0.35, P<0.00001]. Moreover, the incidence of POCD in deep anesthesia (NTS E1) at 7 days after surgery was significantly lower than that of conventional anesthesia (NTS D0) (OR =0.45, 95% CI: 0.23–0.91, P=0.03), while the incidence of POCD 7 days after NTS D2 in conventional anesthesia was significantly lower than that of NTS D0 (OR =0.42, 95% CI: 0.24–0.71, P=0.001).DiscussionsPOCDs are thought to be the result of a combination of physical defects and precipitating factors in patients with their own physical impairments, and despite potential adverse effects, there is currently no consensus on the incidence of POCDs in patients with tumor, current risk factors, causes, and prevention strategies. Moreover, the level of evidence is low, and the deviation between different studies cannot be ruled out.

Nucleus accumbens neurons expressing dopamine D1 receptors modulate states of consciousness in sevoflurane anesthesia

Although general anesthesia (GA) enables patients to undergo surgery without consciousness, the precise neural mechanisms underlying this phenomenon have yet to be identified. In addition to many studies over the past two decades implicating the thalamus, cortex, brainstem, and conventional sleep-wake circuits in GA-induced loss of consciousness (LOC), some recent studies have begun to highlight the importance of other brain areas as well. Here, we found that population activities of neurons expressing dopamine D1 receptor (D1R) in the nucleus accumbens (NAc), a critical interface between the basal ganglia and limbic system, began to decrease before sevoflurane-induced LOC and gradually returned after recovery of consciousness (ROC). Chemogenetic activation of NAcD1R neurons delayed induction of and accelerated emergence from sevoflurane GA, whereas chemogenetic inhibition of NAcD1R neurons exerted opposite effects. Moreover, transient activation of NAcD1R neurons induced significant cortical activation and behavioral emergence during continuous steady-state GA with sevoflurane or deep anesthesia state with constant and stable burst-suppression oscillations. Taken together, our findings uncover that NAcD1R neurons modulated states of consciousness associated with sevoflurane GA and may represent an area for targeting GA-induced changes in consciousness and ameliorating related adverse effects.

Signal Processing and Machine‐learning Algorithm to classify anesthesia depth

BackgroundAn algorithm with complexity measures, nonlinear dynamics, and neural networks were developed to detect and classify the anesthetic deep (AD). It has been shown that extreme anesthetic depth has been correlated with an increased risk of mortality. Likewise, intraoperative awareness has been reported in the anesthetic drugs under dosage.MethodsOur artificial intelligence classifier algorithm was developed using a Complexity Brainwave Index (CBI) and a heart rate variability parameter (HRVP). Data from 60 patients (25 men and 35 women), adults between 18 and 65 years of age undergoing surgical procedures (ASA I–II) were collected. The classifier was designed using multi‐layer feedforward neural networks with a hyperbolic activation function using the patient data set and their anesthesia records.ResultsThe CBI by itself showed a better prediction probability with Pk of 0.935 when compared with Datex‐Ohmeda index in which State Entropy and Response Entropy had a Pk of 0.884 and 0.899 respectively; also, our CBI showed a performance of 99% of the awake state and 93.3% for deep anesthesia state. Additionally, when combining the CBI and the HRVP, the C‐Statistic was 99% for the awake state, 87.41% for light anesthesia, 82,46% for general anesthesia, and 93.33% for deep anesthesia.ConclusionsOur results demonstrate that special biological signal filtering and a machine learning algorithm may be used to classify AD during a surgical procedure on ASA I–II patients, assisting anesthesiologists and clinicians in decision making.Support or Funding InformationUniversity of La Sabana

Propofol inhibits the local activity and connectivity of nuclei in the cortico-reticulo-thalamic loop in rats.

The present study aimed to investigate the effects of different dosages of propofol, that induced different depths of anesthesia, on the local activity and connectivity of nuclei within the cortico-reticulo-thalamic loops, as well as the release of amino acids in those nuclei. The nonlinear dynamics analysis of electroencephalogram, including approximate entropy (ApEn) and cross-ApEn (C-ApEn), was used to analyze the effects of different dosages of propofol on the local activity and connectivity of the important nuclei, including the primary somatosensory cortex (S1), ventroposteromedial thalamic nucleus (VPM), reticular thalamic nucleus (RTN), and oral part of the pontine reticular nucleus (PnO). The levels of glutamate (Glu), γ-aminobutyric acid (GABA), and glycine (Gly) in the S1, VPM, and RTN were detected using cerebral microdialysis. ApEn was more significantly reduced in the cortex than in the subcortical nuclei from awake to deep anesthesia state induced by propofol, and C-ApEn was also more significantly reduced between cortical nucleus and subcortical nucleus than between subcortical nuclei from awake to deep anesthesia state induced by propofol. Propofol inhibited the levels of Glu in S1 and VPM, but elevated the levels in RTN. Gly level decreased in S1, and GABA level increased in S1 after infusion of propofol. The cortex rather than the subcortical structures, and the cortex-subcortical connectivity instead of subcortical connectivity might be the more vulnerable targets of propofol during anesthesia.

ESTIMATION OF THE DEPTH OF ANESTHESIA BY ELECTROENCEPHALOGRAM USING NEURAL NETWORKS

Introduction. Monitoring of the depth of anesthesia during surgery is a complex task. Since electroencephalogram (EEG) signals contain valuable information about processes in the brain, EEG analysis is considered to be one of the most useful methods for study and assessment of the depth of anesthesia in clinical applications. Anesthetics affect the frequency composition of the EEG. EEG of awake persons, as a rule, contains mixed alpha and beta rhythms. Changes in the EEG, caused by the transition from the waking state to the state of deep anesthesia, manifest as a shift of the spectral components of the signal to the lower part of the frequency range. Anesthetics cause a whole range of neurophysiological changes, which cannot be correctly assessed with just one indicator. Objective. In order to describe complex processes during the transition from the waking state to the state of deep anesthesia adequately, it is required to propose a method for assessing the depth of anesthesia, using a comprehensive set of parameters reflecting changes in the EEG signal. The article presents the results of study the possibility of building a regression model based on artificial neural networks (ANN) to determine levels of anesthesia using a set of parameters calculated by EEG. Materials and methods. The authors of the article propose the method for assessing the level of anesthesia, based on the use of neural networks, which input parameters are time and frequency EEG parameters, namely: spectral entropy (SE); burst-suppression ratio (BSR); spectral edge frequency (SEF95) and log power ratio of the spectrum (RBR) for three pairs of frequency ranges. Results. The optimal parameters of ANN were determined, at which the highest level of regression is achieved between the calculated and the verified values of the anesthesia depth indices. Conclusion. In order to create a practical version of the algorithm, it is necessary to investigate further the noise stability of the proposed method and develop a set of algorithmic solutions, which ensure a reliable operation of the algorithm in the presence of noise.

Human Midbrain Participates In Mismatch Detection Without Cognitive Activity Of The Cerebral Cortex: Case Report

Mismatch detection is the process of identification of rare stimuli from a sequence of stimuli. This important cognitive function is usually attributed to the cerebral cortex. To test the human midbrain involvement in sound mismatch detection, we recorded local field potentials in the states of deep anesthesia and clear consciousness from the drainage-electrode implanted in the cerebral aqueduct of an adult patient with an obstructive hydrocephaly who had undergone pineal region tumor removal through anterior interhemispheric transcallosal approach. We found a significant difference in the state of deep anesthesia at 256-364 ms after hearing a rarely presented sounds compared with frequently presented sounds and equally probable sounds. This difference was not found in the same experiment in the state of clear consciousness. The results suggest that human midbrain participates in mismatch detection and can do it even without cognitive activity of the cerebral cortex. Amplitude-frequency analysis of the midbrain records revealed that propofol affects the electrical activity of both human midbrain and cortex but the level of inhibition of the cortex is 6 times higher than the level of inhibition of the midbrain. We suppose that the human cortex is more susceptible to propofol than the human midbrain.

The Influence of Anesthesia on Corticocortical Evoked Potential Monitoring Network Between Frontal and Temporoparietal Cortices

Previous studies have reported the usefulness of intraoperative corticocortical evoked potentials (CCEPs) for preserving language function during brain surgery. This study aimed to assess the influence of depth of anesthesia on CCEP to establish its clinical utility. Twenty patients with brain tumors or epilepsy who underwent awake craniotomy were included in this study. Before resection, the electrode plates were placed on the frontal and temporoparietal cortices, and 1-Hz alternating electrical stimuli were delivered to the pars opercularis/pars triangularis in a bipolar fashion. Electrocorticograms from the temporoparietal cortices time-locked to stimuli were averaged to obtain CCEP responses from a state of deep anesthesia until the awake state. The correlation between CCEP waveforms and bispectral index (BIS) was evaluated. CCEP amplitude increased with the increase in the BIS level. CCEP latency decreased in 5 patients and increased in 15 patients under anesthesia compared with the awake state. CCEP amplitudes decreased by 11.3% to 75.2% (median 31.3%) under anesthesia with <65 BIS level. These differences were statistically significant (P < 0.01, Wilcoxon signed-rank test). With respect to CCEP latencies, there was no significant difference between the awake and anesthetic states. CCEP amplitudes were correlated with depth of anesthesia, whereas CCEP latencies were not affected by anesthesia. The influence of anesthesia should be considered when applying this technique to intraoperative monitoring.

Increasing isoflurane dose reduces homotopic correlation and functional segregation of brain networks in mice as revealed by resting-state fMRI

Effects of anesthetics on brain functional networks are not fully understood. In this work, we investigated functional brain networks derived from resting-state fMRI data obtained under different doses of isoflurane in mice using stationary and dynamic functional connectivity (dFC) analysis. Stationary network analysis using FSL Nets revealed a modular structure of functional networks, which could be segregated into a lateral cortical, an associative cortical network, elements of the prefrontal network, a subcortical network, and a thalamic network. Increasing isoflurane dose led to a loss of functional connectivity between the bilateral cortical regions. In addition, dFC analysis revealed a dominance of dynamic functional states (dFS) exhibiting modular structure in mice anesthetized with a low dose of isoflurane, while at high isoflurane levels dFS showing widespread unstructured correlation displayed highest weights. This indicates that spatial segregation across brain functional networks is lost with increasing dose of the anesthetic drug used. To what extent this indicates a state of deep anesthesia remains to be shown. Combining the results of stationary and dynamic FC analysis indicates that increasing isoflurane levels leads to loss of modular network organization, which includes loss of the strong bilateral interactions between homotopic brain areas.

The influence of depth of anesthesia on motor evoked potential response during awake craniotomy.

OBJECTIVE Motor evoked potentials (MEPs) are a critical indicator for monitoring motor function during neurological surgery. In this study, the influence of depth of anesthesia on MEP response was assessed. METHODS Twenty-eight patients with brain tumors who underwent awake craniotomy were included in this study. From a state of deep anesthesia until the awake state, MEP amplitude and latency were measured using 5-train electrical bipolar stimulations on the same site of the precentral gyrus each minute during the surgery. The depth of anesthesia was evaluated using the bispectral index (BIS). BIS levels were classified into 7 stages: < 40, and from 40 to 100 in groups of 10 each. MEP amplitude and latency of each stage were compared. The deviation of the MEP measurements, which was defined as a fluctuation from the average in every BIS stage, was also considered. RESULTS A total of 865 MEP waves in 28 cases were evaluated in this study. MEP amplitude was increased and latency was decreased in accordance with the increases in BIS level. The average MEP amplitudes in the > 90 BIS level was approximately 10 times higher than those in the < 40 BIS level. Furthermore, the average MEP latencies in the > 90 BIS level were 1.5-3.1 msec shorter than those in the < 60 BIS level. The deviation of measured MEP amplitudes in the > 90 BIS level was significantly stabilized in comparison with that in the < 60 BIS level. CONCLUSIONS MEP amplitude and latency were closely correlated with depth of anesthesia. In addition, the deviation in MEP amplitude was also correlated with depth of anesthesia, which was smaller during awake surgery (high BIS level) than during deep anesthesia. Therefore, MEP measurement would be more reliable in the awake state than under deep anesthesia.

Analysis of anesthesia stages based on the EEG entropy estimation

New algorithm for anesthesia depth analysis using EEG signal is presented. The algorithm is intended for the use in anesthesia depth monitors in the course of surgical operations. The suggested algorithm is based upon the combination of the following three approaches: signal randomness analysis with the use of approximate entropy, power spectrum analysis and analysis of specific signal changes that take place at the state of deep anesthesia. The algorithm was tested with the use of real ECG recordings obtained in the course of surgical operations and demonstrated good performance. The software package realizing this algorithm is used in an anesthesia depth monitor prepared to the batch production. Further efforts for the algorithm improving should be directed to the increase of the algorithm robustness to noises.

Neural origin of spontaneous hemodynamic fluctuations in rats under burst-suppression anesthesia condition.

Spontaneous hemodynamic signals fluctuate coherently within many resting-brain functional networks not only in awake humans and lightly anesthetized primates but also in animals under deep anesthesia characterized by burst-suppression electroencephalogram (EEG) activity and unconsciousness. To understand the neural origin of spontaneous hemodynamic fluctuations under such a deep anesthesia state, epidural EEG and cerebral blood flow (CBF) were simultaneously recorded from the bilateral somatosensory cortical regions of rats with isoflurane-induced burst-suppression EEG activity. Strong neurovascular coupling was observed between spontaneous EEG "bursts" and CBF "bumps," both of which were also highly synchronized across the 2 hemispheres. Functional magnetic resonance imaging (fMRI) was used to image spontaneous blood oxygen level-dependent (BOLD) signals under the same anesthesia conditions and showed similar BOLD "bumps" and dependence on anesthesia depth as the CBF signals. The spatiotemporal BOLD correlations indicate a strong but less-specific coherent network covering a wide range of cortical regions. The overall findings reveal that the spontaneous CBF/BOLD fluctuations under unconscious burst-suppression anesthesia conditions originate mainly from underlying neural activity. They provide insights into the neurophysiological basis for the use of BOLD- and CBF-based fMRI signals for noninvasively imaging spontaneous and synchronous brain activity under various brain states.

Approximate entropy of anesthesia EEG: compromise between calculation time and clinical validity

Approximate entropy, a measure of regularity, can be used to analyze the electroencephalogram of patients in general anesthesia to discriminate between different states of consciousness. EEG burst suppression patterns reflect a state of deep anesthesia. Due to the instationary character of this EEG pattern approximate entropy values do not correctly classify the patient state. Possible solutions to this problem may be limited by the demand of computing power for entropy calculation and the reaction time following changes in patient state. Different approaches for an online monitoring application are examined.

A retrograde double-labelling study of retinal ganglion cells that project ipsilaterally to vLGN and LPN rather than dLGN and SC, in albino rat

We studied ipsilaterally projecting, double-labeled retinal ganglion cells that have bifurcating axons by retrograde fluorescent double-labeling in albino rats. Ten albino (Wistar, Japan Clea) rats of either sex, weighing 350–400 g were used. With the rats in a state of deep anesthesia, we pressure-injected 0.02 μl of 15% Evans blue (EB) into the right ventral lateral geniculate nucleus (vLGN), and 4% Fluoro-gold (FG) iontophoretically into the right posterior lateral thalamic nucleus (LP). The animals were perfused with formol-saline 48–72 h later and both the brain and eyes were excised. The brain was sectioned coronally, and each retina was removed and mounted flat on a glass slide. Double-labeled cells were found in the ventral temporal crescent of the retina. In one animal the total number of ipsilaterally labeled cells was 566, and the percentages of double-labeled vLGN and LP projecting cells, single-labeled vLGN projecting cells, and single-labeled LP projecting cells were 29.8, 58.8 and 11.3, respectively.

An electroencephalographic comparison of effects of propofol and methohexital

Thirty-eight patients were randomly allocated to receive propofol 1 mg/kg (group A, N = 10), methohexital 0.7 mg/kg (group B, N = 9), propofol 2 mg/kg (group C, N = 10), methohexital 1.5 mg/kg (group D, N = 9). They were all male with a mean age of 65.8 years (range, 46–85) and a mean weight of 76.2 kg (range, 50–109). Patients received no premedication. All drugs were administered as a single i.v. bolus. After baseline EEG recordings were obtained, i.v. bolus doses were given and the recording continued until the patients became fully responsive to verbal commands. The EEGs were visually analyzed and classified into 4 phases: phase 0, the wake physiologic pattern; phase 1, initial changes after i.v. bolus doses; phase 2, state of deep anesthesia; and phase 3, stage of recovery. The main change during phase 1 was increase in the amplitude of the background rhythms. Phase 2 was characterized by theta and delta activity and burst suppression in some patients. During phase 3 beta activity was seen following methohexital. Propofol produced a much deeper level of anesthesia compared to methohexital. The stage of deep anesthesia was prolonged following propofol. The clinical and EEG recoveries were prolonged after induction doses of propofol. The quality of recovery, however, was far superior with propofol. Methohexital produces a “hang over” effect which delays full recovery.

Mechanism of lowering of the basal metabolism during adaptation to hypoxia

During adaptation of rats to periodic hypoxia in a pressure chamber the oxygen consumption fell by 40%. This decrease was still found in a state of deep anesthesia and, consequently, it was independent of adaptive changes in cortical regulation of the animals' motor activity. Half of this decrease in oxygen consumption still continued during exposure of the animal to cold, noradrenalin, and 2,4-dinitrophenol (DNP), which uncouples oxidative phosphorylation. The economic utilization of oxygen during adaptation to hypoxia cannot thus be completely explained by an increase in the degree of coupling of oxidation with phosphorylation.

"Anesthesia produced by magnesium salts," a preliminary communication, with demonstrations

The authors exhibited to the society two guinea-pigs, which were deeply narcotized by injections of magnesium sulfate. One of these animals had been similarly narcotized twice before, and fully recovered each time. In their physiological and toxicological studies of magnesium salts, the authors found that by subcutaneous injections of certain quantities of sulfate or chlorid of magnesium, animals can be brought into a state of deep anesthesia, during which any operation can be performed upon them without the least resistance. If the dose of the salts is not too large, heartbeat, blood-pressure and respiration remain nearly normal. It was tested on dogs, cats, rabbits, guinea-pigs, white rats and frogs. A gram and a half of magnesium sulfate is about the effective dose for most of the animals. The chlorid has to be used in smaller doses in proportion to its smaller molecular weight. Particulars will be reported later. The authors emphasized the fact that these salts are very poisonous when certain maximum doses are exceeded.