Alternative sensor montage for Index based EEG monitoring. A systematic review

The main objective of this systematic review is to assess the reliability of alternative positions of processed electroencephalogram sensors for depth of anesthesia monitoring and its applicability in clinical practice. A systematic search was conducted in PubMed, Embase, Cochrane Library, Clinical trial.gov in accordance with reporting guidelines of PRISMA statement together with the following sources: Google and Google Scholar. We considered eligible prospective studies, written in the English language. The last search was run on the August 2023. Risk of bias and quality assessment were performed. Data extraction was performed by two authors and results were synthesized narratively owing to the heterogeneity of the included studies. Thirteen prospective observational studies (438 patients) were included in the systematic review after the final assessment, with significant diversity in study design. Most studies had a low risk of bias but due to lack of information in one key domain of bias (Bias due to missing data) the overall judgement would be No Information. However, there is no clear indication that the studies are at serious or critical risk of bias. Bearing in mind, the heterogeneity and small sample size of the included studies, current evidence suggests that the alternative infraorbital sensor position is the most comparable for clinical use when the standard sensor position in the forehead is not possible.

Assessment of seizure duration and utility of using SedLine® EEG tracing in veterans undergoing electroconvulsive therapy: a retrospective analysis

BACKGROUND

Electroconvulsive therapy (ECT) endures as a definitive treatment for refractory depression and catatonia and is also considered an effective treatment for a number of other severe psychiatric disorders (Lisanby, N Engl J Med 357:1939-1945, 2007)(Weiner and Prudic, Biol Psychiatry 73:105-106, 2013). GA is an essential component of the ECT procedure for various reasons (Lee, Jenkins and Sparkle, Life 11, 2021). Monitoring anesthetic effects on the brain is desirable as anesthetic agents affect seizure duration and recovery (Rasulo, Hopkins, Lobo, et al,  Neurocrit Care 38:296-311, 2023) (Jones , Nittur , Fleming and Applegate,  BMC Anesthesiol 21:105, 2021) (Soehle , Kayser , Ellerkmann and Schlaepfer,  BJA 112:695-702, 2013). Perioperative anesthetic effects on consciousness can be assessed with brain function monitoring using raw electroencephalogram (EEG) traces and processed EEG indices.

OBJECTIVE

We examined the usefulness and utility of the SedLine® anesthetic effect monitor during ECT procedures. We hypothesized that the seizure duration as measured by the EEG tracing of the ECT machine is equivalent to the duration assessed by the SedLine® EEG tracing. A secondary objective was to describe the SedLine® patient state indices (PSI) at different phases of treatment.

METHODS

Following IRB approval, we analyzed the data of the electronic medical records of 45 ECT treatments of 23 patients in an urban VA medical center between July 01, 2021, and March 30, 2022. We compared the seizure duration in minutes and seconds as measured either by the ECT machine EEG tracing or the SedLine® EEG tracing. We then collected SedLine® processed EEG indices at four different stages during the treatment. Appropriate comparative and observational statistical analyses were applied.

RESULTS

There was no significant difference in measured seizure duration between the two methods examined (p < 0.05). We observed a lag of the SedLine PSI value at the time before stimulus delivery and limited PSI utility during the course of ECT.

CONCLUSION

The SedLine® EEG tracing can be an alternative to the machine EEG tracing for the determination of seizure duration. The SedLine® processed EEG indices are not consistently useful before and after ECT delivery. Anesthetic effect monitoring during ECT is feasible.

Performance of the SEDLine Monitor: Age Dependency and Time Delay

BACKGROUND

Devices monitoring the hypnotic component of general anesthesia can help to guide anesthetic management. The main purposes of these devices are the titration of anesthesia dose. While anesthesia at low doses can result in awareness with intraoperative memory formation, excessive administration of anesthetics may be associated with an increased risk of postoperative neurocognitive disorder. We have previously shown for various indices that they are significantly influenced by the patient's age and that the monitors have a significant time delay. Here, we evaluated the influence of patient's age and time delay on the patient state index (PSI) of the SEDLine monitor.

METHODS

To analyze the influence of the patient's age, we replayed 2 minutes of electroencephalography (EEG) of 141 patients (19-88 years, ASA I-IV) undergoing general anesthesia maintained with desflurane, sevoflurane, or propofol to the SEDLine monitor. We extracted the PSI as well as the spectral edge frequency (SEF) and performed a linear regression analysis. For evaluation of the time delay, we replayed 5 minutes of EEG of stable episodes of adequate anesthesia (PSI between 25 and 50) or light sedation/wake (PSI >70) in different orders to the SEDLine to simulate sudden changes between the states. Time delays were defined as the required time span of the monitor to reach the stable target index.

RESULTS

PSI and SEF increased significantly with the patient's age. These findings did not depend on the administered anesthetic. The evaluation of the correlation between SEF and PSI showed a strong correlation with Spearman's correlation coefficient of ρ = 0.86 (0.82; 0.89). The time delays depended on the type of transition. We found a median time delay of 54 (Min: 46; Max: 61) seconds for the important transition between adequate anesthesia and awake and 55 (Min: 50; Max: 67) seconds in the other direction.

CONCLUSIONS

With our analyses, we show that the indices presented on the SEDLine display, the PSI and the SEF, increase with age for patients under general anesthesia. Additionally, a delay of the PSI to react to sudden neurophysiologic changes due to dose of the maintenance anesthetic is of a time course that is clinically significant. These factors should be considered when navigating anesthesia relying on only the proprietary index for the SEDLine monitor.

A Pilot Investigation Evaluating Relative Changes in Fronto-Occipital Alpha and Beta Spectral Power as Measurement of Anesthesia Hypnotic Depth

BACKGROUND

Other than clinical observation of a patient's vegetative response to nociception, monitoring the hypnotic component of general anesthesia (GA) and unconsciousness relies on electroencephalography (EEG)-based indices. These indices exclusively based on frontal EEG activity neglect an important observation. One of the main hallmarks of transitions from wakefulness to GA is a shift in alpha oscillations (7.5-12.5 Hz activity) from occipital brain regions toward anterior brain regions ("alpha anteriorization"). Monitoring the degree of this alpha anteriorization may help to guide induction and maintenance of hypnotic depth and prevent intraoperative awareness. However, the occipital region of the brain is completely disregarded and occipital alpha as characteristic of wakefulness and its posterior-to-anterior shift during induction are missed. Here, we propose an application of Narcotrend's reduced power alpha beta (RPAB) index, originally developed to monitor differences in hemispheric perfusion, for determining the ratio of alpha and beta activity in the anterior-posterior axis.

METHODS

Perioperative EEG data of 32 patients undergoing GA in the ophthalmic surgery department of Bern University Hospital were retrospectively analyzed. EEG was recorded with the Narcotrend® monitor using a frontal (Fp1-Fp2) and a posterior (T9-Oz) bipolar derivation with reference electrode over A2. The RPAB index was computed between both bipolar signals, defining the fronto-occipital RPAB (FO-RPAB). FO-RPAB was analyzed during wakefulness, GA maintenance, and emergence, as well as before and after the intraoperative administration of a ketamine bolus. FO-RPAB was compared with a classical quantitative EEG measure-the spectral edge frequency 95% (SEF-95).

RESULTS

A significant shift of the FO-RPAB was observed during both induction of and emergence from GA ( P < .001). Interestingly, the additional administration of ketamine during GA did not lead to a significant change in FO-RPAB ( P = 0.81). In contrast, a significant increase in the SEF-95 in the frontal channel was observed during the 10-minute period after ketamine administration ( P < .001).

CONCLUSIONS

FO-RPAB appears to qualify as a marker of unconsciousness, reflecting physiological fronto-occipital activity differences during GA. In contrast to frontal SEF-95, it is not disturbed by additional administration of ketamine for analgesia.

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.

Effects of Different Injection Rates of Propofol on Postoperative Cognition in Elderly Patients Undergoing Laparoscopic Inguinal Hernia Repair

Purpose

This study aimed to explore the effects of different injection rates of propofol on postoperative cognition in elderly patients undergoing laparoscopic inguinal hernia repair.

Methods

A total of 180 elderly patients who planned to undergo laparoscopic inguinal hernia repair were randomly divided into three groups: slow injection of propofol (V_S-Group, 30 mg kg^-1 h^-1); medium injection of propofol (V_M-Group, 100 mg kg^-1 h^-1) or fast injection of propofol (V_F-Group, 300 mg kg^-1 h^-1). Propofol was induced by microinfusion pump, and the depth of anesthesia was monitored by bispectral index (BIS). Propofol and remifentanil were continuously infused during anesthesia maintenance and adjusted according to BIS. The primary outcome was the use of the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) to measure the incidence of postoperative cognitive decline (POCD) in elderly patients on the first and seventh postoperative day. Secondary outcomes included induced dose of propofol, incidence of burst suppression and maximum electroencephalographic (EEG) effect of propofol (BIS-min) during induction.

Results

The incidence of POCD on the first and seventh day postoperatively was similar among the three groups (P > 0.05). However, with the increase of propofol injection rate, induced dose of propofol, incidence of burst suppression and BIS-min during induction, the number of patients requiring vasoactive agents were significantly increased (P < 0.001). Multivariate regression analysis showed that the brief duration of burst suppression during induction did not affect the occurrence of POCD, while age and duration of hospitalization were risk factors for POCD.

Conclusion

For elderly patients undergoing laparoscopic inguinal hernia repair, lowering the injection rate of propofol (such as 30 mg kg^-1 h^-1) cannot decrease the incidence of early POCD, but reduces induction dose of propofol and use of vasoactive drugs, making the patient's hemodynamics more stable.

The use of processed electroencephalography (pEEG) in obstetric anaesthesia: a narrative review

Accidental awareness under general anaesthesia (AAGA) remains a major complication of anaesthesia. The incidence of AAGA during obstetric anaesthesia is high relative to other specialities. The use of processed electroencephalography (pEEG) in the form of "depth of anaesthesia" monitoring has been shown to reduce the incidence of AAGA in the non-obstetric population. The evidence for using pEEG to prevent AAGA in the obstetric population is poor and requires further exploration. Furthermore, pregnancy and disease states affecting the central nervous system, such as pre-eclampsia, may alter the interpretation of pEEG waveforms although this has not been fully characterised. National guidelines exist for pEEG monitoring with total intravenous anaesthesia and for "high-risk" cases regardless of technique, including the obstetric population. However, none of the currently available guidelines relates specifically to obstetric anaesthesia. Using pEEG monitoring for obstetric anaesthesia may also provide additional benefits beyond a reduction in risk of AAGA. These potential benefits include reduced postoperative nausea and vomiting, reduced anaesthetic agent use, a shorter post-anaesthetic recovery stay. In addition, pEEG acts as a surrogate marker of cerebral perfusion, and thus as an additional monitor for impending cardiovascular collapse, as seen in amniotic fluid embolism. The subtle physiological and pathological changes in EEG activity that may occur during pregnancy are an unexplored research area in the context of anaesthetic pEEG monitors. We believe that the direction of clinical practice is moving towards greater use of pEEG monitoring and individualisation of anaesthesia.

Cerebral Tissue Oxygen Saturation Correlates with Emergence from Propofol-Remifentanil Anesthesia: An Observational Cohort Study

Anesthesia emergence is accompanied by changes in cerebral circulation. It is unknown whether cerebral tissue oxygen saturation (SctO₂) could be an indicator of emergence. Changes in SctO₂, bispectral index (BIS), mean arterial pressure (MAP), and heart rate (HR) were evaluated during the emergence from propofol-remifentanil anesthesia. At the time of cessation of anesthetic delivery, SctO₂, BIS, MAP, and HR values were recorded as baseline. The changes of these parameters from the baseline were recorded as Δ SctO₂, Δ BIS, Δ MAP, and Δ HR. The behavioral signs (body movement, coughing, or eye opening) and response to commands (indicating regaining of consciousness) were used to define emergence states. Prediction probability (Pk) was used to examine the accuracy of SctO₂, BIS, MAP, and HR as indicators of emergence. SctO₂ showed an abrupt and distinctive increase when appearing behavioral signs. BIS, MAP, and HR, also increased but with a large inter-individual variability. Pk value of Δ SctO₂ was 0.97 to predict the appearance behavioral signs from 2 min before that, which was much higher than the Pk values of Δ BIS (0.81), Δ MAP (0.71) and Δ HR (0.87). The regaining of consciousness was associated with a further increase in the SctO₂ value.

Pharmacodynamic analysis of intravenous bolus remimazolam for loss of consciousness in patients undergoing general anaesthesia: a randomised, prospective, double-blind study

BACKGROUND

Remimazolam is a new rapid offset benzodiazepine used for procedural sedation and general anaesthesia. This study evaluated the efficacy and safety of i.v. bolus remimazolam during induction of anaesthesia.

METHODS

A total of 120 patients undergoing general anaesthesia were randomly allocated into six dose groups (n=20) of i.v. bolus remimazolam (0.02-0.27 mg kg^-1). Loss of consciousness, respiratory depression, patient state index (PSI), and haemodynamic variables were evaluated during anaesthetic induction. Parametric time-to-event models were used to identify the 50% effective dose (ED50)/95% effective dose (ED95) associated with loss of consciousness and respiratory depression. Non-linear mixed-effect models analysed the PSI and haemodynamic changes after i.v. bolus remimazolam.

RESULTS

Loss of consciousness and respiratory depression onset showed steep dose-responses with ED50/ED95 of 0.11/0.19 and 0.14/0.27 mg kg^-1 and Hill coefficients of 5.3 and 4.6, respectively. Older age was significantly associated with lower ED50/ED95 for both endpoints. ED50/ED95 and the Hill coefficient of PSI decline were 0.12/0.68 mg kg^-1 and 1.7, respectively. We propose optimal doses of 0.25-0.33, 0.19-0.25, and 0.14-0.19 mg kg^-1 in patients aged <40, 60-80, and >80 yr, respectively, based on the ED95 estimates for the corresponding age groups. The maximum percentage reduction of MAP was 27.8% and the ED50/ED95 were 0.14/2.60 mg kg^-1. The effect of remimazolam on heart rate was insignificant.

CONCLUSIONS

The ED50/ED95s of i.v. bolus remimazolam were successfully estimated from the time to loss of consciousness and respiratory depression. No serious adverse events occurred within the range of tested doses.

CLINICAL TRIAL REGISTRATION

NCT04901871.

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.

Anaesthetic depth and delirium: a challenging balancing act

This editorial highlights the findings of the Balanced Anaesthesia Delirium study, a 515-patient substudy of the 6644 patient Balanced Anaesthesia trial, which found that targeting deep anaesthesia in patients undergoing major noncardiac surgery was not associated with significantly increased postoperative death or major morbidity. The substudy found that using bispectral index (BIS) guidance with the intention of deliberately achieving deep volatile agent-based anaesthesia (target BIS reading 35 vs 50) significantly increased delirium incidence (28% vs 19%), although not subsyndromal delirium incidence (45% vs 49%). We discuss the implications of these findings for anaesthetic practice, and address whether the BIS should be used as a guide to deliver precision anaesthesia for delirium prevention. We posit that subpopulation-based differences within this multicentre substudy could have affected delirium occurrence, since the findings appeared to rest on outcomes in patients from East Asia. We conclude that questions of whether and for whom deep anaesthesia is deliriogenic remain unanswered.

Air-embolism in the semi-sitting position for craniotomy: A narrative review with emphasis on a single centers experience

Albeit the semi-sitting position in neurosurgery has been in use for several decades, its application remains controversial in the neurosurgical and neuro-anaesthesia communities. The imminent and most feared risk of the sitting position is air entry into the vascular system due to the negative intravascular pressure leading to potentially life-threatening air embolism with its consequences. Recent advents in neurosurgical (improvement of the operating microscope, employment of intra-operative neurophysiological monitoring) and neuro-anaesthesia care (new anaesthetics, advanced monitoring modalities) have significantly impacted the approach to these surgeries. Vigilant intra-operative observation by an experienced team and peri-operative patient management guided by institutional protocols improves the safety profile of these surgeries. This review outlines the workflow and protocols used in our institution for all cases of semi-sitting position for skull base neurosurgery.

Propofol-Bispectral Index (BIS) Electroencephalography (EEG) Pharmacokinetic-Pharmacodynamic Model in Patients With Post-Cerebral Hemorrhage Hydrocephalus

Background. Titrating hypnotic agents for patients who suffer from a cerebral insult is a challenging task. To date there is no real gold standard to precisely quantify electroencephalography (EEG) response in a fashion that could be utilized for patients with post-cerebral hemorrhage hydrocephaly. While we must administer "as per usual" analgesics for noxious stimuli, we have to administer the hypnotic agents more "sparingly" due to lack of objective monitoring. Methods. We compared 15 adult post-cerebral hemorrhage hydrocephalus patients undergoing ventriculo-peritoneal shunt placement with 15 controls matched for gender and approximate age. We set propofol target controlled infusion estimated plasma concentrations (C_p) to gradually reach 4 µg/mL over 4 minutes. To precisely quantify post-cerebral hemorrhage mental dysfunction, we used electronically retrieved bispectral index (BIS) and propofol C_p data points to create individual inhibitory monophasic mathematical model for each patient that incorporates an independent hysteresis "lag" function. Results. In post-cerebral hemorrhage patients C_p-BIS curve, C₅₀ (propofol concentration associated with inhibitory 50% BIS response) cutoff point was significantly shifted to the left by 39%. Whereas before infusion and at stable propofol 4 µg/mL aneurismal surgical sides ipsilateral (75 ± 13, 25 ± 9) and contralateral (73 ± 15, 27 ± 9) mean ± SD BIS values were significantly lower than ipsilateral (95 ± 3, 46 ± 12) and contralateral (94 ± 3, 46 ± 12) matched controls. Conclusions. Using BIS as surrogate marker of propofol hypnotic effect, BIS monitoring in patients with post-cerebral hemorrhage hydrocephaly showed a pattern of change and trend that was similar albeit 39% significantly lower than subjects without.

Applications and Limitations of Neuro-Monitoring in Paediatric Anaesthesia and Intravenous Anaesthesia: A Narrative Review

Safe management of anaesthesia in children has been one of the top areas of research over the last decade. After the large volume of articles which focused on the putative neurotoxic effect of anaesthetic agents on the developing brain, the attention and research efforts shifted toward prevention and treatment of critical events and the importance of peri-anaesthetic haemodynamic stability to prevent negative neurological outcomes. Safetots.org is an international initiative aiming at raising the attention on the relevance of a high-quality anaesthesia in children undergoing surgical and non-surgical procedures to guarantee a favourable outcome. Children might experience hemodynamic instability for many reasons, and how the range of normality within brain autoregulation is maintained is still unknown. Neuro-monitoring can guide anaesthesia providers in delivering optimal anaesthetic drugs dosages and also correcting underling conditions that can negatively affect the neurological outcome. In particular, it is referred to EEG-based monitoring and monitoring for brain oxygenation.

The influence of age on EEG-based anaesthesia indices

STUDY OBJECTIVE

In the upcoming years there will be a growing number of elderly patients requiring general anaesthesia. As age is an independent risk factor for postoperative delirium (POD) the incidence of POD will increase concordantly. One approach to reduce the risk of POD would be to avoid excessively high doses of anaesthetics by using neuromonitoring to guide anaesthesia titration. Therefore, we evaluated the influence of patient's age on various electroencephalogram (EEG)-based anaesthesia indices.

DESIGN AND PATIENTS

We conducted an analysis of previously published data by replaying single electrode EEG episodes of maintenance of general anaesthesia from 180 patients (18-90 years; ASA I-IV) into the five different commercially available monitoring systems and evaluated their indices. We included the State/Response Entropy, Narcotrend, qCON/qNOX, bispectral index (BIS), and Treaton MGA-06. For a non-commercial comparison, we extracted the spectral edge frequency (SEF) from the BIS. To evaluate the influence of the age we generated linear regression models. We also assessed the correlation between the various indices.

MAIN RESULTS

During anaesthetic maintenance the values of the SEF, State/Response Entropy, qCON/qNOX and BIS all significantly increased (0.05 Hz/0.19-0.26 index points per year) with the patient's age (p < 0.001); whereas the Narcotrend did not change significantly with age (0.06 index points per year; p = 0.28). The index values of the Treaton device significantly decreased with age (-0.09 index points per year; p < 0.001). These findings were independent of the administered dose of anaesthetics.

CONCLUSIONS

Almost all current neuromonitoring devices are influenced by age, with the potential to result in inappropriately high dosage of anaesthetics. Therefore, anaesthesiologists should be aware of this phenomenon, and the next generation of monitors should correct for these changes.

The Relationship between the Timing of Sugammadex Administration and the Upper Airway Obstruction during Awakening from Anesthesia: A Retrospective Study

Background and Objectives: The harmonization of recovery of consciousness and muscular function is important in emergence from anesthesia. Even if muscular function is recovered, tracheal extubation without adequate recovery of consciousness may increase the risk of respiratory complications. In particular, upper airway obstruction is one of the common respiratory complications and can sometimes be fatal. However, the association between the timing of sugammadex administration and the upper airway obstruction that can occur during awakening from anesthesia has rarely been studied. Materials and Methods: The medical records of 456 patients who had surgery under general endotracheal anesthesia (GETA) at the Haeundae Paik Hospital between October 2017 and July 2018 and who received intravenous sugammadex to reverse rocuronium-induced neuromuscular blockade were analyzed. The correlations between bispectral index (BIS) and minimum alveolar concentration (MAC) at the time of sugammadex administration, the incidence of complications, and the time to tracheal extubation were analyzed to investigate how different timings of sugammadex administration affected upper airway obstruction after tracheal extubation. Conclusions: The effect of BIS and the duration from anesthetic discontinuation to sugammadex administration on upper airway obstruction was not statistically significant. However, the odds ratio of complication rates with MAC < 0.3 compared with MAC ≥ 0.3 was 0.40 (95% confidence interval 0.20 to 0.81, p = 0.011), showing a statistically significant increase in risk with MAC ≥ 0.3 for upper airway obstruction.

Polyspikes and Rhythmic Polyspikes During Volatile Induction of General Anesthesia With Sevoflurane Result in Bispectral Index Variations

BACKGROUND

Although electroencephalography (EEG)-based indices may show artifactual values, raw EEG signal is seldom used to monitor the depth of volatile induction of general anesthesia (VIGA). The current analysis aimed to identify whether bispectral index (BIS) variations reliably reflect the actual depth of general anesthesia during presence of different types of epileptiform patterns (EPs) in EEGs during induction of general anesthesia.

METHODS

Sixty patients receiving either VIGA with sevoflurane using increasing concentrations (group VIMA) or vital capacity (group VCRII) technique or intravenous single dose of propofol (group PROP) were included. Monitoring included facial electromyography (fEMG), fraction of inspired sevoflurane (FiAA), fraction of expired sevoflurane (FeAA), minimal alveolar concentration (MAC) of sevoflurane, BIS, standard EEG, and hemodynamic parameters.

RESULTS

In the PROP group no EPs were observed. During different stages of VIGA with sevoflurane in the VIMA and VCRII groups, presence of polyspikes and rhythmic polyspikes in patients' EEGs resulted in artifactual BIS values indicating a false awareness/wakefulness from anesthesia, despite no concomitant change of FiAA, FeAA, and MAC of sevoflurane. Periodic epileptiform discharges did not result in aberrant BIS values.

CONCLUSION

Our results suggest that raw EEG correlate it with values of BIS, FiAA, FeAA, and MAC of sevoflurane during VIGA. It seems that because artifactual BIS values indicating false awareness/wakefulness as a result of presence of polyspikes and rhythmic polyspikes in patients' EEGs may be misleading to an anesthesiologist, leading to unintentional administration of toxic concentration of sevoflurane in ventilation gas.

Neuromonitoring during general anesthesia in non-neurologic surgery

Cerebral complications are common in perioperative settings even in non-neurosurgical procedures. These include postoperative cognitive dysfunction or delirium as well as cerebrovascular accidents. During surgery, it is essential to ensure an adequate degree of sedation and analgesia, and at the same time, to provide hemodynamic and respiratory stability in order to minimize neurological complications. In this context, the role of neuromonitoring in the operating room is gaining interest, even in the non-neurolosurgical population. The use of multimodal neuromonitoring can potentially reduce the occurrence of adverse effects during and after surgery, and optimize the administration of anesthetic drugs. In addition to the traditional focus on monitoring hemodynamic and respiratory systems during general anesthesia, the ability to constantly monitor the activity and maintenance of brain homeostasis, creating evidence-based protocols, should also become part of the standard of care: in this challenge, neuromonitoring comes to our aid. In this review, we aim to describe the role of the main types of noninvasive neuromonitoring such as those based on electroencephalography (EEG) waves (EEG, Entropy module, Bispectral Index, Narcotrend Monitor), near-infrared spectroscopy (NIRS) based on noninvasive measurement of cerebral regional oxygenation, and Transcranial Doppler used in the perioperative settings in non-neurosurgical intervention. We also describe the advantages, disadvantage, and limitation of each monitoring technique.

Influence of an "Electroencephalogram-Based" Monitor Choice on the Delay Between the Predicted Propofol Effect-Site Concentration and the Measured Drug Effect

BACKGROUND

Clinicians can optimize propofol titration by using 2 sources of pharmacodynamic (PD) information: the predicted effect-site concentration for propofol (Ceprop) and the electroencephalographically (EEG) measured drug effect. Relation between these sources should be time independent, that is, perfectly synchronized. In reality, various issues corrupt time independency, leading to asynchrony or, in other words, hysteresis. This asynchrony can lead to conflicting information, making effective drug dosing challenging. In this study, we tried to quantify and minimize the hysteresis between the Ceprop (calculated using the Schnider model for propofol) and EEG measured drug effect, using nonlinear mixed-effects modeling (NONMEM). Further, we measured the influence of EEG-based monitor choice, namely Bispectral index (BIS) versus qCON index (qCON) monitor, on propofol PD hysteresis.

METHODS

We analyzed the PD data from 165 patients undergoing propofol-remifentanil anesthesia for outpatient surgery. Drugs were administered using target-controlled infusion (TCI) pumps. Pumps were programmed with Schnider model for propofol and Minto model for remifentanil. We constructed 2 PD models (direct models) relating the Schnider Ceprop to the measured BIS and qCON monitor values. We quantified the models' misspecification due to hysteresis, on an individual level, using the root mean squared errors (RMSEs). Subsequently, we optimized the PD models' predictions by adding a lag term to both models (lag-time PD models) and quantified the optimization using the RMSE.

RESULTS

There is a counterclockwise hysteresis between Ceprop and BIS/qCON values. Not accounting for this hysteresis results in a direct PD model with an effect-site concentration which produces 50% of the maximal drug effect (Ce50) of 6.24 and 8.62 µg/mL and RMSE (median and interquartile range [IQR]) of 9.38 (7.92-11.23) and 8.41(7.04-10.2) for BIS and qCON, respectively. Adding a modeled lag factor of 49 seconds to the BIS model and 53 seconds to the qCON model improved both models' prediction, resulting in similar Ce50 (3.66 and 3.62 µg/mL for BIS and qCON) and lower RMSE (median (IQR) of 7.87 (6.49-9.90) and 6.56 (5.28-8.57) for BIS and qCON.

CONCLUSIONS

There is a significant "Ceprop versus EEG measured drug effect" hysteresis. Not accounting for it leads to conflicting PD information and false high Ce50 for propofol in both monitors. Adding a lag term improved the PD model performance, improved the "pump-monitor" synchrony, and made the estimates of Ce50 for propofol more realistic and less monitor dependent.

A Real-Time Depth of Anesthesia Monitoring System Based on Deep Neural Network With Large EDO Tolerant EEG Analog Front-End

In this article, we present a real-time electroencephalogram (EEG) based depth of anesthesia (DoA) monitoring system in conjunction with a deep learning framework, AnesNET. An EEG analog front-end (AFE) that can compensate ±380-mV electrode DC offset using a coarse digital DC servo loop is implemented in the proposed system. The EEG-based MAC, EEGMAC, is introduced as a novel index to accurately predict the DoA, which is designed for applying to patients anesthetized by both volatile and intravenous agents. The proposed deep learning protocol consists of four layers of convolutional neural network and two dense layers. In addition, we optimize the complexity of the deep neural network (DNN) to operate on a microcomputer such as the Raspberry Pi 3, realizing a cost-effective small-size DoA monitoring system. Fabricated in 110-nm CMOS, the prototype AFE consumes 4.33 μW per channel and has the input-referred noise of 0.29 μVrms from 0.5 to 100 Hz with the noise efficiency factor of 2.2. The proposed DNN was evaluated with pre-recorded EEG data from 374 subjects administrated by inhalational anesthetics under surgery, achieving an average squared and absolute errors of 0.048 and 0.05, respectively. The EEGMAC with subjects anesthetized by an intravenous agent also showed a good agreement with the bispectral index value, confirming the proposed DoA index is applicable to both anesthetics. The implemented monitoring system with the Raspberry Pi 3 estimates the EEGMAC within 20 ms, which is about thousand-fold faster than the BIS estimation in literature.

Target-controlled propofol infusion with or without bispectral index monitoring of sedation during advanced gastrointestinal endoscopy

BACKGROUND AND AIM

Target-controlled infusion (TCI) uses averaged pharmacokinetic datasets derived from population samples to automatically control the infusion rate. Bispectral index (BIS) technology non-invasively measures levels of consciousness during surgical procedures. We compared the efficacy and safety of propofol TCI with or without BIS monitoring for sedation during advanced gastrointestinal endoscopy.

METHODS

This prospective study enrolled 200 patients who were premedicated with midazolam 2 mg and alfentanil 0.4 mg before undergoing advanced gastrointestinal endoscopy. The initial target blood concentration of propofol was set at 1.0 μg/mL, and adjustments of 0.2 μg/mL were made as necessary to maintain moderate-to-deep sedation. Patients were randomized to either the BIS-blind group and evaluated for depth of anesthesia by monitoring scores of 1-2 on the Modified Observer's Assessment of Alertness/Sedation scale (n = 100) or to the BIS-open group and monitored by BIS scores of 60-80 (n = 100). The primary outcome was the total amount of propofol required to maintain anesthesia. Secondary outcomes were sedation-induced adverse events, recovery, and quality of sedation (endoscopist and patient satisfaction).

RESULTS

The mean propofol infusion rate was significantly higher in patients not monitored by BIS scores than in those who were (5.44 ± 2.12 vs 4.76 ± 1.84 mg/kg/h; P = 0.016). Levels of satisfaction were higher for endoscopists who used BIS monitoring than in those who did not.

CONCLUSIONS

Mean infusion rates were higher in propofol TCI without BIS monitoring compared with propofol TCI with BIS during advanced gastrointestinal endoscopy. Endoscopists expressed satisfaction with BIS monitoring.

Variations in Values of State, Response Entropy and Haemodynamic Parameters Associated with Development of Different Epileptiform Patterns during Volatile Induction of General Anaesthesia with Two Different Anaesthetic Regimens Using Sevoflurane in Comparison with Intravenous Induct: A Comparative Study

BACKGROUND AND OBJECTIVES

Raw electroencephalographic (EEG) signals are rarely used to monitor the depth of volatile induction of general anaesthesia (VIGA) with sevoflurane, even though EEG-based indices may show aberrant values. We aimed to identify whether response (RE) and state entropy (SE) variations reliably reflect the actual depth of general anaesthesia in the presence of different types of epileptiform patterns (EPs) in EEGs during induction of general anaesthesia.

MATERIALS AND METHODS

A randomized, prospective clinical study was performed with 60 patients receiving VIGA using sevoflurane with the increasing concentrations (group VIMA) or the vital capacity (group VCRII) technique or an intravenous single dose of propofol (group PROP). Facial electromyography (fEMG), fraction of inspired sevoflurane (FiAA), fraction of expired sevoflurane (FeAA), minimal alveolar concentration (MAC) of sevoflurane, RE and SE, and standard electroencephalographic evaluations were performed in these patients.

RESULTS

In contrast to periodic epileptiform discharges, erroneous SE and RE values in the patients' EEGs were associated with the presence of polyspikes (PS) and rhythmic polyspikes (PSR), which were more likely to indicate toxic depth rather than false emergence from anaesthesia with no changes in the FiAA, FeAA, and MAC of sevoflurane.

CONCLUSION

Calculated RE and SE values may be misleading during VIGA when EPs are present in patients' EEGs. During VIGA with sevoflurane, we recommend monitoring raw EEG data in scientific studies to correlate it with potentially erroneous RE and SE values and the end-tidal concentration of sevoflurane in everyday clinical practice, when monitoring raw EEG is not available, because they can mislead anaesthesiologists to reduce sevoflurane levels in the ventilation gas and result in unintentional true emergence from anaesthesia. Further studies are required to investigate the behaviour of EEG-based indices during rapid changes in sevoflurane concentrations at different stages of VIGA and the influence of polyspikes and rhythmic polyspikes on the transformation of EEG signals into a digital form.

Practical Training of Anesthesia Clinicians in Electroencephalogram-Based Determination of Hypnotic Depth of General Anesthesia

BACKGROUND

Electroencephalographic (EEG) brain monitoring during general anesthesia provides information on hypnotic depth. We hypothesized that anesthesia clinicians could be trained rapidly to recognize typical EEG waveforms occurring with volatile-based general anesthesia.

METHODS

This was a substudy of a trial testing the hypothesis that EEG-guided anesthesia prevents postoperative delirium. The intervention was a 35-minute training session, summarizing typical EEG changes with volatile-based anesthesia. Participants completed a preeducational test, underwent training, and completed a posteducational test. For each question, participants indicated whether the EEG was consistent with (1) wakefulness, (2) non-slow-wave anesthesia, (3) slow-wave anesthesia, or (4) burst suppression. They also indicated whether the processed EEG (pEEG) index was discordant with the EEG waveforms. Four clinicians, experienced in intraoperative EEG interpretation, independently evaluated the EEG waveforms, resolved disagreements, and provided reference answers. Ten questions were assessed in the preeducational test and 9 in the posteducational test.

RESULTS

There were 71 participants; 13 had previous anesthetic-associated EEG interpretation training. After training, the 58 participants without prior training improved at identifying dominant EEG waveforms (median 60% with interquartile range [IQR], 50%-70% vs 78% with IQR, 67%-89%; difference: 18%; 95% confidence interval [CI], 8-27; P < .001). In contrast, there was no significant improvement following the training for the 13 participants who reported previous training (median 70% with IQR, 60%-80% vs 67% with IQR, 67%-78%; difference: -3%; 95% CI, -18 to 11; P = .88). The difference in the change between the pre- and posteducational session for the previously untrained versus previously trained was statistically significant (difference in medians: 21%; 95% CI, 2-28; P = .005). Clinicians without prior training also improved in identifying discordance between the pEEG index and the EEG waveform (median 60% with IQR, 40%-60% vs median 100% with IQR, 75%-100%; difference: 40%; 95% CI, 30-50; P < .001). Clinicians with prior training showed no significant improvement (median 60% with IQR, 60%-80% vs 75% with IQR, 75%-100%; difference: 15%; 95% CI, -16 to 46; P = .16). Regarding the identification of discordance, the difference in the change between the pre- and posteducational session for the previously untrained versus previously trained was statistically significant (difference in medians: 25%; 95% CI, 5-45; P = .012).

CONCLUSIONS

A brief training session was associated with improvements in clinicians without prior EEG training in (1) identifying EEG waveforms corresponding to different hypnotic depths and (2) recognizing when the hypnotic depth suggested by the EEG was discordant with the pEEG index.

Spectral and Entropic Features Are Altered by Age in the Electroencephalogram in Patients under Sevoflurane Anesthesia

BACKGROUND

Preexisting factors such as age and cognitive performance can influence the electroencephalogram (EEG) during general anesthesia. Specifically, spectral EEG power is lower in elderly, compared to younger, subjects. Here, the authors investigate age-related changes in EEG architecture in patients undergoing general anesthesia through a detailed examination of spectral and entropic measures.

METHODS

The authors retrospectively studied 180 frontal EEG recordings from patients undergoing general anesthesia, induced with propofol/fentanyl and maintained by sevoflurane at the Waikato Hospital in Hamilton, New Zealand. The authors calculated power spectral density and normalized power spectral density, the entropic measures approximate and permutation entropy, as well as the beta ratio and spectral entropy as exemplary parameters used in current monitoring systems from segments of EEG obtained before the onset of surgery (i.e., with no noxious stimulation).

RESULTS

The oldest quartile of patients had significantly lower 1/f characteristics (P < 0.001; area under the receiver operating characteristics curve, 0.84 [0.76 0.92]), indicative of a more uniform distribution of spectral power. Analysis of the normalized power spectral density revealed no significant impact of age on relative alpha (P = 0.693; area under the receiver operating characteristics curve, 0.52 [0.41 0.63]) and a significant but weak effect on relative beta power (P = 0.041; area under the receiver operating characteristics curve, 0.62 [0.52 0.73]). Using entropic parameters, the authors found a significant age-related change toward a more irregular and unpredictable EEG (permutation entropy: P < 0.001, area under the receiver operating characteristics curve, 0.81 [0.71 0.90]; approximate entropy: P < 0.001; area under the receiver operating characteristics curve, 0.76 [0.66 0.85]). With approximate entropy, the authors could also detect an age-induced change in alpha-band activity (P = 0.002; area under the receiver operating characteristics curve, 0.69 [0.60 78]).

CONCLUSIONS

Like the sleep literature, spectral and entropic EEG features under general anesthesia change with age revealing a shift toward a faster, more irregular, oscillatory composition of the EEG in older patients. Age-related changes in neurophysiological activity may underlie these findings however the contribution of age-related changes in filtering properties or the signal to noise ratio must also be considered. Regardless, most current EEG technology used to guide anesthetic management focus on spectral features, and improvements to these devices might involve integration of entropic features of the raw EEG.

The effects of different doses of dexmedetomidine on the requirements for propofol for loss of consciousness in patients monitored via the bispectral index: a double-blind, placebo-controlled trial

BACKGROUND

The α₂-adrenergic agonist dexmedetomidine (DEX) is a sedative and can be used as an adjunct to hypnotics. The study sought to evaluate the effects of different doses of DEX on the requirements for propofol for loss of consciousness (LOC) in patients monitored via the bispectral index (BIS).

METHODS

In this randomized, double-blind, three arm parallel group design and placebo-controlled trial, 73 patients aged between 18 and ~ 65 years with a BMI range of 18.0-24.5 kg·m^- 2 and an American Society of Anesthesiologists (ASA) grade I or II who were scheduled for general anesthesia at the General Hospital of Ningxia Medical University were included in this study. Anesthesiologists and patients were blinded to the syringe contents. All patients were randomly assigned in a 1:1:1 ratio to receive a 0.5 μg·kg^- 1 DEX infusion (0.5 μg·kg^- 1 DEX group; n = 24), a 1.0 μg·kg^- 1 DEX infusion (1.0 μg·kg^- 1 DEX group; n = 25) or a saline infusion (control group; n = 24) for 10 min. Propofol at a concentration of 20 mg·kg^- 1·h^- 1 was then infused at the end of the DEX or saline infusion. The propofol infusion was stopped when the patient being infused lost consciousness. The primary endpoint were propofol requirements for LOC and BIS value at LOC.

RESULTS

The data from 73 patients were analyzed. The propofol requirements for LOC was reduced in the DEX groups compared with the control group (1.12 ± 0.33 mg·kg^- 1 for the 0.5 μg·kg^- 1 DEX group vs. 1.79 ± 0.39 mg·kg^- 1 for the control group; difference, 0.68 mg·kg^- 1 [95% CI, 0.49 to 0.87]; P = 0.0001) (0.77 ± 0.27 mg·kg^- 1 for the 1.0 μg·kg^- 1 DEX group vs. 1.79 ± 0.39 mg·kg^- 1 for the control group; difference, 1.02 mg·kg^- 1 [95% CI, 0.84 to 1.21]; P = 0.0001). The propofol requirements for LOC was lower in the 1.0 μg·kg^- 1 DEX group than the 0.5 μg·kg^- 1 DEX group (0.77 ± 0.27 mg·kg^- 1 vs. 1.12 ± 0.33 mg·kg^- 1, respectively; difference, 0.34 mg·kg^- 1 [95% CI, 0.16 to 0.54]; P = 0.003). At the time of LOC, the BIS value was higher in the DEX groups than in the control group (67.5 ± 3.5 for group 0.5 μg·kg^- 1 DEX vs. 60.5 ± 3.8 for the control group; difference, 7.04 [95% CI, 4.85 to 9.23]; P = 0.0001) (68.4 ± 4.1 for group 1.0 μg·kg^- 1 DEX vs. 60.5 ± 3.8 for the control group; difference, 7.58 [95% CI, 5.41 to 9.75]; P = 0.0001).

CONCLUSION

The study showed that DEX (both 0.5 and 1.0 μg·kg^- 1 DEX) reduced the propofol requirements for LOC. DEX pre-administration increased the BIS value for LOC induced by propofol.

CLINICAL TRIAL REGISTRATION

The study was registered at ClinicalTrials.gov (trial ID: NCT02783846 on May 26, 2016).

Comparison of electroencephalogram between propofol- and thiopental-induced anesthesia for awareness risk in pregnant women

There have been few comparative studies using electroencephalogram (EEG) spectral characteristics during the induction of general anesthesia for cesarean section. This retrospective study investigated the differences in the depth of anesthesia through EEG analysis between propofol- and thiopental-induced anesthesia. We reviewed data of 42 patients undergoing cesarean section who received either thiopental (5 mg/kg) or propofol (2 mg/kg). EEG data were extracted from the bispectral index (BIS) monitor, and 10-second segments were selected from the following sections: 1) Stage I, BIS below 60 after induction; 2) Stage II, after intubation completion; 3) Stage III, end-tidal sevoflurane above 0 vol%. The risk of awareness was represented by the BIS and entropy measures. In Stage III, the thiopental group (n = 20) showed significantly higher BIS value than the propofol group (n = 22) (67.9 [18.66] vs 44.5 [20.63], respectively, p = 0.002). The thiopental group had decreased slow-delta oscillations and increased beta-oscillations as compared to the propofol group in Stages II and III (p < 0.05). BIS, spectral entropy, and Renyi permutation entropy were also higher in the thiopental group at Stages II and III (p < 0.05). In conclusion, frontal spectral EEG analysis demonstrated that propofol induction maintained a deeper anesthesia than thiopental in pregnant women.

Time delay of the qCON monitor and its performance during state transitions

We investigated the performance of the qCON index regarding its time delay for sudden changes in the anesthetic level as well as to separate responsiveness from unresponsiveness during loss and return of responsiveness (LOR and ROR). For evaluation of the time delay, we replayed relevant EEG episodes to the qCON to simulate sudden changes between the states (i) awake/sedation, (ii) adequate anesthesia, or (iii) suppression. We also replayed EEG from 40 patients during LOR and ROR to evaluate the qCON’s ability to separate responsiveness from unresponsiveness. The time delays depended on the type of transition. The delays for the important transition between awake/sedation and adequate anesthesia were 21(5) s from awake/sedation to adequate anesthesia and 26(5) s in the other direction. The performance of the qCON to separate responsiveness from unresponsiveness depended on signal quality, the investigation window, i.e. ± 30 s or ± 60 s around LOR/ROR, and the specific transition being tested. AUC was 0.63–0.90 for LOR and 0.61–0.79 for ROR. Time delay and performance during state transitions of the qCON were similar to other monitoring systems such as bispectral index. The better performance of qCON during LOR than ROR probably reflects the sudden change in EEG activity during LOR and the more heterogeneous EEG during ROR.

Electroencephalography and Brain Oxygenation Monitoring in the Perioperative Period

Maintaining brain function and integrity is a pivotal part of anesthesiological practice. The present overview aims to describe the current role of the 2 most frequently used monitoring methods for evaluation brain function in the perioperative period, ie, electroencephalography (EEG) and brain oxygenation monitoring. Available evidence suggests that EEG-derived parameters give additional information about depth of anesthesia for optimizing anesthetic titration. The effects on reduction of drug consumption or recovery time are heterogeneous, but most studies show a reduction of recovery times if anesthesia is titrated along processed EEG. It has been hypothesized that future EEG-derived indices will allow a better understanding of the neurophysiological principles of anesthetic-induced alteration of consciousness instead of the probabilistic approach most often used nowadays.Brain oxygenation can be either measured directly in brain parenchyma via a surgical burr hole, estimated from the venous outflow of the brain via a catheter in the jugular bulb, or assessed noninvasively by near-infrared spectroscopy. The latter method has increasingly been accepted clinically due to its ease of use and increasing evidence that near-infrared spectroscopy-derived cerebral oxygen saturation levels are associated with neurological and/or general perioperative complications and increased mortality. Furthermore, a goal-directed strategy aiming to avoid cerebral desaturations might help to reduce these complications. Recent evidence points out that this technology may additionally be used to assess autoregulation of cerebral blood flow and thereby help to titrate arterial blood pressure to the individual needs and for bedside diagnosis of disturbed autoregulation.

Automated tracking of level of consciousness and delirium in critical illness using deep learning

Over- and under-sedation are common in the ICU, and contribute to poor ICU outcomes including delirium. Behavioral assessments, such as Richmond Agitation-Sedation Scale (RASS) for monitoring levels of sedation and Confusion Assessment Method for the ICU (CAM-ICU) for detecting signs of delirium, are often used. As an alternative, brain monitoring with electroencephalography (EEG) has been proposed in the operating room, but is challenging to implement in ICU due to the differences between critical illness and elective surgery, as well as the duration of sedation. Here we present a deep learning model based on a combination of convolutional and recurrent neural networks that automatically tracks both the level of consciousness and delirium using frontal EEG signals in the ICU. For level of consciousness, the system achieves a median accuracy of 70% when allowing prediction to be within one RASS level difference across all patients, which is comparable or higher than the median technician–nurse agreement at 59%. For delirium, the system achieves an AUC of 0.80 with 69% sensitivity and 83% specificity at the optimal operating point. The results show it is feasible to continuously track level of consciousness and delirium in the ICU.

[Evaluation of Bispectral Index time delay in response to anesthesia induction: an observational study]

BACKGROUND AND OBJECTIVES

According to the manufacturer, the Bispectral Index (BIS) has a processing time delay of 5-10s. Studies addressing this have suggested longer delays. We evaluated the time delay in the Bispectral Index response.

METHODS

Based on clinical data from 45 patients, using the difference between the predicted and the real BIS, calculated during a fixed 3minutes period after the moment the Bispectral Index dropped below 80 during the induction of general anesthesia with propofol and remifentanil.

RESULTS

The difference between the predicted and the real BIS was in average 30.09±18.73s.

CONCLUSION

Our results may be another indication that the delay in BIS processing may be much longer than stated by the manufacture, a fact with clinical implications.

Brain Monitoring of Sedation in the Intensive Care Unit Using a Recurrent Neural Network

Over and under-sedation are common in critically ill patients admitted to the Intensive Care Unit. Clinical assessments provide limited time resolution and are based on behavior rather than the brain itself. Existing brain monitors have been developed primarily for non-ICU settings. Here, we use a clinical dataset from 154 ICU patients in whom the Richmond Agitation-Sedation Score is assessed about every 2 hours. We develop a recurrent neural network (RNN) model to discriminate between deep vs. no sedation, trained end-to-end from raw EEG spectrograms without any feature extraction. We obtain an average area under the ROC of 0.8 on 10-fold cross validation across patients. Our RNN is able to provide reliable estimates of sedation levels consistently better compared to a feed-forward model with simple smoothing. Decomposing the prediction error in terms of sedatives reveals that patient-specific calibration for sedatives is expected to further improve sedation monitoring.

Evaluation of Bispectral Index time delay in response to anesthesia induction: an observational study

Background and objectives

According to the manufacturer, the Bispectral Index (BIS) has a processing time delay of 5–10 s. Studies addressing this have suggested longer delays. We evaluated the time delay in the Bispectral Index response.

Methods

Based on clinical data from 45 patients, using the difference between the predicted and the real BIS, calculated during a fixed 3 minutes period after the moment the Bispectral Index dropped below 80 during the induction of general anesthesia with propofol and remifentanil.

Results

The difference between the predicted and the real BIS was in average 30.09 ± 18.73 s.

Conclusion

Our results may be another indication that the delay in BIS processing may be much longer than stated by the manufacture, a fact with clinical implications.

Pharmacokinetics and pharmacodynamics of propofol: changes in patients with frontal brain tumours

Background

Models of propofol pharmacokinetics and pharmacodynamics developed in patients without brain pathology are widely used for target-controlled infusion (TCI) during brain tumour excision operations. The goal of this study was to determine if the presence of a frontal brain tumour influences propofol pharmacokinetics and pharmacodynamics and existing PK-PD model performance.

Methods

Twenty patients with a frontal brain tumour and 20 control patients received a propofol infusion to achieve an induction-emergence-induction anaesthetic sequence. Propofol plasma concentration was measured every 4 min and at each transition of the conscious state. Bispectral index (BIS) values were continuously recorded. We used non-linear mixed-effects modelling to analyse the effects of the presence of a brain tumour on the pharmacokinetics and pharmacodynamics of propofol. Subsequently we calculated the predictive performance of Marsh, Schnider, and Eleveld models in terms of median prediction error (MdPE) and median absolute prediction error (MdAPE).

Results

Patients with brain tumours showed 40% higher propofol clearance than control patients. Performance of the Schnider model (MdPEpk -20.0%, MdAPEpk 23.4%) and Eleveld volunteer model (MdPEpk -8.58%, MdAPEpk 21.6%) were good. The Marsh model performed less well (MdPEpk -14.3%, MdAPEpk 41.4%), as did the Eleveld patient model (MdPEpk -30.8%, MdAPEpk 32.1%).

Conclusions

Brain tumours might alter the pharmacokinetics of propofol. Caution should be exerted when using propofol TCI in patients with frontal brain tumours due to higher clearance.

Trial registry number

NCT01060631.

Electroencephalographic (EEG) density spectral array monitoring in children during sevoflurane anaesthesia: a prospective observational study

Electroencephalographic density spectral array monitoring has been developed to facilitate the interpretation of unprocessed electroencephalogram signals. The primary aim of this prospective observational study, performed in a tertiary children's hospital, was to identify the clinical applicability and validity of density spectral array monitoring in infants and children during sevoflurane anaesthesia. We included 104 children, aged < 6 years, undergoing elective surgery during sevoflurane anaesthesia. We investigated the correlation between non‐steady state end‐tidal sevoflurane and the expression of the four electroencephalogram frequency bands β, α, θ and δ, representing density spectral array. Patients were divided into three age groups (< 6 months, 6–12 months, > 12 months). There was a significant correlation between end‐tidal sevoflurane and density spectral array in the age groups 6–12 months (p < 0.05) and 1–6 years (p < 0.0001). In infants < 6 months of age, the relative percentages of density spectral array did not correlate with end‐tidal sevoflurane. The main finding was that different end‐tidal concentrations of sevoflurane produce age‐dependent changes in the density spectral array power spectrum. In infants younger than 6 months‐old, α and β coherence are absent, whereas θ and δ oscillations have already emerged. In cases where anaesthesia was too deep, this presented as burst suppression on the electroencephalogram, θ disappeared, leaving the electroencephalographic activity in the δ range. Future research should address this issue, aiming to clarify whether the emergence of θ oscillations in infants helps to prevent sevoflurane overdosing.

Handgrip dynamometry for continuous assessment of volitional control during induction of anesthesia: a prospective observational study

PURPOSE

Response to commands is the gold standard to assess the level of consciousness during anesthesia induction but it only provides an intermittent, binary measure with low temporal resolution. To overcome these limitations, we combined the object hold method with handgrip dynamometry to continuously record the force applied to hold a dynamometer as a surrogate measure of the level of consciousness during induction of anesthesia.

METHODS

Fourteen patients scheduled for elective lumbar surgery and 14 age-matched non-anesthetized controls were enrolled. The subjects held the dynamometer with their dominant hand for as long as possible (patients) or until told to stop (controls). After a one-minute baseline, propofol was infused (1.0 mg·kg^-1·min^-1) to the patient group until the subject dropped the dynamometer, which defined the object hold time. Three additional patients were also asked intermittently to squeeze the dynamometer during the propofol infusion to determine any retained ability to exert a strong grip despite any grip changes during induction.

RESULTS

The mean (standard deviation) object hold time was 115 (22) seconds after the start of the propofol infusion. There was a progressive significant linear decrease (R² = 0.98; P < 0.001) in dynamometry-determined handgrip force starting approximately 74 seconds before object drop. Age was inversely related to the object hold time (R² = 0.47, P < 0.01). The three additional propofol induction patients had strong intermittent grip strength despite progressive decreases in the hold force. Of the 17 patients who completed the object hold task (14 with the standard protocol and three with intermittent squeeze requests), 16 (94%; 95% confidence interval, 76 to 99%) did not respond to verbal commands after dropping the dynamometer.

CONCLUSION

Handgrip dynamometry can be used to continuously track volitional control during induction of anesthesia while also reliably showing a gradual loss of consciousness. This method could be useful for studies investigating mechanisms of anesthesia.

The prediction probabilities for emergence from sevoflurane anesthesia in children: A comparison of the perfusion index and the bispectral index

BACKGROUND

Predicting recovery of consciousness is one of the most essential functions of anesthesia depth monitors in anesthesia practice. Perfusion index and bispectral index are 2 indicators of the anesthesia depth monitoring with different working principles. The progression of the anesthesia emergence stages reflected by those monitors has not been well understood, especially in pediatric patients. The goals of this study were to compare the prediction probabilities of perfusion index and bispectral index in predicting awakening and in differentiating the different levels of arousal during emergence after sevoflurane anesthesia in children undergoing open inguinal hernia repairs.

METHODS

Forty-five patients, aged 1 to 5 years, ASA Status I or II and scheduled for elective open inguinal hernia repairs under general anesthesia were enrolled. The perfusion index and bispectral index were monitored simultaneously during anesthesia recovery. The University of Michigan Sedation Scale was applied to evaluate the clinical arousal levels during emergence. The prediction probability was used to assess the performance of perfusion index and bispectral index in predicting awakening and distinguishing different levels of arousal corresponding to the University of Michigan Sedation Scale during recovery.

RESULTS

The prediction probability of perfusion index (Pk_PI-Awakening  = .81, 95% CI 0.73-0.89) in differentiating full consciousness from unconsciousness during recovery was comparable to that of bispectral index (Pk_{BIS- Awakening}  = .86, 95% CI 0.79-0.92) (P = .47). The prediction probability for perfusion index (Pk_PI-UMSS  = .61, 95% CI 0.55-0.73) and bispectral index (Pk_BIS-UMSS  = .64, 95% CI 0.53-0.69) had similar performance in distinguishing different University of Michigan Sedation Scale levels.

CONCLUSION

Both the perfusion index and bispectral index performed comparably well in predicting awakening and different arousal levels when emerging from sevoflurane anesthesia in children.

Awareness and Aortocaval Obstruction in Obstetric Anesthesia

Awareness during general anesthesia for cesarean delivery continues to be a major problem. The key to preventing awareness is strict attention to anesthetic technique. The prevalence and implications of aortocaval compression have been firmly established. Compression of the vena cava is a real occurrence when assuming the supine position. Relief of this compression most likely does not occur until the patient is turned 30°, which is not feasible for performing cesarean delivery. Although it is still wise to tilt the patient, the benefit of this tilt may not be as great as once thought.

Differences between state entropy and bispectral index during analysis of identical electroencephalogram signals: a comparison with two randomised anaesthetic techniques

BACKGROUND

It is claimed that bispectral index (BIS) and state entropy reflect an identical clinical spectrum, the hypnotic component of anaesthesia. So far, it is not known to what extent different devices display similar index values while processing identical electroencephalogram (EEG) signals.

OBJECTIVE

To compare BIS and state entropy during analysis of identical EEG data. Inspection of raw EEG input to detect potential causes of erroneous index calculation.

DESIGN

Offline re-analysis of EEG data from a randomised, single-centre controlled trial using the Entropy Module and an Aspect A-2000 monitor.

SETTING

Klinikum rechts der Isar, Technische Universität München, Munich.

PATIENTS

Forty adult patients undergoing elective surgery under general anaesthesia.

INTERVENTIONS

Blocked randomisation of 20 patients per anaesthetic group (sevoflurane/remifentanil or propofol/remifentanil). Isolated forearm technique for differentiation between consciousness and unconsciousness.

MAIN OUTCOME MEASURES

Prediction probability (PK) of state entropy to discriminate consciousness from unconsciousness. Correlation and agreement between state entropy and BIS from deep to light hypnosis. Analysis of raw EEG compared with index values that are in conflict with clinical examination, with frequency measures (frequency bands/Spectral Edge Frequency 95) and visual inspection for physiological EEG patterns (e.g. beta or delta arousal), pathophysiological features such as high-frequency signals (electromyogram/high-frequency EEG or eye fluttering/saccades), different types of electro-oculogram or epileptiform EEG and technical artefacts.

RESULTS

PK of state entropy was 0.80 and of BIS 0.84; correlation coefficient of state entropy with BIS 0.78. Nine percent BIS and 14% state entropy values disagreed with clinical examination. Highest incidence of disagreement occurred after state transitions, in particular for state entropy after loss of consciousness during sevoflurane anaesthesia. EEG sequences which led to false 'conscious' index values often showed high-frequency signals and eye blinks. High-frequency EEG/electromyogram signals were pooled because a separation into EEG and fast electro-oculogram, for example eye fluttering or saccades, on the basis of a single EEG channel may not be very reliable. These signals led to higher Spectral Edge Frequency 95 and ratio of relative beta and gamma band power than EEG signals, indicating adequate unconscious classification. The frequency of other artefacts that were assignable, for example technical artefacts, movement artefacts, was negligible and they were excluded from analysis.

CONCLUSION

High-frequency signals and eye blinks may account for index values that falsely indicate consciousness. Compared with BIS, state entropy showed more false classifications of the clinical state at transition between consciousness and unconsciousness.

Robust control of burst suppression for medical coma

OBJECTIVE

Medical coma is an anesthetic-induced state of brain inactivation, manifest in the electroencephalogram by burst suppression. Feedback control can be used to regulate burst suppression, however, previous designs have not been robust. Robust control design is critical under real-world operating conditions, subject to substantial pharmacokinetic and pharmacodynamic parameter uncertainty and unpredictable external disturbances. We sought to develop a robust closed-loop anesthesia delivery (CLAD) system to control medical coma.

APPROACH

We developed a robust CLAD system to control the burst suppression probability (BSP). We developed a novel BSP tracking algorithm based on realistic models of propofol pharmacokinetics and pharmacodynamics. We also developed a practical method for estimating patient-specific pharmacodynamics parameters. Finally, we synthesized a robust proportional integral controller. Using a factorial design spanning patient age, mass, height, and gender, we tested whether the system performed within clinically acceptable limits. Throughout all experiments we subjected the system to disturbances, simulating treatment of refractory status epilepticus in a real-world intensive care unit environment.

MAIN RESULTS

In 5400 simulations, CLAD behavior remained within specifications. Transient behavior after a step in target BSP from 0.2 to 0.8 exhibited a rise time (the median (min, max)) of 1.4 [1.1, 1.9] min; settling time, 7.8 [4.2, 9.0] min; and percent overshoot of 9.6 [2.3, 10.8]%. Under steady state conditions the CLAD system exhibited a median error of 0.1 [-0.5, 0.9]%; inaccuracy of 1.8 [0.9, 3.4]%; oscillation index of 1.8 [0.9, 3.4]%; and maximum instantaneous propofol dose of 4.3 [2.1, 10.5] mg kg(-1). The maximum hourly propofol dose was 4.3 [2.1, 10.3] mg kg(-1) h(-1). Performance fell within clinically acceptable limits for all measures.

SIGNIFICANCE

A CLAD system designed using robust control theory achieves clinically acceptable performance in the presence of realistic unmodeled disturbances and in spite of realistic model uncertainty, while maintaining infusion rates within acceptable safety limits.