The fundamental contribution of the electromyogram to a high bispectral index: a postoperative observational study

Effect of sugammadex on processed EEG parameters in patients undergoing robot-assisted radical prostatectomy

BACKGROUND

Sugammadex has been associated with increases in the bispectral index (BIS). We evaluated the effects of sugammadex administration on quantitative electroencephalographic (EEG) and electromyographic (EMG) measures.

METHODS

We performed a prospective observational study of adult male patients undergoing robot-assisted radical prostatectomy. All patients received a sevoflurane-based general anaesthetic and a continuous infusion of rocuronium, which was reversed with 2 mg kg-1 of sugammadex i.v. BIS, EEG, and EMG measures were captured with the BIS Vista™ monitor.

RESULTS

Twenty-five patients were included in this study. Compared with baseline, BIS increased at 4-6 min (β coefficient: 3.63; 95% confidence interval [CI]: 2.22-5.04; P<0.001), spectral edge frequency 95 (SEF95) increased at 2-4 min (β coefficient: 0.29; 95% CI: 0.05-0.52; P=0.016) and 4-6 min (β coefficient: 0.71; 95% CI: 0.47-0.94; P<0.001), and EMG increased at 4-6 min (β coefficient: 1.91; 95% CI: 1.00-2.81; P<0.001) after sugammadex administration. Compared with baseline, increased beta power was observed at 2-4 min (β coefficient: 93; 95% CI: 1-185; P=0.046) and 4-6 min (β coefficient: 208; 95% CI: 116-300; P<0.001), and decreased delta power was observed at 4-6 min (β coefficient: -526.72; 95% CI: -778 to -276; P<0.001) after sugammadex administration. Neither SEF95 nor frequency band data analysis adjusted for EMG showed substantial differences. None of the patients showed clinical signs of awakening.

CONCLUSIONS

After neuromuscular block reversal with 2 mg kg-1 sugammadex, BIS, SEF95, EMG, and beta power showed small but statistically significant increases over time, while delta power decreased.

Development of a Bispectral index score prediction model based on an interpretable deep learning algorithm

BACKGROUND

Proper maintenance of hypnosis is crucial for ensuring the safety of patients undergoing surgery. Accordingly, indicators, such as the Bispectral index (BIS), have been developed to monitor hypnotic levels. However, the black-box nature of the algorithm coupled with the hardware makes it challenging to understand the underlying mechanisms of the algorithms and integrate them with other monitoring systems, thereby limiting their use.

OBJECTIVE

We propose an interpretable deep learning model that forecasts BIS values 25 s in advance using 30 s electroencephalogram (EEG) data.

MATERIAL AND METHODS

The proposed model utilized EEG data as a predictor, which is then decomposed into amplitude and phase components using fast Fourier Transform. An attention mechanism was applied to interpret the importance of these components in predicting BIS. The predictability of the model was evaluated on both regression and binary classification tasks, where the former involved predicting a continuous BIS value, and the latter involved classifying a dichotomous status at a BIS value of 60. To evaluate the interpretability of the model, we analyzed the attention values expressed in the amplitude and phase components according to five ranges of BIS values. The proposed model was trained and evaluated using datasets collected from two separate medical institutions.

RESULTS AND CONCLUSION

The proposed model achieved excellent performance on both the internal and external validation datasets. The model achieved a root-mean-square error of 6.614 for the regression task, and an area under the receiver operating characteristic curve of 0.937 for the binary classification task. Interpretability analysis provided insight into the relationship between EEG frequency components and BIS values. Specifically, the attention mechanism revealed that higher BIS values were associated with increased amplitude attention values in high-frequency bands and increased phase attention values in various frequency bands. This finding is expected to facilitate a more profound understanding of the BIS prediction mechanism, thereby contributing to the advancement of anesthesia technologies.

Effect of Carbon Dioxide on Bispectral Index of EEG under Intravenous Target-Controlled Anesthesia Based on Intelligent Medical Treatment

Laparoscopic surgery has the advantages of less trauma and quick recovery, and it is more and more favored by surgeons and patients in clinical practice. However, the impact of carbon dioxide pneumoperitoneum on the body during laparoscopic surgery has attracted the attention of many scholars. Pneumoperitoneum can cause increased cerebral blood flow and increased intracranial pressure, cerebral metabolic rate is highly correlated with blood carbon dioxide partial pressure, and cerebral metabolism without cardiopulmonary bypass is linearly correlated with the depth of anesthesia. Electroencephalographic (EEG) bispectral index (BIS) is a signal analysis method, which can directly measure the effect of drugs on the cerebral cortex and reflect the depth of anesthesia. Based on this, this study takes smart medical treatment as the background and uses the improved BP neural network as a tool to explore the effect of carbon dioxide on EEG bispectral index under intravenous target-controlled anesthesia. The main purpose is to observe the correlation between arterial blood carbon dioxide partial pressure and EEG bispectral index under propofol target-controlled anesthesia during retroperitoneal laparoscopic surgery. The experimental results show that the model proposed in this study can efficiently and accurately obtain the size of the influencing factors, which provides a clinical basis for the anesthesia management and anesthesia depth regulation of carbon dioxide pneumoperitoneum laparoscopic surgery.

Evaluation of Anesthetic Specific EEG Dynamics during State Transitions between Loss and Return of Responsiveness

Purpose: electroencephalographic (EEG) information is used to monitor the level of cortical depression of a patient undergoing surgical intervention under general anesthesia. The dynamic state transitions into and out of anesthetic-induced loss and return of responsiveness (LOR, ROR) present a possibility to evaluate the dynamics of the EEG induced by different substances. We evaluated changes in the EEG power spectrum during anesthesia emergence for three different anesthetic regimens. We also assessed the possible impact of these changes on processed EEG parameters such as the permutation entropy (PeEn) and the cerebral state index (CSI). Methods: we analyzed the EEG from 45 patients, equally assigned to three groups. All patients were induced with propofol and the groups differed by the maintenance anesthetic regimen, i.e., sevoflurane, isoflurane, or propofol. We evaluated the EEG and parameter dynamics during LOR and ROR. For the emergence period, we focused on possible differences in the EEG dynamics in the different groups. Results: depending on the substance, the EEG emergence patterns showed significant differences that led to a substance-specific early activation of higher frequencies as indicated by the “wake” CSI values that occurred minutes before ROR in the inhalational anesthetic groups. Conclusion: our results highlight substance-specific differences in the emergence from anesthesia that can influence the EEG-based monitoring that probably have to be considered in order to improve neuromonitoring during general anesthesia.

Evaluation of Prognosis of Coma Patients With Acute Brain Injury by Electroencephalogram Bispectral Index Monitoring

BACKGROUND

The high mortality rate of comatose patients with traumatic brain injury is a prominent public health issue that negatively impacts patients and their families. Objective, reliable tools are needed to guide treatment decisions and prioritize resources.

OBJECTIVE

This study aimed to evaluate the prognostic value of the bispectral index (BIS) in comatose patients with severe brain injury.

METHODS

This was a retrospective cohort study of 84 patients with severe brain injury and Glasgow Coma Scale (GCS) scores of 8 and less treated from January 2015 to June 2017. Sedatives were withheld at least 24 hr before BIS scoring. The BIS value, GCS scores, and Full Outline of UnResponsiveness (FOUR) were monitored hourly for 48 hr. Based on the Glasgow Outcome Scale (GOS) score, the patients were divided into poor (GOS score: 1-2) and good prognosis groups (GOS score: 3-5). The correlation between BIS and prognosis was analyzed by logistic regression, and the receiver operating characteristic curves were plotted.

RESULTS

The mean (SD) of the BIS value: 54.63 (11.76), p = .000; and GCS score: 5.76 (1.87), p = .000, were higher in the good prognosis group than in the poor prognosis group. Lower BIS values and GCS scores were correlated with poorer prognosis. Based on the area under the curve of receiver operating characteristic curves, the optimal diagnostic cutoff value of the BIS was 43.6, and the associated sensitivity and specificity were 85.4% and 74.4%, respectively.

CONCLUSION

Taken together, our study indicates that BIS had good predictive value on prognosis. These findings suggested that BIS could be used to evaluate the severity and prognosis of severe brain injury.

Rapid arousal from anaesthesia after reversal of deep rocuronium-induced neuromuscular block with sugammadex in a neuroradiological procedure

We describe the case of a 42-year-old man undergoing elective embolisation of an arteriovenous malformation at the level of the right posterior cerebral artery under propofol anaesthesia. We used the SedLine Brain Function Monitor (Masimo) to titrate the anaesthetic depth with propofol. At the end of the procedure, the patient aroused from anaesthesia very rapidly after the reversal of deep neuromuscular block with sugammadex, despite still significant calculated doses of propofol at the effect site. This rapid arousal was monitored using the SedLine Brain Function Monitor.

Bilateral Bispectral Index Monitoring Performance in the Detection of Seizures in Nonanesthetized Epileptic Patients: An Observational Study

BACKGROUND

The aim of this observational study was to determine whether bilateral bispectral index (BIS) monitoring can detect seizures in epileptic patients.

METHODS

Four-channel frontal BIS monitoring and standard 40-channel electroencephalography monitoring were conducted in epileptic patients undergoing evaluation for epilepsy surgery. The BIS numerical value, signal quality index, electromyography, suppression ratio, and color density spectral array were continuously recorded. In patients with electroencephalography-confirmed seizures, the mean value and trend (slope of linear regression) of bilateral BIS monitor parameters were analyzed from 1 minute before to 1 minute after seizure onset.

RESULTS

Of 48 patients included in the study, 21 (43.8%) had at least 1 seizure. BIS numerical value was not able to detect focal or focal to bilateral tonic-clonic seizures. Considering all seizures, the only significant differences between recordings 1 minute before and 1 minute after seizure onset were a decrease in the signal quality index slope from 1 hemisphere (0.039±0.297 vs. -0.085±0.321, respectively; P=0.029) and in the mean signal quality index recorded from both hemispheres (left hemisphere: 65.775±30.599 vs. 61.032±26.285; P=0.016 and right hemisphere: 63.244±31.985 vs. 59.837±27.360; 0.029); these differences were not maintained after Hochberg adjustment for multiple comparisons. In seizures occurring during sleep, there was a change in the electromyography slope of 1 hemisphere before and after seizure onset (-0.141±0.176 vs. 0.162±0.140, respectively; P=0.038). There were variable responses in BIS parameters in the 3 patients who developed focal nonconvulsive seizure clusters.

CONCLUSION

Bilateral BIS monitoring was not able to detect the occurrence of seizures in epileptic patients.

Bispectral Index Alterations and Associations With Autonomic Changes During Hypnosis in Trauma Center Researchers: Formative Evaluation Study

BACKGROUND

Previous work performed by our group demonstrated that intermittent reductions in bispectral index (BIS) values were found during neurofeedback following mindfulness instructions. Hypnosis was induced to enhance reductions in BIS values.

OBJECTIVE

This study aims to assess physiologic relaxation and explore its associations with BIS values using autonomic monitoring.

METHODS

Each session consisted of reading a 4-minute baseline neutral script and playing an 18-minute hypnosis tape to 3 researchers involved in the BIS neurofeedback study. In addition to BIS monitoring, autonomic monitoring was performed, and this included measures of electromyography (EMG), skin temperature, skin conductance, respiratory rate, expired carbon dioxide, and heart rate variability. The resulting data were analyzed using two-tailed t tests, correlation analyses, and multivariate linear regression analyses.

RESULTS

We found that hypnosis was associated with reductions in BIS (P<.001), EMG (P<.001), respiratory rate (P<.001), skin conductance (P=.006), and very low frequency power (P=.04); it was also associated with increases in expired carbon dioxide (P<.001), skin temperature (P=.04), high frequency power (P<.001), and successive heart interbeat interval difference (P=.04) values. Decreased BIS values were associated with reduced EMG measures (R=0.76; P<.001), respiratory rate (R=0.35; P=.004), skin conductance (R=0.57; P<.001), and low frequency power (R=0.32; P=.01) and with increased high frequency power (R=-0.53; P<.001), successive heart interbeat interval difference (R=-0.32; P=.009), and heart interbeat interval SD (R=-0.26; P=.04) values.

CONCLUSIONS

Hypnosis appeared to induce mental and physical relaxation, enhance parasympathetic neural activation, and attenuate sympathetic nervous system activity, changes that were associated with BIS values. Findings from this preliminary formative evaluation suggest that the current hypnosis model may be useful for assessing autonomic physiological associations with changes in BIS values, thus motivating us to proceed with a larger investigation in trauma center nurses and physicians.

Effect of neuromuscular blockade on the bispectral index in critically ill patients

INTRODUCTION

It has been suggested that neuromuscular blockade (NMB) affects the capacity of bispectral index (BIS) monitoring to measure consciousness in sedated children. Our aim was to analyse the impact of NMB on BIS values in critically ill children.

METHODS

We conducted a prospective observational study of children monitored with a BIS system that received a continuous infusion of vecuronium. We analysed data on clinical, diagnostic and haemodynamic variables, sedatives, analgesics, muscle relaxants, and BIS parameters. We compared BIS parameters before the use of a muscle relaxant, during its administration, before its discontinuation and for the 24h following the end of the infusion.

RESULTS

The analysis included 35 patients (median age, 30 months). The most common diagnosis was heart disease (85%). The most frequent indication for initiation of NMB was low cardiac output (45%), followed by adaptation to mechanical ventilation (20%). Neuromuscular blockade did not produce a significant change in BIS values. We found a decrease was observed in electromyography (EMG) values at 6h (34.9±9.4 vs 31.2±7; P=.008) and 12h after initiation of NMB (34.9±9.4 vs 28.6±4.8; P =.006). We observed a small significant increase in BIS after discontinuation of NMB (from 42.7±11 to 48.4±14.5, P=.001), and 6 and 12h later (51.3±16.6; P=.015). There were no differences in the doses of sedatives or analgesics except for fentanyl, of which the dose was lowered after discontinuation of vecuronium.

CONCLUSION

Continuous NMB produces small changes on BIS values that are not clinically significant and therefore does not interfere with BIS consciousness monitoring in critically ill children.

End of year summary 2019: anaesthesia and airway management

This end of the year summary reviews anesthesia related manuscripts that have been published in the Journal of Clinical Monitoring and Computing in 2019. Anesthesia is currently defined as being composed of unconsciousness, immobility, and autonomic nervous system (ANS) control (Br J Anaesth;122:e127-e135135, Egan 2019). Pain is a postoperative issue, because by definition unconsciousness implies pain cannot be experienced. We first review work related to these aspect of the profession: unconsciousness (EEG, target control), immobility (muscle relaxants), and ANS control. Regaining consciousness has to be accompanied by pain control, and it is important to ensure that the patient regains baseline cognitive function. Anesthesia machine equipment, drug administration, and airway related topics make up the rest of published manuscripts.