The Technology of Processed Electroencephalogram Monitoring Devices for Assessment of Depth of Anesthesia

A nomogram based on quantitative EEG to predict the prognosis of nontraumatic coma patients in the neuro-intensive care unit

OBJECTIVE

We aimed to establish a quantitative electroencephalography-based prognostic prediction model specifically tailored for nontraumatic coma patients to guide clinical work.

METHODS

This retrospective study included 126 patients with nontraumatic coma admitted to the First Affiliated Hospital of Chongqing Medical University from December 2020 to December 2022. Six in-hospital deaths were excluded. The Glasgow Outcome Scale assessed the prognosis at 3 months after discharge. The least absolute shrinkage and selection operator regression analysis and stepwise regression method were applied to select the most relevant predictors. We developed a predictive model using binary logistic regression and then presented it as a nomogram. We assessed the predictive effectiveness and clinical utility of the model.

RESULTS

After excluding six deaths that occurred within the hospital, a total of 120 patients were included in this study. Three predictor variables were identified, including APACHE II score [39.129 (1.4244-1074.9000)], sleep cycle [OR: 0.006 (0.0002-0.1808)], and RAV [0.068 (0.0049-0.9500)]. The prognostic prediction model showed exceptional discriminative ability, with an AUC of 0.939 (95 % CI: 0.899-0.979).

CONCLUSION

A lack of sleep cycles, smaller relative alpha variants, and higher APACHE II scores were associated with a poor prognosis of nontraumatic coma patients in the neurointensive care unit at 3 months after discharge.

CLINICAL IMPLICATION

This study presents a novel methodology for the prognostic assessment of nontraumatic coma patients and is anticipated to play a significant role in clinical practice.

Comparison of hypotension incidence between remimazolam and propofol in patients with hypertension undergoing neurosurgery: prospective, randomized, single-blind trial

BACKGROUND

Remimazolam, a newer benzodiazepine that targets the GABAA receptor, is thought to allow more stable blood pressure management during anesthesia induction. In contrast, propofol is associated with vasodilatory effects and an increased risk of hypotension, particularly in patients with comorbidities. This study aimed to identify medications that can maintain stable vital signs throughout the induction phase.

METHODS

We conducted a single-center, two-group, randomized controlled trial to investigate and compare the incidence of hypotension between remimazolam- and propofol-based total intravenous anesthesia (TIVA). We selected patients aged between 19 and 75 years scheduled for neurosurgery under general anesthesia, who were classified as American Society of Anesthesiologists Physical Status I-III and had a history of hypertension.

RESULTS

We included 94 patients in the final analysis. The incidence of hypotension was higher in the propofol group (91.3%) than in the remimazolam group (85.4%; P = 0.057). There was no significant difference in the incidence of hypotension among the various antihypertensive medications despite the majority of patients being on multiple medications. In comparison with the propofol group, the remimazolam group demonstrated a higher heart rate immediately after intubation.

CONCLUSIONS

Our study indicated that the hypotension incidence of remimazolam-based TIVA was comparable to that of propofol-based TIVA throughout the induction phase of EEG-guided anesthesia. Both remimazolam and propofol may be equally suitable for general anesthesia in patients undergoing neurosurgery.

TRIAL REGISTRATION

Clinicaltrials.gov (NCT05164146).

Intraoperative pediatric electroencephalography monitoring: an updated review

Intraoperative electroencephalography (EEG) monitoring under pediatric anesthesia has begun to attract increasing interest, driven by the availability of pediatric-specific EEG monitors and the realization that traditional dosing methods based on patient movement or changes in hemodynamic response often lead to imprecise dosing, especially in younger infants who may experience adverse events (e.g., hypotension) due to excess anesthesia. EEG directly measures the effects of anesthetics on the brain, which is the target end-organ responsible for inducing loss of consciousness. Over the past ten years, research on anesthesia and computational neuroscience has improved our understanding of intraoperative pediatric EEG monitoring and expanded the utility of EEG in clinical practice. We now have better insights into neurodevelopmental changes in the developing pediatric brain, functional connectivity, the use of non-proprietary EEG parameters to guide anesthetic dosing, epileptiform EEG changes during induction, EEG changes from spinal/regional anesthesia, EEG discontinuity, and the use of EEG to improve clinical outcomes. This review article summarizes the recent literature on EEG monitoring in perioperative pediatric anesthesia, highlighting several of the topics mentioned above.

Intraoperative Neurophysiological Monitoring in Neurosurgery

Intraoperative neurophysiological monitoring (IONM) is a crucial advancement in neurosurgery, enhancing procedural safety and precision. This technique involves continuous real-time assessment of neurophysiological signals, aiding surgeons in timely interventions to protect neural structures. In addition to inherent limitations, IONM necessitates a detailed anesthetic plan for accurate signal recording. Given the growing importance of IONM in neurosurgery, we conducted a narrative review including the most relevant studies about the modalities and their application in different fields of neurosurgery. In particular, this review provides insights for all physicians and healthcare professionals unfamiliar with IONM, elucidating commonly used techniques in neurosurgery. In particular, it discusses the roles of IONM in various neurosurgical settings such as tumoral brain resection, neurovascular surgery, epilepsy surgery, spinal surgery, and peripheral nerve surgery. Furthermore, it offers an overview of the anesthesiologic strategies and limitations of techniques essential for the effective implementation of IONM.

Personalized anesthesia and precision medicine: a comprehensive review of genetic factors, artificial intelligence, and patient-specific factors

Precision medicine, characterized by the personalized integration of a patient's genetic blueprint and clinical history, represents a dynamic paradigm in healthcare evolution. The emerging field of personalized anesthesia is at the intersection of genetics and anesthesiology, where anesthetic care will be tailored to an individual's genetic make-up, comorbidities and patient-specific factors. Genomics and biomarkers can provide more accurate anesthetic protocols, while artificial intelligence can simplify anesthetic procedures and reduce anesthetic risks, and real-time monitoring tools can improve perioperative safety and efficacy. The aim of this paper is to present and summarize the applications of these related fields in anesthesiology by reviewing them, exploring the potential of advanced technologies in the implementation and development of personalized anesthesia, realizing the future integration of new technologies into clinical practice, and promoting multidisciplinary collaboration between anesthesiology and disciplines such as genomics and artificial intelligence.

γ-Aminobutyric Acid-Ergic Development Contributes to the Enhancement of Electroencephalogram Slow-Delta Oscillations Under Volatile Anesthesia in Neonatal Rats

BACKGROUND

General anesthetics (eg, propofol and volatile anesthetics) enhance the slow-delta oscillations of the cortical electroencephalogram (EEG), which partly results from the enhancement of (γ-aminobutyric acid [GABA]) γ-aminobutyric acid-ergic (GABAergic) transmission. There is a GABAergic excitatory-inhibitory shift during postnatal development. Whether general anesthetics can enhance slow-delta oscillations in the immature brain has not yet been unequivocally determined.

METHODS

Perforated patch-clamp recording was used to confirm the reversal potential of GABAergic currents throughout GABAergic development in acute brain slices of neonatal rats. The power density of the electrocorticogram and the minimum alveolar concentrations (MAC) of isoflurane and/or sevoflurane were measured in P4-P21 rats. Then, the effects of bumetanide, an inhibitor of the Na + -K + -2Cl - cotransporter (NKCC1) and K + -Cl - cotransporter (KCC2) knockdown on the potency of volatile anesthetics and the power density of the EEG were determined in vivo.

RESULTS

Reversal potential of GABAergic currents were gradually hyperpolarized from P4 to P21 in cortical pyramidal neurons. Bumetanide enhanced the hypnotic effects of volatile anesthetics at P5 (for MAC LORR , isoflurane: 0.63% ± 0.07% vs 0.81% ± 0.05%, 95% confidence interval [CI], -0.257 to -0.103, P < .001; sevoflurane: 1.46% ± 0.12% vs 1.66% ± 0.09%, 95% CI, -0.319 to -0.081, P < .001); while knockdown of KCC2 weakened their hypnotic effects at P21 in rats (for MAC LORR , isoflurane: 0.58% ± 0.05% to 0.77% ± 0.20%, 95% CI, 0.013-0.357, P = .003; sevoflurane: 1.17% ± 0.04% to 1.33% ± 0.04%, 95% CI, 0.078-0.244, P < .001). For cortical EEG, slow-delta oscillations were the predominant components of the EEG spectrum in neonatal rats. Isoflurane and/or sevoflurane suppressed the power density of slow-delta oscillations rather than enhancement of it until GABAergic maturity. Enhancement of slow-delta oscillations under volatile anesthetics was simulated by preinjection of bumetanide at P5 (isoflurane: slow-delta changed ratio from -0.31 ± 0.22 to 1.57 ± 1.15, 95% CI, 0.67-3.08, P = .007; sevoflurane: slow-delta changed ratio from -0.46 ± 0.25 to 0.95 ± 0.97, 95% CI, 0.38-2.45, P = .014); and suppressed by KCC2-siRNA at P21 (isoflurane: slow-delta changed ratio from 16.13 ± 5.69 to 3.98 ± 2.35, 95% CI, -18.50 to -5.80, P = .002; sevoflurane: slow-delta changed ratio from 0.13 ± 2.82 to 3.23 ± 2.49, 95% CI, 3.02-10.79, P = .003).

CONCLUSIONS

Enhancement of cortical EEG slow-delta oscillations by volatile anesthetics may require mature GABAergic inhibitory transmission during neonatal development.

Effect of raw electroencephalogram-guided anesthesia administration on postoperative outcomes in elderly patients undergoing abdominal major surgery: a randomized controlled trial

BACKGROUND

EEG monitoring techniques are receiving increasing clinical attention as a common method of reflecting the depth of sedation in the perioperative period. The influence of depth of sedation indices such as the bispectral index (BIS) generated by the processed electroencephalogram (pEEG) machine to guide the management of anesthetic depth of sedation on postoperative outcome remains controversial. This research was designed to decide whether an anesthetic agent exposure determined by raw electroencephalogram (rEEG) can influence anesthetic management and cause different EEG patterns and affect various patient outcomes.

METHODS

A total of 141 participants aged ≥ 60 years undergoing abdominal major surgery were randomized to rEEG-guided anesthesia or routine care group. The rEEG-guided anesthesia group had propofol titrated to keep the rEEG waveform at the C-D sedation depth during surgery, while in the routine care group the anesthetist was masked to the patient's rEEG waveform and guided the anesthetic management only through clinical experience. The primary outcome was the presence of postoperative complications, the secondary outcomes included intraoperative anesthetic management and different EEG patterns.

RESULTS

There were no statistically significant differences in the occurrence of postoperative respiratory, circulatory, neurological and gastrointestinal complications. Further EEG analysis revealed that lower frontal alpha power was significantly associated with a higher incidence of POD, and that rEEG-guidance not only reduced the duration of deeper anesthesia in patients with lower frontal alpha power, but also allowed patients with higher frontal alpha power to receive deeper and more appropriate depths of anesthesia than in the routine care group.

CONCLUSIONS

In elderly patients undergoing major abdominal surgery, rEEG-guided anesthesia did not reduce the incidence of postoperative respiratory, circulatory, neurological and gastrointestinal complications. rEEG-guided anesthesia management reduced the duration of intraoperative BS in patients and the duration of over-deep sedation in patients with lower frontal alpha waves under anesthesia, and there was a strong association between lower frontal alpha power under anesthesia and the development of POD. rEEG-guided anesthesia may improve the prognosis of patients with vulnerable brains by improving the early identification of frail elderly patients and providing them with a more effective individualized anesthetic managements.

Incidence change of postoperative delirium after implementation of processed electroencephalography monitoring during surgery: a retrospective evaluation study

BACKGROUND

Postoperative delirium (POD) is a common complication in the elderly, which is associated with poor outcomes after surgery. Recognized as predisposing factors for POD, anesthetic exposure and burst suppression during general anesthesia can be minimized with intraoperative processed electroencephalography (pEEG) monitoring. In this study, we aimed to evaluate whether implementation of intraoperative pEEG-guided anesthesia is associated with incidence change of POD.

METHODS

In this retrospective evaluation study, we analyzed intravenous patient-controlled analgesia (IVPCA) dataset from 2013 to 2017. There were 7425 patients using IVPCA after a noncardiac procedure under general anesthesia. Patients incapable of operating the device independently, such as cognitive dysfunction or prolonged sedation, were declined and not involved in the dataset. After excluding patients who opted out within three days (N = 110) and those with missing data (N = 24), 7318 eligible participants were enrolled. Intraoperative pEEG has been implemented since July 2015. Participants having surgery after this time point had intraoperative pEEG applied before induction until full recovery. All related staff had been trained in the application of pEEG-guided anesthesia and the assessment of POD. Patients were screened twice daily for POD within 3 days after surgery by staff in the pain management team. In the first part of this study, we compared the incidence of POD and its trend from 2013 January-2015 July with 2015 July-2017 December. In the second part, we estimated odds ratios of risk factors for POD using multivariable logistic regression in case-control setting.

RESULTS

The incidence of POD decreased from 1.18 to 0.41% after the administration of intraoperative pEEG. For the age group ≧ 75 years, POD incidence decreased from 5.1 to 1.56%. Further analysis showed that patients with pEEG-guided anesthesia were associated with a lower odd of POD (aOR 0.33; 95% CI 0.18-0.60) than those without after adjusting for other covariates.

CONCLUSIONS

Implementation of intraoperative pEEG was associated with a lower incidence of POD within 3 days after surgery, particularly in the elderly. Intraoperative pEEG might be reasonably considered as part of the strategy to prevent POD in the elder population.

TRIAL REGISTRATION

Not applicable.

Is the Patient State Index a reliable parameter as guide to anaesthesiology in cranial neurosurgery? A first intraoperative study and a literature review

BACKGROUND

Patient State Index (PSI) and Suppression Ratio (SR) are two indices calculated by quantitative analysis of EEG used to estimate the depth of anaesthesia but their validation in neurosurgery must be done. Our aim was to investigate the congruity PSI and SR with raw EEG monitoring in neurosurgery.

METHODS

We included 34 patients undergoing elective cranial neurosurgery. Each patient was monitored by a SedLine device (PSI and SR) and by raw EEG. To appraise the agreement between PSI, SR and EEG Suppr%, Bland-Altman analysis was used. We also correlated the PSI and SR recorded at different times during surgery to the degree of suppression of the raw EEG data by Spearman's rank correlation coefficient. For a comparison with previous data we made an international literature review according to PRISMA protocol.

RESULTS

At all recording times, we found that there is a strong agreement between PSI and raw EEG. We also found a significant correlation for both PSI and SR with the EEG suppression percentage (p < 0.05), but with a broad dispersion of the individual values within the confidence interval.

CONCLUSION

The Masimo SedLine processed EEG monitoring system can be used as a guide in the anaesthetic management of patients during elective cranial neurosurgery, but the anaesthesiologist must be aware that previous correlations between PSI and SR with the suppression percentage may not always be valid in all individual patients. The use of an extended visual raw EEG evaluated by an expert electroencephalographer might help to provide better guidance.

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.

Comparative analysis of the effect of electromyogram to bispectral index and 95% spectral edge frequency under remimazolam and propofol anesthesia: a prospective, randomized, controlled clinical trial

Background

Bispectral index (BIS), an index used to monitor the depth of anesthesia, can be interfered with by the electromyogram (EMG) signal. The 95% spectral edge frequency (SEF95) also can reflect the sedation depth. Remimazolam in monitored anesthesia care results in higher BIS values than propofol, though in the same sedation level assessed by Modified Observers Assessment of Alertness and Sedation (MOAA/S). Our study aims to illustrate whether EMG is involved in remimazolam causing higher BIS value than propofol preliminarily and to explore the correlations among BIS, EMG, and SEF95 under propofol and remimazolam anesthesia.

Patients and methods

Twenty-eight patients were randomly divided into propofol (P) and remimazolam (RM) groups. Patients in the two groups received alfentanil 10 μg/kg, followed by propofol 2 mg/kg and remimazolam 0.15 mg/kg. Blood pressure (BP), heart rate (HR), and oxygen saturation (SpO2) were routinely monitored. The BIS, EMG, and SEF95 were obtained through BIS VISTATM. The primary outcomes were BIS, EMG, and the correlation between BIS and EMG in both groups. Other outcomes were SEF95, the correlation between BIS and SEF95, and the correlation between EMG and SEF95. And all the statistical and comparative analysis between these signals was conducted with SPSS 26.0 and GraphPad Prism 8.

Results

BIS values, EMG, and SEF95 were significantly higher in the RM group than in the P group (all p < 0.001). There was a strong positive correlation between BIS and EMG in the RM group (r = 0.416). Nevertheless, the BIS in the P group showed a weak negative correlation with EMG (r = -0.219). Both P (r = 0.787) and RM group (r = 0.559) had a reasonably significant correlation coefficient between BIS and SEF95. SEF95 almost did not correlate with EMG in the RM group (r = 0.101).

Conclusion

Bispectral index can be interfered with high EMG intensity under remimazolam anesthesia. However, EMG can hardly affect the accuracy of BIS under propofol anesthesia due to low EMG intensity and a weak negative correlation between EMG and BIS. Moreover, SEF95 may have a great application prospect in predicting the sedation condition of remimazolam.

Changes in SedLine-derived processed electroencephalographic parameters during hypothermia in patients undergoing cardiac surgery with cardiopulmonary bypass

Objective

Processed electroencephalography (pEEG) is used to monitor depth-of-anesthesia during cardiopulmonary bypass (CPB). The SedLine device has been recently introduced for pEEG monitoring. However, the effect of hypothermia on its parameters during CPB is unknown. Accordingly, we aimed to investigate temperature-induced changes in SedLine-derived pEEG parameters during CPB.

Design

Prospective observational study.

Setting

Cardiac surgery operating theatre.

Participants

28 patients undergoing elective cardiac surgery with CPB.

Interventions

We continuously measured patient state index (PSI), suppression ratio (SR), bilateral spectral edge frequency (SEF) and temperature. We used linear mixed modelling with fixed and random effects to study the interactions between pEEG parameters and core temperature.

Measurements and main results

During CPB maintenance, the median temperature was 32.1°C [interquartile range (IQR): 29.8-33.6] at the end of cooling and 32.8°C (IQR: 30.1-34.0) at rewarming initiation. For each degree Celsius change in temperature during cooling and rewarming the PSI either decreased by 0.8 points [95% confidence interval (CI): 0.7-1.0; p < 0.001] or increased by 0.7 points (95% CI: 0.6-0.8; p < 0.001). The SR increased by 2.9 (95% CI: 2.3-3.4); p < 0.001) during cooling and decreased by 2.2 (95% CI: 1.7-2.7; p < 0.001) during rewarming. Changes in the SEF were not related to changes in temperature.

Conclusions

During hypothermic CPB, temperature changes led to concordant changes in the PSI. The SR increased during cooling and decreased during rewarming. Clinicians using SedLine for depth-of-anesthesia monitoring should be aware of these effects when interpreting the PSI and SR values.

A Narrative Review Illustrating the Clinical Utility of Electroencephalogram-Guided Anesthesia Care in Children

The major therapeutic end points of general anesthesia include hypnosis, amnesia, and immobility. There is a complex relationship between general anesthesia, responsiveness, hemodynamic stability, and reaction to noxious stimuli. This complexity is compounded in pediatric anesthesia, where clinicians manage children from a wide range of ages, developmental stages, and body sizes, with their concomitant differences in physiology and pharmacology. This renders anesthetic requirements difficult to predict based solely on a child's age, body weight, and vital signs. Electroencephalogram (EEG) monitoring provides a window into children's brain states and may be useful in guiding clinical anesthesia management. However, many clinicians are unfamiliar with EEG monitoring in children. Young children's EEGs differ substantially from those of older children and adults, and there is a lack of evidence-based guidance on how and when to use the EEG for anesthesia care in children. This narrative review begins by summarizing what is known about EEG monitoring in pediatric anesthesia care. A key knowledge gap in the literature relates to a lack of practical information illustrating the utility of the EEG in clinical management. To address this gap, this narrative review illustrates how the EEG spectrogram can be used to visualize, in real time, brain responses to anesthetic drugs in relation to hemodynamic stability, surgical stimulation, and other interventions such as cardiopulmonary bypass. This review discusses anesthetic management principles in a variety of clinical scenarios, including infants, children with altered conscious levels, children with atypical neurodevelopment, children with hemodynamic instability, children undergoing total intravenous anesthesia, and those undergoing cardiopulmonary bypass. Each scenario is accompanied by practical illustrations of how the EEG can be visualized to help titrate anesthetic dosage to avoid undersedation or oversedation when patients experience hypotension or other physiological challenges, when surgical stimulation increases, and when a child's anesthetic requirements are otherwise less predictable. Overall, this review illustrates how well-established clinical management principles in children can be significantly complemented by the addition of EEG monitoring, thus enabling personalized anesthesia care to enhance patient safety and experience.

Unwanted spontaneous responsiveness and burst suppression in patients undergoing entropy-guided total intravenous anesthesia with target-controlled infusion: An observational prospective trial

STUDY OBJECTIVE

To estimate the incidence of unwanted spontaneous responsiveness and burst suppression (BSupp) in patients undergoing state entropy (SE) and surgical pleth index (SPI)-guided total intravenous anesthesia (TIVA) with target-controlled infusion (TCI).

DESIGN

Observational, prospective, single-center study.

SETTINGS

Operating room.

PATIENTS

107 adult (<65 years) and elderly (≥65 years) women undergoing breast surgery.

INTERVENTIONS

Propofol-remifentanil TIVA-TCI-guided by SE for depth of anesthesia monitoring (target value 40-60) and SPI for antinociception monitoring (target value 20-50) without neuromuscular blockade.

MEASUREMENTS

Age; body mass index; American Society of Anesthesiologists physical status classification; concentration at the effect site of propofol (CeP) and remifentanil (CeR) at loss of responsiveness (LoR), median during anesthesia maintenance (MdM), and at return of responsiveness (RoR); propofol infusion duration; incidence of postoperative delirium (POD) with Confusing Assessment Method for the Intensive Care Unit.

MAIN RESULTS

During SE-SPI-guided TIVA-TCI, 13.1% of patients showed unwanted spontaneous responsiveness, whereas 45.8% showed BSupp. Unwanted spontaneous responsiveness was observed mainly in adults (p < 0.05), and higher CeP RoR (p < 0.05) was registered. BSupp was observed mainly in patients showing a lower CeP MdM (p < 0.01) and CeP RoR (p < 0.05). Unwanted spontaneous responsiveness and BSupp were not associated with significant differences in CeRs. An age-related hysteresis effect was observed, resulting in higher CeP LoR than CeP RoR (p < 0.001). 12.2% of patients showed POD. Only preoperative serum albumin was associated with increased likelihood of POD (p = 0.046).

CONCLUSIONS

The SE-SPI-guided TIVA-TCI did not prevent unwanted spontaneous responsiveness and BSupp. CeP RoR may be used as a proxy for anesthetic sensitivity.

Consistency of the anesthesia consciousness index versus the bispectral index during laparoscopic gastrointestinal surgery with sevoflurane anesthesia: A prospective multi-center randomized controlled clinical study

Background

This study aimed to compare the consistency of anesthesia consciousness index (Ai) with that of bispectral index (BIS) in monitoring the depth of anesthesia (DOA) during sevoflurane anesthesia, to reveal the optimal cutoff values in different states of consciousness, and explore the stability of DOA monitoring during intraoperative injurious stimulation.

Methods

We enrolled 145 patients (97 men and 48 women) from 10 medical centers. General anesthesia was induced using intravenous anesthetics and maintained with sevoflurane. Ai and BIS values were recorded.

Results

The mean difference between the Ai and BIS was-0.1747 (95% confidence interval, −0.6660 to 0.3166; p = 0.4857). The regression equation of Ai and BIS from the Deming regression analysis was y = 5.6387 + 0.9067x (y is BIS, x is Ai), and the slope and intercept were statistically significant. Meanwhile, the receiver operating characteristic curve analysis of anesthesia-induced unconsciousness, loss of consciousness, and recovery of consciousness revealed that the accuracy of Ai and BIS were similar. In addition, the optimal cutoff values of the different states of consciousness were not sensitive to age, and both Ai and BIS had no correlation with hemodynamics.

Conclusion

We conclude that Ai and BIS show no systematic deviation in readings with high consistency, similar accuracy, and good stability; these insights provide more data for clinical application.

The effect of remifentanil infusion on sevoflurane minimum alveolar concentration-no movement (MACNM) and bispectral index in dogs

OBJECTIVE

To determine the effect of remifentanil infusion on the minimum alveolar concentration of sevoflurane preventing movement (SEVOMAC_NM) and bispectral index (BIS) in dogs.

STUDY DESIGN

Prospective, unmasked study.

ANIMALS

A total of 10 adult Beagle dogs weighing 9.0 ± 1.1 kg.

METHODS

Dogs were anesthetized with sevoflurane and baseline SEVOMAC_NM was determined. Remifentanil was infused at 5, 10 and 20 μg kg^-1 hour^-1, in sequence, with 20 minutes washout between infusions. Variables monitored throughout anesthesia included heart rate (HR), oscillometric blood pressure, end-tidal partial pressure of carbon dioxide, end-tidal sevoflurane concentration (Fe'Sevo) and BIS. SEVOMAC_NM after remifentanil infusion (SEVOMAC_NM-REMI) determination started 20 minutes after the start of each infusion. Venous blood samples were collected for plasma remifentanil concentration determination at baseline, SEVOMAC_NM-REMI determination time points, and 20 minutes after each infusion was stopped. A mixed model analysis was used to determine the effect of remifentanil infusion on response variables. The relationships between BIS and Fe'Sevo, plasma remifentanil concentrations and the percentage decrease in baseline SEVOMAC_NM were evaluated (p < 0.05).

RESULTS

The overall SEVOMAC_NM at baseline was 2.47 ± 0.11%. Addition of remifentanil at all infusion rates significantly decreased SEVOMAC_NM, but the medium and high doses resulted in significantly greater decreases in SEVOMAC_NM than the lower dose. There was no difference in SEVOMAC_NM percentage change between infusions 10 and 20 μg kg^-1 hour^-1. Plasma remifentanil concentrations were significantly different in all infusion rates. Baseline BIS value was 70 ± 1 and was lower than the BIS values recorded during all remifentanil infusions. BIS values were not significantly different among infusion rates. HR was lower and mean arterial pressure was higher during remifentanil infusions than at baseline.

CONCLUSIONS AND CLINICAL RELEVANCE

All remifentanil infusions decreased SEVOMAC_NM in dogs. Remifentanil infusion at any rate studied did not reduce BIS values.

Performance of the bispectral index and electroencephalograph derived parameters of anesthetic depth during emergence from xenon and sevoflurane anesthesia

Many processed EEG monitors (pEEG) are unreliable when non-GABAergic anesthetic agents are used. The primary aim of the study was to compare the response of the Bispectral Index (BIS) during emergence from anesthesia maintained by xenon and sevoflurane. To better understand the variation in response of pEEG to these agents, we also compared several EEG derived parameters relevant to pEEG monitoring during emergence. Twenty-four participants scheduled for lithotripsy were randomized to receive xenon or sevoflurane anesthesia. Participants were monitored with the BIS and had simultaneous raw EEG collected. BIS index values were compared at three key emergence timepoints: first response, eyes open and removal of airway. Two sets of EEG derived parameters, three related to the BIS: relative beta ratio, SynchFastSlow and SynchFastSlow biocoherence, and two unrelated to the BIS: spectral edge frequency and the composite cortical state, were calculated for comparison. BIS index values were significantly lower in the xenon group than the sevoflurane group at each emergence timepoint. The relative beta ratio parameter increased significantly during emergence in the sevoflurane group but not in the xenon group. The spectral edge frequency and composite cortical state parameters increased significantly in both groups during emergence. The BIS index is lower at equivalent stages of behavioural response during emergence from xenon anesthesia when compared to sevoflurane anesthesia, most likely due to differences in how these two agents influence the relative beta ratio. The spectral edge frequency and composite cortical state might better reflect emergence from xenon anaesthesia.Clinical trial number and registry Australia New Zealand Clinical Trials Registry Number: ACTRN12618000916246.

Estimating the Depth of Anesthesia from EEG Signals Based on a Deep Residual Shrinkage Network

The reliable monitoring of the depth of anesthesia (DoA) is essential to control the anesthesia procedure. Electroencephalography (EEG) has been widely used to estimate DoA since EEG could reflect the effect of anesthetic drugs on the central nervous system (CNS). In this study, we propose that a deep learning model consisting mainly of a deep residual shrinkage network (DRSN) and a 1 × 1 convolution network could estimate DoA in terms of patient state index (PSI) values. First, we preprocessed the four raw channels of EEG signals to remove electrical noise and other physiological signals. The proposed model then takes the preprocessed EEG signals as inputs to predict PSI values. Then we extracted 14 features from the preprocessed EEG signals and implemented three conventional feature-based models as comparisons. A dataset of 18 patients was used to evaluate the models' performances. The results of the five-fold cross-validation show that there is a relatively high similarity between the ground-truth PSI values and the predicted PSI values of our proposed model, which outperforms the conventional models, and further, that the Spearman's rank correlation coefficient is 0.9344. In addition, an ablation experiment was conducted to demonstrate the effectiveness of the soft-thresholding module for EEG-signal processing, and a cross-subject validation was implemented to illustrate the robustness of the proposed method. In summary, the procedure is not merely feasible for estimating DoA by mimicking PSI values but also inspired us to develop a precise DoA-estimation system with more convincing assessments of anesthetization levels.

Characteristics of Electroencephalogram in the Prefrontal Cortex during Deep Brain Stimulation of Subthalamic Nucleus in Parkinson's Disease under Propofol General Anesthesia

BACKGROUND

Monitoring the depth of anesthesia by electroencephalogram (EEG) based on the prefrontal cortex is an important means to achieve accurate regulation of anesthesia for subthalamic nucleus (STN) deep brain stimulation (DBS) under general anesthesia in patients with Parkinson's disease (PD). However, no previous study has conducted an in-depth investigation into this monitoring data. Here, we aimed to analyze the characteristics of prefrontal cortex EEG during DBS with propofol general anesthesia in patients with PD and determine the reference range of parameters derived from the depth of anesthesia monitoring. Additionally, we attempted to explore whether the use of benzodiazepines in the 3 days during hospitalization before surgery impacted the interpretation of the EEG parameters.

MATERIALS AND METHODS

We included the data of 43 patients with PD who received STN DBS treatment and SedLine monitoring during the entire course of general anesthesia with propofol in a single center. Eighteen patients (41.86%) took benzodiazepines during hospitalization. We divided the anesthesia process into three stages: awake state before anesthesia, propofol anesthesia state, and shallow anesthesia state during microelectrode recording (MER). We analyzed the power spectral density (PSD) and derived parameters of the patients' prefrontal EEG, including the patient state index (PSI), spectral edge frequency (SEF) of the left and right sides, and the suppression ratio. The baseline characteristics, preoperative medication, preoperative frontal lobe image characteristics, preoperative motor and non-motor evaluation, intraoperative vital signs, internal environment and anesthetic information, and postoperative complications are listed. We also compared the groups according to whether they took benzodiazepines before surgery during hospitalization.

RESULTS

The average PSI of the awake state, propofol anesthesia state, and MER state were 89.86 ± 6.89, 48.68 ± 12.65, and 62.46 ± 13.08, respectively. The preoperative administration of benzodiazepines did not significantly affect the PSI or SEF, but did reduce the total time of suppression, maximum suppression ratio, and the PSD of beta and gamma during MER. Regarding the occurrence of postoperative delirium and mini-mental state examination (MMSE) scores, there was no significant difference between the two groups (chi-square test, p = 0.48; Mann-Whitney U test, p = 0.30).

CONCLUSION

For the first time, we demonstrate the reference range of the derived parameters of the depth of anesthesia monitoring and the characteristics of the prefrontal EEG of patients with PD in the awake state, propofol anesthesia state, and shallow anesthesia during MER. Taking benzodiazepines in the 3 days during hospitalization before surgery reduces suppression and the PSD of beta and gamma during MER, but does not significantly affect the observation of anesthesiologists on the depth of anesthesia, nor affect the postoperative delirium and MMSE scores.

Bispectral index monitoring to detect delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage

PURPOSE

Evaluate the bispectral index (BIS) monitoring to detect delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH).

MATERIALS AND METHODS

A single-center prospective study in patients with aSAH. BIS monitoring was recorded during 25-120 min in two periods, within the initial 72 h (BIS1) and between days 4 and 6 (BIS2) from admission. The median for each exported BIS parameter was analyzed. Transcranial Doppler (TCD) sonography was simultaneously performed with BIS1 (TCD1) and BIS2 (TCD2) monitoring. A multivariate logistic regression model was built to identify the variables associated with DCI.

RESULTS

Sixty-four patients were included and 16 (25%) developed DCI. During BIS2 monitoring, significant differences were found in BIS value (left, p = 0.01; right, p = 0.009), 95% spectral edge frequency (left and right, p = 0.04), and total power (left and right, p = 0.04). In multivariable analysis, vasospasm on TCD2 (OR 42.8 [95% CI 3.1-573]; p = 0.005), a median BIS2 value <85 in one or both sides (OR 6.2 [95% CI 1.28-30]; p = 0.023), and age (OR 1.08 [95% CI 1.00-1.17]; p = 0.04) were associated with the development of DCI.

CONCLUSIONS

BIS value is the most useful BIS parameter for detecting DCI after aSAH. Pending further validation, BIS monitoring might be even more accurate than TCD.

Usability of the SedLine® electroencephalographic monitor of depth of anaesthesia in pigs: a pilot study

To investigate the usability of the SedLine® monitor in anaesthetized pigs. Five juvenile healthy pigs underwent balanced isoflurane-based general anaesthesia for surgical placement of a subcutaneous jugular venous port. The SedLine® was applied to continuously monitor electroencephalographic (EEG) activity and its modulation during anaesthesia. Computer tomography and magnetic resonance were performed to investigate the relationship between electrodes' positioning and anatomical structures. The pediatric SedLine® EEG-sensor could be easily applied and SedLine®-generated variables collected. An EEG Density Spectral Array (DS) was displayed over the whole procedure. During surgery, the EEG signal was dominated by elevated power in the delta range (0.5-4 Hz), with an underlying broadband signal (where power decreased with increasing frequency). The emergence period was marked by a decrease in delta power, and a more evenly distributed power over the 4-40 Hz frequency range. From incision to end of surgery, mean SedLine®-generated values (± standard deviation) were overall stable [23.0 (± 2.8) Patient State Index (PSI), 1.0% (± 3.8%) Suppression Ratio (SR), 8.8 Hz (± 2.5 Hz) Spectral Edge Frequency 95% (SEF) left, 7.7 Hz (± 2.4 Hz) SEF right], quickly changing during emergence [75.3 (± 11.1) PSI, 0.0 (± 0.0) SR, 12.5 (± 6.6) SEF left 10.4 (± 6.6) SEF right]. Based on the imaging performed, the sensor does not record EEG signals from the same brain areas as in humans. SedLine®-DSA and -generated variables seemed to reflect variations in depth of anaesthesia in pigs. Further studies are needed to investigate this correlation, as well as to define the species-specific brain structures monitored by the EEG-sensor.

Comparison of general anesthesia and continuous intravenous sedation for electrochemotherapy of head and neck skin lesions

Background

Electrochemotherapy of cutaneous tumor nodules requires local or general anesthesia. For multiple and larger nodules, general anesthesia is recommended by standard operating procedures. The choice of general anesthesia is at the discretion of the treating center. Continuous intravenous sedation is also an option. Our study aimed to elucidate the tolerability, safety and possible advantages of continuous intravenous sedation in comparison to general anesthesia in patients undergoing electrochemotherapy.

Patients and methods

In the prospective study, 27 patients undergoing electrochemotherapy were either under general anesthesia or under continuous intravenous sedation. Evaluated were different endpoints, such as feasibility and safety, duration of anesthesia and compliance with the patients.

Results

Ten patients were treated under general anesthesia, and 17 patients were under continuous intravenous sedation. The comparison of the approaches indicated that continuous intravenous sedation required a lower overall dosage of propofol, a shorter duration of anesthesia, a shorter time to reach an Aldrete score &gt;8, and greater satisfaction of the patients with the procedure compared to general anesthesia.

Conclusion

The results indicate the feasibility and safety of continuous intravenous sedation for patients undergoing electrochemotherapy of cutaneous tumor nodules. This proved the preferred choice of anesthesia due to its shorter duration and better compliance with the patients compared to general anesthesia.

Monitoring the Awake and Anesthetized Unconscious States Using Bispectral Index and Electroencephalographic Connectivity Measures

Objective. Our objective was to compare three electroencephalography (EEG)-based methods with anesthesiologist clinical judgment of the awake and anesthetized unconscious states. Methods. EEG recorded from 25 channels and from four channel bilateral Bispectral index (BIS) electrodes were collected from 20 patients undergoing surgery with general anesthesia. To measure connectivity we applied Directed Transfer Function (DTF) in eight channels of the EEG, and extracted data from BIS over the same time segments. Shannon's entropy was applied to assess the complexity of the EEG signal. Discriminant analysis was used to evaluate the data in relation to clinical judgment. Results. Assessing anesthetic state relative clinical judgment, the bilateral BIS gave the highest accuracy (ACC) (95.4%) and lowest false positive discovery rate (FDR) (0.5%) . Equivalent DTF gave 94.5% for ACC and 2.6% for FDR. Combining all methods gave ACC = 94.9% and FDR = 1%. Generally, entropy scored lower on ACC and higher on FDR than the other methods (ACC 90.87% and FDR 4.6%). BIS showed at least a one minute delay in 18 of the 20 patients. Conclusions. Our results show that BIS and DTF both have a high ACC and low FDR. Because of time delays in BIS values, we recommend combining the two methods.

Photoplethysmography temporal marker-based machine learning classifier for anesthesia drug detection

Anesthesia drug overdose hazards and lack of gold standards in anesthesia monitoring lead to an urgent need for accurate anesthesia drug detection. To investigate the PPG waveform features affected by anesthesia drugs and develop a machine-learning classifier with high anesthesia drug sensitivity. This study used 64 anesthesia and non-anesthesia patient data (32 cases each), extracted from Queensland and MIMIC-II databases, respectively. The key waveform features (total area, rising time, width 75%, 50%, and 25%) were extracted from 16,310 signal recordings (5-s duration). Discriminant analysis, support vector machine (SVM), and K-nearest neighbor (KNN) were evaluated by splitting the dataset into halve training (11 patients, 8570 segments) and halve testing dataset (11 patients, 7740 segments). Significant differences exist between PPG waveform features of anesthesia and non-anesthesia groups (p < 0.05) except total area feature (p > 0.05). The KNN classifier achieved 91.7% (AUC = 0.95) anesthesia detection accuracy with the highest sensitivity (0.88) and specificity (0.90) as compared to other classifiers. Kohen’s kappa also shows almost perfect agreement (0.79) with the KNN classifier. The KNN classifier trained with significant PPG features has the potential to be used as a reliable, non-invasive, and low-cost method for the detection of anesthesia drugs for depth analysis during surgical operations and postoperative monitoring.

Comparison of the performance of phase lag entropy and bispectral index for monitoring the depth of sedation under dexmedetomidine sedation: A prospective, observational, and non-inferiority trial

STUDY OBJECTIVE

Although the performance of phase lag entropy (PLE), a new depth-of-sedation monitor based on the diversity of temporal patterns in the phase relationships in electroencephalogram (EEG) data, during propofol sedation has been proven through several studies, since different sedatives have different effects on EEG, we aimed to evaluate the performance of the PLE in comparison with the bispectral index (BIS) during dexmedetomidine sedation.

DESIGN

A prospective, observational, and non-inferiority trial.

SETTING

Tertiary university hospital operating room.

PATIENTS

Forty-two patients aged 20-80 years who were scheduled to undergo elective surgery under spinal anesthesia and had American Society of Anesthesiologists (ASA) physical status I to III were enrolled in this study.

INTERVENTIONS

Dexmedetomidine was administered with a loading dose of 0.5-1 μg/kg for 10 min, followed by a maintenance dose of 0.3-0.6 μg/kg/h.

MEASUREMENTS

The depth of sedation was assessed using the modified observer's assessment of alertness/sedation (MOAA/S) scale; the data for PLE and BIS were collected; and vital signs, including blood pressure, heart rate, EKG, and pulse oximetry, were evaluated.

MAIN RESULTS

215,082 data points for the MOAA/S score and PLE and BIS values were analyzed. The baseline variabilities of PLE and BIS were 4.53% and 7.02%, respectively. The Spearman correlation coefficients of the MOAA/S score with PLE and BIS were 0.599 and 0.566, respectively. The prediction probabilities of the MOAA/S score with PLE and BIS were 0.647 and 0.636, respectively. When the MOAA/S score was 3 points, the mean (SD) values of PLE and BIS were 68.35 (15.68) and 75.85 (9.81), respectively, However, the mean (SD) values of PLE and BIS for an MOAA/S score of 1 point were 56.08 (12.49) and 68.29 (12.65), respectively.

CONCLUSIONS

PLE shows potential as a hypnotic depth indicator during dexmedetomidine sedation, and its performance was not inferior to that of BIS.

Processed Electroencephalogram-Based Monitoring to Guide Sedation in Critically Ill Adult Patients: Recommendations from an International Expert Panel-Based Consensus

BACKGROUND

The use of processed electroencephalography (pEEG) for depth of sedation (DOS) monitoring is increasing in anesthesia; however, how to use of this type of monitoring for critical care adult patients within the intensive care unit (ICU) remains unclear.

METHODS

A multidisciplinary panel of international experts consisting of 21 clinicians involved in monitoring DOS in ICU patients was carefully selected on the basis of their expertise in neurocritical care and neuroanesthesiology. Panelists were assigned four domains (techniques for electroencephalography [EEG] monitoring, patient selection, use of the EEG monitors, competency, and training the principles of pEEG monitoring) from which a list of questions and statements was created to be addressed. A Delphi method based on iterative approach was used to produce the final statements. Statements were classified as highly appropriate or highly inappropriate (median rating ≥ 8), appropriate (median rating ≥ 7 but < 8), or uncertain (median rating < 7) and with a strong disagreement index (DI) (DI < 0.5) or weak DI (DI ≥ 0.5 but < 1) consensus.

RESULTS

According to the statements evaluated by the panel, frontal pEEG (which includes a continuous colored density spectrogram) has been considered adequate to monitor the level of sedation (strong consensus), and it is recommended by the panel that all sedated patients (paralyzed or nonparalyzed) unfit for clinical evaluation would benefit from DOS monitoring (strong consensus) after a specific training program has been performed by the ICU staff. To cover the gap between knowledge/rational and routine application, some barriers must be broken, including lack of knowledge, validation for prolonged sedation, standardization between monitors based on different EEG analysis algorithms, and economic issues.

CONCLUSIONS

Evidence on using DOS monitors in ICU is still scarce, and further research is required to better define the benefits of using pEEG. This consensus highlights that some critically ill patients may benefit from this type of neuromonitoring.

VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients

In modern anesthesia, multiple medical devices are used simultaneously to comprehensively monitor real-time vital signs to optimize patient care and improve surgical outcomes. However, interpreting the dynamic changes of time-series biosignals and their correlations is a difficult task even for experienced anesthesiologists. Recent advanced machine learning technologies have shown promising results in biosignal analysis, however, research and development in this area is relatively slow due to the lack of biosignal datasets for machine learning. The VitalDB (Vital Signs DataBase) is an open dataset created specifically to facilitate machine learning studies related to monitoring vital signs in surgical patients. This dataset contains high-resolution multi-parameter data from 6,388 cases, including 486,451 waveform and numeric data tracks of 196 intraoperative monitoring parameters, 73 perioperative clinical parameters, and 34 time-series laboratory result parameters. All data is stored in the public cloud after anonymization. The dataset can be freely accessed and analysed using application programming interfaces and Python library. The VitalDB public dataset is expected to be a valuable resource for biosignal research and development.

Measurement(s)	vital signs of patients during surgery • perioperative patient information
Technology Type(s)	Vital Signs Measurement • Electronic Medical Record
Factor Type(s)	vital signs data including various numeric and waveform data acquired from multiple patient monitors • perioperative patient information acquired from the electronic medical record system
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	hospital
Sample Characteristic - Location	South Korea

Abnormally high Patient State Index associated with epicardial pacing: a case report

Background

Anesthesiologists monitor electroencephalography (EEG) intraoperatively to maintain adequate depth of anesthesia. However, the EEG signal is affected by noise and interference. The SedLine® is a brain function monitor with which the Patient State Index (PSI) is calculated. In this study, we report abnormally high PSI values associated with epicardial pacing during open heart surgery.

Case presentation

A 50-year-old man was scheduled for total arch replacement. Atrial demand pacing was started before weaning from cardiopulmonary bypass. The PSI increased from 30 to 80 soon after the start of pacing, and the EEG waveform showed spikes synchronized with the pacing. As the pacing output was lowered, the spikes on the EEG attenuated and disappeared, and the PSI decreased to < 40. When the pacing output was increased again, the spikes recurred, and the PSI increased again.

Conclusions

Pacemaker spikes may cause contamination of the EEG, resulting in abnormally high PSI values.

Adaptive single-channel EEG artifact removal for real-time clinical monitoring

OBJECTIVE

Electroencephalography (EEG) has become very common in clinical practice due to its relatively low cost, ease of installation, non-invasiveness, and good temporal resolution. Portable EEG devices are increasingly popular in clinical monitoring applications such as sleep scoring or anesthesia monitoring. In these situations, for reasons of speed and simplicity only few electrodes are used and contamination of the EEG signal by artifacts is inevitable. Visual inspection and manual removal of artifacts is often not possible, especially in real-time applications. Our goal is to develop a flexible technique to remove EEG artifacts in these contexts with minimal supervision.

METHODS

We propose here a new wavelet-based method which allows to remove artifacts from single-channel EEGs. The method is based on a data-driven renormalization of the wavelet components and is capable of adaptively attenuate artifacts of different nature. We benchmark our method against alternative artifact removal techniques.

RESULTS

We assessed the performance of the proposed method on publicly available datasets comprising ocular, muscular, and movement artifacts. The proposed method shows superior performances on different kinds of artifacts and signal-to-noise levels. Finally, we present an application of our method to the monitoring of general anesthesia.

CONCLUSIONS

We show that our method can successfully attenuate various types of artifacts in single-channel EEG.

SIGNIFICANCE

Thanks to its data-driven approach and low computational cost, the proposed method provides a valuable tool to remove artifacts in real-time EEG applications with few electrodes, such as monitoring in special care units.

Resting State Functional Connectivity Analysis During General Anesthesia: A High-Density EEG Study

The depth of anesthesia monitoring is helpful to guide administrations of general anesthetics during surgical procedures,however, the conventional 2-4 channels electroencephalogram (EEG) derived monitors have their limitations in monitoring conscious states due to low spatial resolution and suboptimal algorithm. In this study, 256-channel high-density EEG signals in 24 subjects receiving three types of general anesthetics (propofol, sevoflurane and ketamine) respectively were recorded both before and after anesthesia. The raw EEG signals were preprocessed by EEGLAB 14.0. Functional connectivity (FC) analysis by traditional coherence analysis (CA) method and a novel sparse representation (SR) method. And the network parameters, average clustering coefficient (ACC) and average shortest path length (ASPL) before and after anesthesia were calculated. The results show SR method find more significant FC differences in frontal and occipital cortices, and whole brain network (p<0.05). In contrast, CA can hardly obtain consistent ASPL in the whole brain network (p>0.05). Further, ASPL calculated by SR for whole brain connections in all of three anesthesia groups increased, which can be a unified EEG biomarker of general anesthetics-induced loss of consciousness (LOC). Therefore FC analysis based on SR analysis has better performance in distinguishing anesthetic-induced LOC from awake state.

A survey of current practices, attitudes and demands of anaesthesiologists regarding the depth of anaesthesia monitoring in China

Background

In this study, we aimed to analyse survey data to explore two different hypotheses; and for this purpose, we distributed an online survey to Chinese anaesthesiologists. The hypothetical questions in this survey include: (1) Chinese anaesthesiologists mainly use the depth of anaesthesia (DoA) monitors to prevent intraoperative awareness and (2) the accuracy of these monitors is the most crucial performance factor during the clinical daily practice of Chinese anaesthesiologists.

Methods

We collected and statistically analysed the response of a total of 12,750 anesthesiologists who were invited to participate in an anonymous online survey. The Chinese Society of Anaesthesiologists (CSA) trial group provided the email address of each anaesthesiologist, and the selection of respondents was random from the computerized system.

Results

The overall response rate was 32.0% (4037 respondents). Only 9.1% (95% confidence interval, 8.2-10.0%) of the respondents routinely used DoA monitors. Academic respondents (91.5, 90.3-92.7%) most frequently used DoA monitoring to prevent awareness, whereas nonacademic respondents (88.8, 87.4-90.2%) most frequently used DoA monitoring to guide the delivery of anaesthetic agents. In total, the number of respondents who did not use a DoA monitor and whose patients experienced awareness (61.7, 57.8-65.6%) was significantly greater than those who used one or several DoA monitors (51.5, 49.8-53.2%). Overall, the crucial performance factor during DoA monitoring was considered by 61.9% (60.4-63.4%) of the respondents to be accuracy. However, most respondents (95.7, 95.1-96.3%) demanded improvements in the accuracy of the monitors for DoA monitoring. In addition, broad application in patients of all ages (86.3, 85.2-87.4%), analgesia monitoring (80.4, 79.2-81.6%), and all types of anaesthetic agents (75.6, 74.3-76.9%) was reported. In total, 65.0% (63.6-66.5%) of the respondents believed that DoA monitors should be combined with EEG and vital sign monitoring, and 53.7% (52.1-55.2%) believed that advanced DoA monitors should include artificial intelligence.

Conclusions

Academic anaesthesiologists primarily use DoA monitoring to prevent awareness, whereas nonacademic anaesthesiologists use DoA monitoring to guide the delivery of anaesthetics. Anaesthesiologists demand high-accuracy DoA monitors incorporating EEG signals, multiple vital signs, and antinociceptive indicators. DoA monitors with artificial intelligence may represent a new direction for future research on DoA monitoring.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12871-021-01510-7.

Association Between Burst-Suppression Latency and Burst-Suppression Ratio Under Isoflurane or Adjuvant Drugs With Isoflurane Anesthesia in Mice

The same doses of anesthesia may yield varying depths of anesthesia in different patients. Clinical studies have revealed a possible causal relationship between deep anesthesia and negative short- and long-term patient outcomes. However, a reliable index and method of the clinical monitoring of deep anesthesia and detecting latency remain lacking. As burst-suppression is a characteristic phenomenon of deep anesthesia, the present study investigated the relationship between burst-suppression latency (BSL) and the subsequent burst-suppression ratio (BSR) to find an improved detection for the onset of intraoperative deep anesthesia. The mice were divided young, adult and old group treated with 1.0% or 1.5% isoflurane anesthesia alone for 2 h. In addition, the adult mice were pretreated with intraperitoneal injection of ketamine, dexmedetomidine, midazolam or propofol before they were anesthetized by 1.0% isoflurane for 2 h. Continuous frontal, parietal and occipital electroencephalogram (EEG) were acquired during anesthesia. The time from the onset of anesthesia to the first occurrence of burst-suppression was defined as BSL, while BSR was calculated as percentage of burst-suppression time that was spent in suppression periods. Under 1.0% isoflurane anesthesia, we found a negative correlation between BSL and BSR for EEG recordings obtained from the parietal lobes of young mice, from the parietal and occipital lobes of adult mice, and the occipital lobes of old mice. Under 1.5% isoflurane anesthesia, only the BSL calculated from EEG data obtained from the occipital lobe was negatively correlated with BSR in all mice. Furthermore, in adult mice receiving 1.0% isoflurane anesthesia, the co-administration of ketamine and midazolam, but not dexmedetomidine and propofol, significantly decreased BSL and increased BSR. Together, these data suggest that BSL can detect burst-suppression and predict the subsequent BSR under isoflurane anesthesia used alone or in combination with anesthetics or adjuvant drugs. Furthermore, the consistent negative correlation between BSL and BSR calculated from occipital EEG recordings recommends it as the optimal position for monitoring burst-suppression.

Monitoring of Anesthesia by Bispectral Analysis of EEG Signals

Background

In intensive care, monitoring the depth of anesthesia during surgical procedures is a key element in the success of the medical operation and postoperative recovery. However, despite the development of anesthesia thanks to technological and pharmacological advances, its side effects such as underdose or overdose of hypnotics remain a major problem. Observation and monitoring must combine clinical observations (loss of consciousness and reactivity) with tools for real-time measurement of changes in the depth of anesthesia. Methodology. In this work, we will develop a noninvasive method for calculating, monitoring, and controlling the depth of general anesthesia during surgery. The objective is to reduce the effects of pharmacological usage of hypnotics and to ensure better quality recovery. Thanks to the overall activity of sets of neurons in the brain, we have developed a BIS technique based on bispectral analysis of the electroencephalographic signal EEG. Discussion. By collecting the electrical voltages from the brain, we distinguish light sleep from deep sleep according to the values of the BIS indicator (ranging from 0 : sleep to 100 : wake) and also control it by acting on the dosage of propofol and sevoflurane. We showed that the BIS value must be maintained during the operation and the anesthesia at a value greater than 60.

Conclusion

This study showed that the BIS technology led to an optimization of the anesthetic management, the adequacy of the hypnotic dosage, and a better postoperative recovery.

Anesthesia and intraoperative neurophysiological spinal cord monitoring

PURPOSE OF REVIEW

We will explain the basic principles of intraoperative neurophysiological monitoring (IONM) during spinal surgery. Thereafter we highlight the significant impact that general anesthesia can have on the efficacy of the IONM and provide an overview of the essential pharmacological and physiological factors that need to be optimized to enable IONM. Lastly, we stress the importance of teamwork between the anesthesiologist, the neurophysiologist, and the surgeon to improve clinical outcome after spinal surgery.

RECENT FINDINGS

In recent years, the use of IONM has increased significantly. It has developed into a mature discipline, enabling neurosurgical procedures of ever-increasing complexity. It is thus of growing importance for the anesthesiologist to appreciate the interplay between IONM and anesthesia and to build up experience working in a team with the neurosurgeon and the neurophysiologist.

SUMMARY

Safety measures, cooperation, careful choice of drugs, titration of drugs, and maintenance of physiological homeostasis are essential for effective IONM.

Phase Lag Entropy as a Surrogate Measurement of Hypnotic Depth during Sevoflurane Anesthesia

Background and Objectives: Phase lag entropy, an electroencephalographic monitor, evaluates the variety in temporal patterns of phase relationship between frontal and prefrontal brain region. Phase lag entropy can reflect the depth of anesthesia induced by propofol, but the association between sevoflurane and phase lag entropy has not been elucidated. This study examined the effect of sevoflurane on phase lag entropy during induction of general anesthesia. We also explored the pharmacodynamic model between end-tidal anesthetic concentration and electroencephalographic monitor. Materials and Methods: A total of 20 patients were enrolled. General anesthesia was produced by escalating the sevoflurane (1 vol% up to 8 vol%). The relationship between phase lag entropy and end-tidal anesthetic concentration was analyzed. A non-linear mixed-effects model was used to get the relationship of pharmacodynamics between the end-tidal sevoflurane concentration and phase lag entropy. Mean blood pressure, heart rate, and the modified observer’s assessment of alertness/sedation scale were also recorded during sevoflurane anesthesia. Results: As level of sedation increased, phase lag entropy decreased. A significant correlation was showed between phase lag entropy and end-tidal sevoflurane concentration (r = −0.759, p < 0.001). The correlation coefficient between the modified observer’s assessment of alertness/sedation scale and phase lag entropy was 0.731 (p < 0.001). The pharmacodynamic factors assessed by the sigmoid Emax model were E0 = 84.9, Emax = 42, Ce50 = 1.81, γ = 4.78, and ke0 = 0.692. The prediction probability of phase-lag entropy for measuring the modified observer’s assessment of alertness/sedation scale and end-tidal sevoflurane concentration were 0.764 and 0.789, respectively. With the increasing concentration of sevoflurane, mean blood pressure decreased, but heart rate did not change. Conclusions: The continuing escalation in end-tidal sevoflurane concentration caused a decline in phase lag entropy. Phase lag entropy can serve as an indicator of hypnotic depth in patients receiving sevoflurane anesthesia.

Quantitative Electroencephalogram in Pediatric Intensive Care Unit in Three Different Clinical Scenarios

Although clinical judgement and sedation scales are primarily used in intensive care units (ICUs) to manage sedation, adjunctive data are needed to direct therapy with sedative and hypnotic agents to prevent side effects and long-term sequelae. In this case report, we described three cases where we used quantitative electroencephalogram (qEEG) data in a pediatric ICU (PICU); to manage these specific clinical situations and to identify the limitations of the qEEG data, two patients were admitted for post–cardiac arrest care and the third was admitted for status epilepticus. In post–cardiac arrest patients, qEEG was mainly used for monitoring depth of sedation and drug titration. Unnecessary use of high-drug doses was prevented, and monitoring also helped to guide clinical intervention for the management of seizure activity. In the patient with status epilepticus, qEEG data on burst suppression and depth of sedation were used. In this report, we describe three different cases where we used qEEG data in a PICU, to give insight on the use of data in specific clinical situations and to describe the limitations of the qEEG data monitoring system.

Implicit Memory and Anesthesia: A Systematic Review and Meta-Analysis

General anesthesia should induce unconsciousness and provide amnesia. Amnesia refers to the absence of explicit and implicit memories. Unlike explicit memory, implicit memory is not consciously recalled, and it can affect behavior/performance at a later time. The impact of general anesthesia in preventing implicit memory formation is not well-established. We performed a systematic review with meta-analysis of studies reporting implicit memory occurrence in adult patients after deep sedation (Observer's Assessment of Alertness/Sedation of 0-1 with spontaneous breathing) or general anesthesia. We also evaluated the impact of different anesthetic/analgesic regimens and the time point of auditory task delivery on implicit memory formation. The meta-analysis included the estimation of odds ratios (ORs) and 95% confidence intervals (CIs). We included a total of 61 studies with 3906 patients and 119 different cohorts. For 43 cohorts (36.1%), implicit memory events were reported. The American Society of Anesthesiologists (ASA) physical status III-IV was associated with a higher likelihood of implicit memory formation (OR:3.48; 95%CI:1.18-10.25, p < 0.05) than ASA physical status I-II. Further, there was a lower likelihood of implicit memory formation for deep sedation cases, compared to general anesthesia (OR:0.10; 95%CI:0.01-0.76, p < 0.05) and for patients receiving premedication with benzodiazepines compared to not premedicated patients before general anesthesia (OR:0.35; 95%CI:0.13-0.93, p = 0.05).

Machine Learning Based Hardware Architecture for DOA Measurement from Mice EEG

OBJECTIVE

This research aims to design a hardware optimized machine learning based Depth of Anesthesia (DOA) measurement framework for mice and its FPGA implementation.

METHODS

Electroencephalography or EEG signal is acquired from 16 mice in the Neural Interface Research (NIR) Laboratory of the City University of Hong Kong. We present a logistic regression based approach with mathematically uncomplicated feature extraction techniques for efficient hardware implementation to estimate the DOA.

RESULTS

With the extraction of only two features, the proposed system can classify the state of consciousness with 94% accuracy for a 1 second EEG epoch, leading to a 100% accurate channel prediction after a 7 second run-time on average.

CONCLUSION

Through performance evaluation and comparative study confirmed the efficacy of the prototype.

SIGNIFICANCE

Traditionally the DOA is estimated by checking biophysical responses of a patient during the surgery. However, the physical symptoms can be misleading for a decisive conclusion due to the patient's health condition or as a side-effect of anesthetic drugs. Recently, several neuroscientific research works are correlating the EEG signal with conscious states, which is likely to have less interference with the patient's medical condition. This research presents the first-of-its-kind hardware implemented automatic DOA computation system for mice.

Depth of Anesthesia Monitoring

The electroencephalogram (EEG) can be analyzed in its raw form for characteristic drug-induced patterns of change or summarized using mathematical parameters as a processed electroencephalogram (pEEG). In this article we aim to summarize the contemporary literature pertaining to the commonly available pEEG monitors including the effects of commonly used anesthetic drugs on the EEG and pEEG parameters, pEEG monitor pitfalls, and the clinical implications of pEEG monitoring for anesthesia, pediatrics, and intensive care.

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

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

Comparison of the Spectral Features of the Frontal Electroencephalogram in Patients Receiving Xenon and Sevoflurane General Anesthesia

BACKGROUND

Depth-of-anesthesia monitoring is often utilized for patients receiving xenon anesthesia. Processed electroencephalogram (EEG) depth-of-anesthesia monitoring relies to a significant extent on frequency domain analysis of the frontal EEG, and there is evidence that the spectral features observed under anesthesia vary significantly between anesthetic agents. The spectral features of the EEG during xenon anesthesia for a surgical procedure have not previously been described.

METHODS

Twenty-four participants scheduled for general anesthesia for lithotripsy were randomized to receive either xenon anesthesia or sevoflurane anesthesia. Frontal EEG recordings were obtained from each participant via the Brain Anesthesia Response Monitor (BARM). Twenty-two EEG recordings were suitable for analysis: 11 in participants who received sevoflurane and 11 in participants who received xenon. Spectrograms for the duration of the anesthetic episode were produced for each participant. Group-level spectral analysis was calculated for two 30-second EEG epochs: one recorded at awake baseline and the other during maintenance anesthesia. A linear mixed-effects model was utilized to compare the changes in 5 frequency bands from baseline to maintenance between the 2 groups.

RESULTS

The spectrograms of sevoflurane participants illustrate an increase in frontal delta (0.5-4 Hz), theta (4-8 Hz), and alpha (8-13 Hz) band power during maintenance anesthesia. In contrast, spectrograms of the xenon participants did not illustrate an increase in alpha power. The results of the linear mixed-effects model indicate that both agents were associated with a significant increase in delta power from baseline to maintenance. There was no significant difference in the magnitude of this increase observed between the agents. In contrast, sevoflurane anesthesia was associated with significantly greater absolute power in the theta, alpha, and beta (13-30 Hz) bands when compared to xenon. In terms of relative power, xenon was associated with a significant increase in delta power compared to sevoflurane, while sevoflurane was associated with greater increases in relative theta, alpha, and beta power.

CONCLUSIONS

Both xenon anesthesia and sevoflurane anesthesia were associated with significant increases in delta power. Sevoflurane anesthesia was also associated with increases in theta, alpha, and beta power, while xenon anesthesia was associated with greater consolidation of power in the delta band. Xenon anesthesia and sevoflurane anesthesia are associated with distinct spectral features. These findings suggest that appropriate depth-of-anesthesia monitoring may require the development of agent-specific spectral measures of unconsciousness.

Using the Perfusion Index to predict changes in the depth of anesthesia in children compared with the A-line Autoregression Index: an observational study

BACKGROUND

We investigated the performance of the Perfusion Index (PI) derived from pulse oximetry waveform as a tool for assessment of anesthetic depth in comparison with A-line Autoregression Index (AAI) derived from analysis of Middle-Latency Auditory Evoked Potentials (MLAEP) waveform integrated by aepEXplus monitor in children receiving sevoflurane anesthesia for tonsillectomy.

METHODS

Forty-one patients (4-12 years old) were included in this study. The PI and AAI were recorded simultaneously every minute during different stages of anesthesia delivery. The statistical tests included descriptive analysis, significance tests, correlation tests, and Receiver Operating Characteristic (ROC) curve. The AAI served as a reference.

RESULTS

The PI significantly decreased during light anesthesia and recovery, and significantly increased during deeper planes of anesthesia, with an inverse mirror-image relationship with the AAI. A negative correlation of low to moderate degree was detected between PI and AAI during the study (p > 0.05), that reached a statistical significance at the 5th minute during sevoflurane mask induction (r = -0.457, p = 0.008). ROC analysis at an AAI < 25 extracted the best cut-off value for PI before intubation as 1.48 (AUC = 0.698 [0.537-0.859], 94.4% sensitivity, 44.5% specificity) and at 10-minute intraoperatively as 2.4 (AUC = 0.537 [0.354-0.721], 91.7% sensitivity, 31% specificity). During recovery, at an AAI ≥ 50, the best cutoff was 1.82 (AUC = 0.661 [0.46-0.863], 100% sensitivity and 50% specificity) 2 minutes before spontaneous eye opening.

CONCLUSIONS

Compared with the AAI, the PI can track changes in depth of anesthesia in pediatric patients undergoing tonsillectomy under sevoflurane anesthesia.

TRIAL REGISTRATION

Clinical Trials. Gov. Identifier: NCT03412214.

Update on the SedLine® algorithm for calculating the Patient State Index of older individuals during general anesthesia: a randomized controlled trial

BACKGROUND

The SedLine^® sensor processes (Masimo Corporation; Irvine, CA, USA) raw electroencephalogram (EEG) signals and displays the depth of sedation as a Patient State Index (PSi). Reliance on standard processed EEG data and failure to recognize age-related effects can lead to an erroneous interpretation that low-amplitude EEG findings in an older patient signify an insufficient depth of anesthesia presented as abnormally high PSi values (AHPSi). We hypothesized that the incidence of AHPSi would decrease with the use of the recently-updated version of the SedLine^® sensor, in which the Bispectral Index (BIS) values were used to titrate anesthesia.

METHODS

Thirty-three patients undergoing sevoflurane-remifentanil anesthesia were randomized into two groups. SedLine^® sensors designed based on an old (v.1203) or updated (v.2000) algorithms were used. The BIS (v.4.1) and absolute index of total EEG power (TP) were simultaneously recorded. The attending anesthesiologists titrated the anesthetics, and BIS was maintained at 40-60. The incidence of AHPSi (PSi>50 with BIS 40-60) was calculated during the first 30 min after the start of surgery.

RESULTS

Compared to the old algorithm group, the incidence of AHPSi was significantly lower in the updated algorithm group (26.7% vs. 4.2%, P<0.001). Lower TP values and the use of the old algorithm have significant effect on increased PSi values (P<0.001).

CONCLUSIONS

The incidence of AHPSi decreased with the use of the updated version of the SedLine^® algorithm.

Delayed Obstructive Hydrocephalus After Cardiac Surgery With Cardiopulmonary Bypass in a Patient With Cerebellar Infarction: A Case Report

Obstructive hydrocephalus caused by brainstem compression is a life-threatening complication and usually occurs within 6 days, with peak on day 3 after onset of cerebellar infarction. We present a case of obstructive hydrocephalus that developed on day 8 in a patient with cerebellar infarction. A 39-year-old man with cerebellar infarction caused by myocardial infarction-related intraventricular thrombus underwent left ventricular thrombectomy under cardiopulmonary bypass. He was lucid postoperatively, but his consciousness was diminished on day 8 because of obstructive hydrocephalus. Cerebral edema due to cardiopulmonary bypass may contribute to delayed onset of obstructive hydrocephalus, especially in patients with large-sized cerebellar infarction.

Poincaré Plot Area of Gamma-Band EEG as a Measure of Emergence From Inhalational General Anesthesia

The Poincaré plot obtained from electroencephalography (EEG) has been used to evaluate the depth of anesthesia. A standalone EEG Analyzer application was developed; raw EEG signals obtained from a bispectral index (BIS) monitor were analyzed using an on-line monitoring system. Correlations between Poincaré plot parameters and other measurements associated with anesthesia depth were evaluated during emergence from inhalational general anesthesia. Of the participants, 20 were adults anesthetized with sevoflurane (adult_{_SEV}), 20 were adults anesthetized with desflurane (adult_{_DES}), and 20 were pediatric patients anesthetized with sevoflurane (ped_{_SEV}). EEG signals were preprocessed through six bandpass digital filters (f0: 0.5–47 Hz, f1: 0.5–8 Hz, f2: 8–13 Hz, f3: 13–20 Hz, f4: 20–30 Hz, and f5: 30–47 Hz). The Poincaré plot-area ratio (PP_AR = PP_{A_fx}/PP_{A_f0}, fx = f1∼f5) was analyzed at five frequency ranges. Regardless of the inhalational anesthetic used, there were strong linear correlations between the logarithm of PP_AR at f5 and BIS (R² = 0.67, 0.79, and 0.71, in the adult_{_SEV}, adult_{_DES}, and ped_{_SEV} groups, respectively). As an additional observation, a part of EMG activity at the gamma range of 30–47 Hz probably influenced the calculations of BIS and PP_{AR_f5} with a non-negligible level. The logarithm of PP_AR in the gamma band was most sensitive to state changes during the emergence process and could provide a new non-proprietary parameter that correlates with changes in BIS during measurement of anesthesia depth.

Offline comparison of processed electroencephalogram monitors for anaesthetic-induced electroencephalogram changes in older adults

BACKGROUND

Several devices record and interpret patient brain activity via electroencephalogram (EEG) to aid physician assessment of anaesthetic effect. Few studies have compared EEG monitors on data from the same patient. Here, we describe a set-up to simultaneously compare the performance of three processed EEG monitors using pre-recorded EEG signals from older surgical patients.

METHODS

A playback system was designed to replay EEG signals into three different commercially available EEG monitors. We could then simultaneously calculate indices from the SedLine® Root (Masimo Inc., Irvine, CA, USA; patient state index [PSI]), bilateral BIS VISTA™ (Medtronic Inc., Minneapolis, MN, USA; bispectral index [BIS]), and Datex Ohmeda S/5 monitor with the Entropy™ Module (GE Healthcare, Chicago, IL, USA; E-entropy index [Entropy]). We tested the ability of each system to distinguish activity before anaesthesia administration (pre-med) and before/after loss of responsiveness (LOR), and to detect suppression incidences in EEG recorded from older surgical patients receiving beta-adrenergic blockers. We show examples of processed EEG monitor output tested on 29 EEG recordings from older surgical patients.

RESULTS

All monitors showed significantly different indices and high effect sizes between comparisons pre-med to after LOR and before/after LOR. Both PSI and BIS showed the highest percentage of deeply anaesthetised indices during periods with suppression ratios (SRs) > 25%. We observed significant negative correlations between percentage of suppression and indices for all monitors (at SR >5%).

CONCLUSIONS

All monitors distinguished EEG changes occurring before anaesthesia administration and during LOR. The PSI and BIS best detected suppressed periods. Our results suggest that the PSI and BIS monitors might be preferable for older patients with risk factors for intraoperative awareness or increased sensitivity to anaesthesia.

Normative values for SedLine-based processed electroencephalography parameters in awake volunteers: a prospective observational study

Processed electroencephalography (pEEG) is used to monitor depth of anaesthesia and/or sedation. A novel device (SedLine®) has been recently introduced into clinical practice. However, there are no published data on baseline SedLine values for awake adult subjects. We aimed to determine baseline values for SedLine-derived parameters in eyes-open and eyes-closed states. We performed a prospective observational study in healthy volunteers. SedLine EEG-derived parameters were recorded for 2 min with eyes closed and 8 min with eyes open. We determined the overall reference range for each value, as well as the reference range in each phase. We investigated changes in recorded parameters between the two phases, and the interaction between EMG, baseline characteristics, and Patient State Index (PSI). We collected data from 50 healthy volunteers, aged 23-63 years. Median PSI was 94 (92-95) with eyes open and 88 (87-91) with eyes closed (p < 0.001 for open versus close). EMG activity decreased from 47.2% (46.6-47.9) with eyes open to 28.6% (28.0-29.3) with eyes closing (p < 0.001). There was a significant positive correlation between EMG and PSI with eyes closed (p = 0.01) but not with eyes open, which was confirmed with linear regression analysis (p = 0.01). In awake volunteers, keeping eyes open induces significant changes to SedLine-derived parameters, most likely due to increased EMG activity (e.g. eye blinking). These findings have implications for the clinical interpretation of PSI parameters and for the planning of future research.