Spectral Edge Frequency Research Articles

Quantitative electroencephalography predicts postoperative delirium in cardiac surgical patients after cardiopulmonary bypass: a prospective observational study.

Despite its frequency and associated negative effect, delirium remains poorly recognized in postoperative patients after ICU admission, especially among those who have undergone cardiac surgery with cardiopulmonary bypass. Postoperative delirium is triggered by a wide variety of acute medical conditions associated with impaired neuronal network connectivity. The lack of objective biomarkers primarily hinders the early detection of delirium. Seeking early biomarkers for tracking POD could potentially assist in predicting the onset of delirium and assessing the severity of delirium and response to interventions. QEEGs were taken from 46 sedated postoperative patients, with 24 of them having undergone cardiac surgery. The assessment of delirium was performed twice daily using the Confusion Assessment Method for the ICU (CAM-ICU) to screen for postoperative delirium (POD). QEEG data were interpreted clinically by neurophysiologists and processed by open-source EEGLAB to identify features in patients who had or did not have POD after cardiac or non-cardiac surgery. The incidence of delirium in patients after undergoing cardiac surgery was nine times greater than in those after non-cardiac surgeries (41.7% vs. 4.5%; p = 0.0046). Patients with delirium experienced longer use of mechanical ventilation (118 h (78,323) compared to 20 h (18,23); p < 0.0001) and an extended ICU length of stay (7 days (6, 20) vs. 2 days (2, 4); p < 0.0001). The depth of anesthesia, as measured by RASS scores (p = 0.3114) and spectral entropy (p = 0.1504), showed no significant difference. However, notable differences were observed between delirious and non-delirious patients in terms of the amplitude-integrated EEG (aEEG) upper limit, the relative power of the delta band, and spectral edge frequency 95 (SEF95) (p = 0.0464, p = 0.0417, p = 0.0337, respectively). In a homogenous population of sedated postoperative patients, robust qEEG parameters strongly correlate with delirium and could serve as valuable biomarkers for early detection of delirium and assist in clinical decision-making.

Quantitative electroencephalogram in term neonates under different sleep states.

Electroencephalogram (EEG) can be used to assess depth of consciousness, but interpreting EEG can be challenging, especially in neonates whose EEG undergo rapid changes during the perinatal course. EEG can be processed into quantitative EEG (QEEG), but limited data exist on the range of QEEG for normal term neonates during wakefulness and sleep, baseline information that would be useful to determine changes during sedation or anesthesia. We aimed to determine the range of QEEG in neonates during awake, active sleep and quiet sleep states, and identified the ones best at discriminating between the three states. Normal neonatal EEG from 37 to 46weeks were analyzed and classified as awake, quiet sleep, or active sleep. After processing and artifact removal, total power, power ratio, coherence, entropy, and spectral edge frequency (SEF) 50 and 90 were calculated. Descriptive statistics were used to summarize the QEEG in each of the three states. Receiver operating characteristic (ROC) curves were used to assess discriminatory ability of QEEG. 30 neonates were analyzed. QEEG were different between awake vs asleep states, but similar between active vs quiet sleep states. Entropy beta, delta2 power %, coherence delta2, and SEF50 were best at discriminating awake vs active sleep. Entropy beta had the highest AUC-ROC ≥ 0.84. Entropy beta, entropy delta1, theta power %, and SEF50 were best at discriminating awake vs quiet sleep. All had AUC-ROC ≥ 0.78. In active sleep vs quiet sleep, theta power % had highest AUC-ROC > 0.69, lower than the other comparisons. We determined the QEEG range in healthy neonates in different states of consciousness. Entropy beta and SEF50 were best at discriminating between awake and sleep states. QEEG were not as good at discriminating between quiet and active sleep. In the future, QEEG with high discriminatory power can be combined to further improve ability to differentiate between states of consciousness.

Analysis of Brain Stress in Response to Temperature Changes under Agricultural Work Using Electroencephalogram Measurement

Agricultural workers suffer from various physical problems and mental stress, including depression and insomnia. Various factors affect brain stress, including harsh agricultural working conditions. Further brain stress may also be due to changes in working conditions such as temperature, noise, and vibration. This study aimed to determine the brain stress in response to ambient temperature changes under agricultural work using agricultural machinery. The electroencephalograms (EEGs) of 17 agricultural workers who work using various agricultural machines was measured and analyzed. The EEG was measured for 3 min at the inactive and active state of agricultural work, respectively, at 24 °C, 28 °C, and 32 °C. The EEG was analyzed using the stress indices such as spectral edge frequency 95% (SEF95%), relative gamma power (RGP), and EEG-based working index (EWI). The EEG analysis indicated that brain stress was generated when the subjects performed the agricultural work after an inactive state. Additionally, as the temperature increased to ≥24 °C, the brain regions where SEF95%, RGP, and EWI exhibited an increase were identified. The findings of this study can be used as basic data in determining the working stress in agricultural workers during work as the ambient temperature changes from 24 °C to 32 °C.

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.

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. 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. 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). 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.

EEG response of dexmedetomidine during drug induced sleep endoscopy.

Dexmedetomidine is one of the anesthetics of choice for drug induced sleep endoscopy (DISE), with advantages including limited respiratory depression, analgesia, and decreased incidence of emergence delirium. However, challenges with determining sedation levels and prolonged recovery have limited its usage. An improved understanding of the effect of dexmedetomidine on the level of sedation and the corresponding electroencephalographic (EEG) changes could help overcome these barriers. Fifty-one patients received dexmedetomidine sedation with Richmond Agitation-Sedation Scale (RASS) score assessment and continuous EEG monitoring via SedLine for DISE. We constructed a pharmacokinetic model to determine continuous dexmedetomidine blood concentration. From the SedLine, we extracted the patient state index (PSI), and from the EEG we calculated the spectral edge frequency 95% (SEF95) and the correlation dimension (CD), a type of fractal dimension used to assess the complexity of a system. These metrics were subsequently compared against one another and with the dexmedetomidine concentration. Our pharmacokinetic model yielded a two-compartment model with volumes of 51.8 L and 106.2 L, with clearances of 69.5 and 168.9 L/h, respectively, and a time to effect of 9 min, similar to prior studies. Based on this model, decreasing RASS score, SEF95, CD, and PSI were all significantly associated with increasing dexmedetomidine concentration (p < 0.001, p = 0.006, p < 0.001 respectively). The CD, SEF95, and PSI better captured the effects of increasing dexmedetomidine concentration as compared to the RASS score. Simulating dexmedetomidine concentration based on titration to target levels derived from CD and PSI confirmed commonly used dexmedetomidine infusion dosages. Dexmedetomidine use for DISE confirmed previous pharmacokinetic models seen with dexmedetomidine. Complex EEG metrics such as PSI and CD, as compared to RASS score and SEF95, better captured changes in brain state from dexmedetomidine and have potential to improve the monitoring of dexmedetomidine sedation.

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

BackgroundSugammadex 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. MethodsWe 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. ResultsTwenty-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. ConclusionsAfter 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.

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

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. Prospective observational study. Cardiac surgery operating theatre. 28 patients undergoing elective cardiac surgery with CPB. 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. 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. 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.

Pre-Slaughter Stunning of Farmed Atlantic Halibut in CO2-Saturated Seawater: Assessment of Unconsciousness by Electroencephalography (EEG).

As fish welfare becomes a growing concern, it is important to ensure humane treatment during slaughter. This study aimed to assess the onset of unconsciousness in Atlantic halibut immersed in CO2-saturated seawater through electroencephalography (EEG). Of the 29 fish studied, 10 exhibited escape attempts, indicating aversion to CO2-saturated water despite its oxygenation. EEG signals showed four distinct phases: transitional, excitation (high amplitude-high frequency), suppressed, and iso-electric phases. The onset of the suppressed phase, indicative of unconsciousness, occurred on average 258.8 ± 46.2 s after immersion. The spectral analysis of the EEG signals showed a progressive decrease in median frequency, spectral edge frequency, and high frequency contribution, which corresponded to the gradual loss of consciousness. The study concludes that CO2-saturated water is not recommended for pre-slaughter handling of halibut due to the extended time required for the onset of unconsciousness and the observed aversive behaviour. Ensuring humane treatment during slaughter is important for addressing public concern and safeguarding fish welfare in all stages of production.

Time-trend analysis of the center frequency of the intrinsic mode function from the Hilbert–Huang transform of electroencephalography during general anesthesia: a retrospective observational study

BackgroundAnesthesiologists are required to maintain an optimal depth of anesthesia during general anesthesia, and several electroencephalogram (EEG) processing methods have been developed and approved for clinical use to evaluate anesthesia depth. Recently, the Hilbert–Huang transform (HHT) was introduced to analyze nonlinear and nonstationary data. In this study, we assessed whether the changes in EEG characteristics during general anesthesia that are analyzed by the HHT are useful for monitoring the depth of anesthesia.MethodsThis retrospective observational study enrolled patients who underwent propofol anesthesia. Raw EEG signals were obtained from a monitor through a previously developed software application. We developed an HHT analyzer to decompose the EEG signal into six intrinsic mode functions (IMFs) and estimated the instantaneous frequencies (HHT_IF) for each IMF. Changes over time in the raw EEG waves and parameters such as HHT_IF, BIS, spectral edge frequency 95 (SEF95), and electromyogram parameter (EMGlow) were assessed, and a Gaussian process regression model was created to assess the association between BIS and HHT_IF.ResultsWe analyzed EEG signals from 30 patients. The beta oscillation frequency range (13–25 Hz) was detected in IMF1 and IMF2 during the awake state, then after loss of consciousness, the frequency decreased and alpha oscillation (8–12 Hz) was detected in IMF2. At the emergence phase, the frequency increased and beta oscillations were detected in IMF1, IMF2, and IMF3. BIS and EMGlow changed significantly during the induction and emergence phases, whereas SEF95 showed a wide variability and no significant changes during the induction phase. The root mean square error between the observed BIS values and the values predicted by a Gaussian process regression model ranged from 4.69 to 9.68.ConclusionsWe applied the HHT to EEG analyses during propofol anesthesia. The instantaneous frequency in IMF1 and IMF2 identified changes in EEG characteristics during induction and emergence from general anesthesia. Moreover, the HHT_IF in IMF2 showed strong associations with BIS and was suitable for depicting the alpha oscillation. Our study suggests that the HHT is useful for monitoring the depth of anesthesia.

A Retrospective Study of the Patient State Index During General Anesthesia in Infants and Young Children.

This study described electroencephalogram (EEG) parameters in children under general anesthesia, which could monitor patient-specific brain responses to anesthetics and assess the effects of anesthesia. The objective was to detect the patient state index (PSI) and associated factors. We analyzed EEG parameters in patients in the age range 1 to 36 months. Patients were stratified into 2 groups as those aged 1 to 12 months and 13 to 36 months. Sixty-two patients were involved. Spectral edge frequency (SEF), PSI, and blood pressure were lower, and burst suppression rate (BSR) and heart rate were higher in the 1 to 12 months group. The SEF was associated with PSI in both groups. Age and blood pressure were positively associated with PSI, and BSR was negatively related to PSI in children under 1 year of age. Blood pressure was not associated with PSI in the 13 to 36 months age group. We found that the PSI levels did not accurately assess the depth of anesthesia in children under 1 year of age.

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

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. 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). 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). 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.

How is depth of anaesthesia assessed in experimental pigs? A scoping review.

Despite the large number of pigs involved in translational studies, no gold standard depth of anaesthesia indicators are available. We undertook a scoping review to investigate and summarize the evidence that sustains or contradicts the use of depth of anaesthesia indicators in this species. Medline, Embase and CAB abstract were searched up to September 22nd 2022. No limits were set for time, language and study type. Only original articles of in vivo studies using pigs or minipigs undergoing general anaesthesia were included. The depth of anaesthesia indicators reported in the selected papers were divided in two categories: A, indicators purposely investigated as method to assess depth of anaesthesia; B, indicators reported but not investigated as method to assess depth of anaesthesia. Out of 13792 papers found, 105 were included after the screening process. Category A: 17 depth of anaesthesia indicators were found in 19 papers. Studies were conducted using inhalant anaesthetics as the main anaesthetic agent in the majority of the cases (13/19 = 68.4%), while 3/19 (15.8%) used propofol. The most investigated depth of anaesthesia indicators were bispectral index (8/19 = 42.1%) and spectral edge frequency 95% (5/19 = 26.3%). Contrasting results about the specific usefulness of each depth of anaesthesia indicators were reported. Category B: 23 depth of anaesthesia indicators were found in 92 papers. The most reported depth of anaesthesia indicators were: motor response following a stimulus (37/92 = 40.2%), depth of anaesthesia scores (21/92 = 23.3%), bispectral index (16/92 = 17.8%) and spectral edge frequency 95% (9/92 = 9.8%). Results highlight the lack of scientifically valid and reliable indicators to ensure adequate depth of anaesthesia in pigs.

Electroencephalographic and Cardiovascular Changes Associated with Propofol Constant Rate of Infusion Anesthesia in Young Healthy Dogs.

This study aimed to evaluate electroencephalography (EEG) and cardiovascular changes associated with propofol constant rate of infusion (CRI) anesthesia in dogs. Six dogs were each given propofol CRI to induce different anesthetic phases including induction (1 mg/kg/min for 10 min), and decremental maintenance doses of 2.4 mg per kg per min, 1.6 mg per kg per min, and 0.8 mg per kg per minute over 45 min. Processed EEG indices including patient state index (PSI), (burst) suppression ratio (SR), and spectral edge frequency (95%) were obtained continuously until the dogs recovered to sternal recumbency. The dogs were intubated and ventilated. Cardiovascular and EEG index values were compared between anesthetic phases. The PSI, SR, mean arterial blood pressure, and subjective anesthetic depth scores were highly correlated throughout anesthetic depth changes. The PSI decreased from 85.0 ± 17.3 at awake to 66.0 ± 29.0 at induction, and then sharply reduced to 19.7 ± 23.6 during maintenance and returned to 61.5 ± 19.2 at extubation. The SR increased from 15.4 ± 30.9% at induction to 70.9 ± 39.8% during maintenance and decreased to 3.4 ± 8.9% at extubation. We concluded that EEG indices can be used to aid in tracking ongoing brain state changes during propofol anesthesia in dogs.

Preoperative characterization of baseline EEG recordings for risk stratification of post-anesthesia care unit delirium

Study objectiveDelirium in the post-anesthesia care unit (PACU-D) presents a serious condition with a high medical and socioeconomic impact. In particular, PACU-D is among common postoperative complications of elderly patients. As PACU-D may be associated with postoperative delirium, early detection of at-risk patients and strategies to prevent PACU-D are important. We characterized EEG baseline signatures of patients who developed PACU-D following surgery and general anesthesia and patients who did not. Design and settingWe conducted a post-hoc analysis of preoperative EEG recordings between patients with and without PACU-D, as indicated by positive bCAM scores post general anesthesia and surgery. Patients and measurementsPreoperative baseline EEG recordings from 89 patients were recorded at controlled eyes-open (focused wakefulness) and eyes-closed (relaxed wakefulness) conditions. We computed power spectral densities, permutation entropy, spectral entropy and spectral edge frequency to see if these parameters can reflect potential baseline EEG differences between PACU-D (31.5%) and noPACU-D (68.5%) patients. Wilcoxon's Rank Sum Test as well as AUC values were used to determine statistical significance. Main resultsBaseline EEG recordings showed significant differences between PACU-D and noPACU-D patients preoperatively. Compared to the noPACU-D group, PACU-D patients presented with lower power in higher frequencies during relaxed and focused wakefulness alike. These differences in power led to AUC values of 0.73 [0.59;0.85] (permutation entropy) and 0.72 [0.61;0.83] (spectral edge frequency) indicative of a “fair” performance to separate patients with and without PACU-D. ConclusionsThe baseline EEG of relaxed wakefulness as well as focused wakefulness may be used to assess the risk of developing PACU-D following surgery under general anesthesia. Moreover, routinely used monitoring parameters capture these differences as well, potentially allowing an easy transfer to clinical settings.Clinical trial number: NCT03775356

Performance of the SEDLine Monitor: Age Dependency and Time Delay.

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. 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. 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. 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.

Partial wavelet coherence as a robust method for assessment of neurovascular coupling in neonates with hypoxic ischemic encephalopathy

In neonates with hypoxic ischemic encephalopathy, the computation of wavelet coherence between electroencephalogram (EEG) power and regional cerebral oxygen saturation (rSO2) is a promising method for the assessment of neurovascular coupling (NVC), which in turn is a promising marker for brain injury. However, instabilities in arterial oxygen saturation (SpO2) limit the robustness of previously proposed methods. Therefore, we propose the use of partial wavelet coherence, which can eliminate the influence of SpO2. Furthermore, we study the added value of the novel NVC biomarkers for identification of brain injury compared to traditional EEG and NIRS biomarkers. 18 neonates with HIE were monitored for 72 h and classified into three groups based on short-term MRI outcome. Partial wavelet coherence was used to quantify the coupling between C3–C4 EEG bandpower (2–16 Hz) and rSO2, eliminating confounding effects of SpO2. NVC was defined as the amount of significant coherence in a frequency range of 0.25–1 mHz. Partial wavelet coherence successfully removed confounding influences of SpO2 when studying the coupling between EEG and rSO2. Decreased NVC was related to worse MRI outcome. Furthermore, the combination of NVC and EEG spectral edge frequency (SEF) improved the identification of neonates with mild vs moderate and severe MRI outcome compared to using EEG SEF alone. Partial wavelet coherence is an effective method for removing confounding effects of SpO2, improving the robustness of automated assessment of NVC in long-term EEG-NIRS recordings. The obtained NVC biomarkers are more sensitive to MRI outcome than traditional rSO2 biomarkers and provide complementary information to EEG biomarkers.

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

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. 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. 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). 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.

Evaluation of patient state index, bispectral index, and entropy during drug induced sleep endoscopy with dexmedetomidine.

Multiple electroencephalographic (EEG) monitors and their associated EEG markers have been developed to aid in assessing the level of sedation in the operating room. While many studies have assessed the response of these markers to propofol sedation and anesthetic gases, few studies have compared these markers when using dexmedetomidine, an alpha-2 agonist. Fifty-one patients underwent drug induced sleep endoscopy with dexmedetomidine sedation. Continuous EEG was captured using SedLine (Masimo, Inc), and a playback system was used to extract the bispectral index (BIS) (Medtronic Inc), the patient state index (PSI) (Masimo, Inc), the state and response Entropy (GE Healthcare), and calculate the spectral edge frequency 95% (SEF95). Richmond Agitation-Sedation Scale (RASS) scores were assessed continually throughout the procedure and in recovery. We assessed the correlation between EEG markers and constructed ordinal logistic regression models to predict the RASS score and compare EEG markers. All three commercial EEG metrics were significantly associated with the RASS score (p < 0.001 for all metrics) whereas SEF95 alone was insufficient at characterizing dexmedetomidine sedation. PSI and Entropy achieved higher accuracy at predicing deeper levels of sedation as compared to BIS (PSI: 58.3%, Entropy: 58.3%, BIS: 44.4%). Lightening secondary to RASS score assessment is significantly captured by all three commercial EEG metrics (p < 0.001). Commercial EEG monitors can capture changes in the brain state associated with the RASS score during dexmedetomidine sedation. PSI and Entropy were highly correlated and may be better suited for assessing deeper levels of sedation.

Electroencephalography spectral edge frequency and suppression rate-guided sedation in patients with COVID-19: A randomized controlled trial.

Sedation in coronavirus disease 2019 (COVID-19) patients has been identified as a major challenge. We aimed to investigate whether the use of a multiparameter electroencephalogram (EEG) protocol to guide sedation in COVID-19 patients would increase the 30-day mechanical ventilation-free days (VFD). We conducted a double-blind randomized clinical trial. We included patients with severe pneumonia due to COVID-19 who required mechanical ventilation (MV) and deep sedation. We randomized to the control (n = 25) or multiparameter group (n = 25). Sedation in the intervention group was administered following the standard institutional protocols together with a flow chart designed to reduce the propofol administration dose if the EEG suppression rate was over 2% or the spectral edge frequency 95 (SEF95) was below 10 Hz. We performed an intention-to-treat analysis to evaluate our primary outcome (30-day VFD). There was no difference in VFD at day 30 (median: 11 [IQR 0-20] days in the control group vs. 0 [IQR 0-21] days in the BIS multiparameter group, p = 0.87). Among secondary outcomes, we documented a 17% reduction in the total adjusted propofol administered during the first 5 days of the protocol [median: 2.3 (IQR 1.9-2.8) mg/k/h in the control group vs. 1.9(IQR 1.5-2.2) mg/k/h in the MP group, p = 0.005]. This was accompanied by a higher average BIS value in the intervention group throughout the treatment period. A sedation protocol guided by multivariate EEG-derived parameters did not increase the 30-day VFD. However, the intervention led to a reduction in total propofol administration.

Perioperative Brain Function Monitoring with Electroencephalography in Horses Anesthetized with Multimodal Balanced Anesthetic Protocol Subjected to Surgeries.

Simple SummaryThis study aimed to investigate the use of electroencephalography (EEG) and EEG-derived (processed) indices for detecting brain activity changes perioperatively in 12 anesthetized adult horses subjected to various surgery. Frontal electrodes together with Sedline/Root monitor were used on these horses from soon after anesthesia induction and continued until the horse first attempted to stand in recovery. The EEG waves were characterized by low-frequency high amplitude alpha, theta, and alpha waves during the isoflurane maintenance and surgery, which is commonly observed in profound anesthesia. The processed EEG indices including Patient State Index, Burst Suppression Ratio, and 95% Spectral Edge Frequency changed significantly between the stages (induction, surgery, and recovery) of anesthesia. Collectively, the presence of the slow EEG wave activities and the presence of burst suppression implies that these horses were profoundly unconscious during the anesthesia. We concluded that the use of EEG in conjunction with traditional cardiorespiratory monitoring provides clinically relevant information about perioperative brain state changes in the anesthetized horses.This study aimed to investigate the use of electroencephalography (EEG) for detecting brain activity changes perioperatively in anesthetized horses subjected to surgery. Twelve adult horses undergoing various surgeries were evaluated after premedication with xylazine and butorphanol, induction with ketamine, midazolam, and guaifenesin, and maintenance with isoflurane. The frontal EEG electrodes were placed after the horse was intubated and mechanically ventilated. The EEG data were collected continuously from Stage (S)1—transition from induction to isoflurane maintenance, S2—during surgery, S3—early recovery before xylazine sedation (0.2 mg kg IV), and S4—recovery after xylazine sedation. The Patient State Index (PSI), (Burst) Suppression Ratio (SR), and 95% Spectral Edge Frequency (SEF95) were compared across the stages. The PSI was lowest in S2 (20.8 ± 2.6) and increased to 30.0 ± 27.7 (p = 0.005) in S3. The SR increased from S1 (5.5 ± 10.7%) to S3 (32.7 ± 33.8%, p = 0.0001). The spectral power analysis showed that S3 had a significantly higher content of delta wave activity (0.1–4 Hz) in the EEG and lower relative power in the 3 Hz to 15 Hz range when compared to S1 and S2. A similar result was observed in S4, but the lower power was in a narrower range, from 3 Hz to 7 Hz, which indicate profound central nervous system depression potentiated by xylazine, despite the cessation of isoflurane anesthesia. We concluded that the use of EEG provides clinically relevant information about perioperative brain state changes of the isoflurane-anesthetized horse.