Continuous electroencephalogram monitoring in the intensive care unit

Implementation of 2HELPS2B Seizure Risk Score: A Cost-Effective Approach to Seizure Detection in the Intensive Care Units

Background and Objectives

Continuous EEG (cEEG) has become a standard for monitoring critically ill patients, but it is resource-intensive with limited availability. The 2HELP2B seizure risk score can help stratify seizure risk and aid in clinical decision making to optimize duration of monitoring. This study aimed to incorporate the 2HELPS2B score to inform cEEG duration and provide cost-effective care without compromising seizure detection.

Methods

We conducted a quality improvement study that targeted clinical workflow and seizure risk stratification in the intensive care units of a tertiary academic hospital. The study included adult patients who underwent cEEG between June 2020 and December 2022 (n = 552), after excluding patients undergoing cEEG for management of status epilepticus, spell characterization, intracranial pressure monitoring, and post-cardiac arrest (n = 129). We performed a retrospective chart review to establish baseline cEEG volume, seizure incidence, and monitoring duration. We then introduced the 2HELPS2B risk score through multidisciplinary education and used published recommendations to suggest optimal cEEG duration. After the intervention, we analyzed the impact of integrating the 2HELPS2B score on cEEG duration and seizure detection rates.

Results

Of 552 patients, most were low risk (n = 311, 56.3%), followed by moderate risk (n = 189, 34.2%) and high risk (n = 52, 9.4%). Before the intervention, cEEG duration was similar for all risk groups. After implementation of the 2HELPSB score, there was a significant reduction in cEEG duration for low-risk and moderate-risk patients (low 36.3 vs 23.8 hours; p < 0.0001, moderate 36.5 vs 29.3 hours; p = 0.01) and no significant change for the high-risk group (41.3 vs 40.4 hours; p = 0.92). Seizure detection was low except for the high-risk group (1.3% vs 7.9% vs 39.1%). Reduction in cEEG duration after implementation of the 2HELPS2B score did not lead to a significant change in seizure detection (0.6% vs 9% vs 37.9%).

Discussion

Most critically ill patients had low or moderate seizure risk and, accordingly, a low incidence of seizures detected during cEEG. Implementing the 2HELPS2B seizure risk score allowed customization of cEEG duration for individual patients, applying the practice of precision medicine. This approach successfully improved cEEG utilization without compromising seizure detection. In conclusion, implementing seizure risk stratification can provide cost-effective monitoring and improve cEEG access.

Electroencephalogram monitoring during anesthesia and critical care: a guide for the clinician

Perioperative anesthetic, surgical and critical careinterventions can affect brain physiology and overall brain health. The clinical utility of electroencephalogram (EEG) monitoring in anesthesia and intensive care settings is multifaceted, offering critical insights into the level of consciousness and depth of anesthesia, facilitating the titration of anesthetic doses, and enabling the detection of ischemic events and epileptic activity. Additionally, EEG monitoring can aid in predicting perioperative neurocognitive disorders, assessing the impact of systemic insults on cerebral function, and informing neuroprognostication. This review provides a comprehensive overview of the fundamental principles of electroencephalography, including the foundations of processed and quantitative electroencephalography. It further explores the characteristic EEG signatures associated wtih anesthetic drugs, the interpretation of the EEG data during anesthesia, and the broader clinical benefits and applications of EEG monitoring in both anesthetic practice and intensive care environments.

Utility and Value of Movement Recording with Combined EEG-EMG Monitoring in the Intensive Care Unit

Continuous electroencephalographic (EEG) monitoring has become a standard of care in several contexts in the intensive care unit (ICU), especially for the management of refractory status epilepticus. ICU patients often present movement disorders that may be of epileptic or nonepileptic origin, and their correct identification is crucial for the diagnostic and therapeutic process. Video analysis is often insufficient to precisely detect or characterize movement disorders and the ICU environment is prone to many artifacts. Combined EEG electromyogram (EMG) monitoring can enhance the detection of epileptic seizures with subtle motor expression and help identify nonepileptic movement disorders, such as postanoxic myoclonus, dystonia, or tremor. We will review the various scenarios in which combined EEG-EMG monitoring is useful in routine ICU practice. We also provide a practical guide for easily placing surface EMG electrodes during continuous EEG recording, along with clinical examples to illustrate the significance of this combined approach.

Advances, challenges, and prospects of electroencephalography-based biomarkers for psychiatric disorders: a narrative review

Owing to a lack of appropriate biomarkers for accurate diagnosis and treatment, psychiatric disorders cause significant distress and functional impairment, leading to social and economic losses. Biomarkers are essential for diagnosing, predicting, treating, and monitoring various diseases. However, their absence in psychiatry is linked to the complex structure of the brain and the lack of direct monitoring modalities. This review examines the potential of electroencephalography (EEG) as a neurophysiological tool for identifying psychiatric biomarkers. EEG noninvasively measures brain electrophysiological activity and is used to diagnose neurological disorders, such as depression, bipolar disorder (BD), and schizophrenia, and identify psychiatric biomarkers. Despite extensive research, EEG-based biomarkers have not been clinically utilized owing to measurement and analysis constraints. EEG studies have revealed spectral and complexity measures for depression, brainwave abnormalities in BD, and power spectral abnormalities in schizophrenia. However, no EEG-based biomarkers are currently used clinically for the treatment of psychiatric disorders. The advantages of EEG include real-time data acquisition, noninvasiveness, cost-effectiveness, and high temporal resolution. Challenges such as low spatial resolution, susceptibility to interference, and complexity of data interpretation limit its clinical application. Integrating EEG with other neuroimaging techniques, advanced signal processing, and standardized protocols is essential to overcome these limitations. Artificial intelligence may enhance EEG analysis and biomarker discovery, potentially transforming psychiatric care by providing early diagnosis, personalized treatment, and improved disease progression monitoring.

Effects of oral pregabalin on postoperative sleep of patients after video-assisted thoracoscopic surgery: a randomized double-blind controlled trial

BACKGROUND

The aim of this study was to explore the effect of oral pregabalin at varying concentrations on postoperative sleep of patients undergoing video-assisted thoracic surgery (VATS), and to identify the optimal dosage.

METHODS

A total of 120 VATS-treated patients admitted from June 2023 to October 2023 were randomly assigned to be orally administered with 75 mg pregabalin, 150 mg pregabalin and starch capsules (control group) at a 1:1:1 ratio. One capsule of pregabalin (75 mg) and one capsule of placebo with the same shape and odor, two capsules of pregabalin (150 mg), and two capsules of placebo with the same shape and odor were administered orally to patients in the three groups on the night of surgery, and in the morning and evening of postoperative days 2 and 3. The primary outcome was the incidence of postoperative sleep disturbance (PSD) on postoperative day 1 (POD1). The secondary outcomes included the St.Mary's Hospital Sleep Questionnaire (SMH), the Pittsburg Sleep Quality Index (PSQI) and pain intensity measured with a Numerical Rating Scale (NRS). Multivariate logistic regression analysis was performed to identify risk factors for PSD in VATS-treated patients.

RESULTS

The incidence of PSD on POD1 in the 75 mg pregabalin group and 150 mg pregabalin group was significantly lower than that of the control group (45.0% vs. 42.5% vs. 72.5%; P<0.0167 for two-by-two comparisons of groups A and B with group C, respectively). The SMH scores at night on POD1-3 were significantly higher in the 75 mg pregabalin group and 150 mg pregabalin group than those of the control group (P<0.05). Since there was definitive lower incidence of pain in the experimental groups,the median NRS scores of the incisional pain on POD2-3 were significantly lower in the 75 mg pregabalin group and 150 mg pregabalin group (P<0.05). The incidence of dizziness in the 150 mg pregabalin group was significantly higher than that of the 75 mg pregabalin group and control group (55.0% vs. 25.0% vs. 32.5%; P<0.0167 for two-by-two comparisons of groups A and C with group B, respectively). NRS score on POD1, preoperative PSQI and Self-Rating Depression Scale scores were risk factors for PSD in VATS-treated patients.

CONCLUSIONS

Oral administration of 75 mg or 150mg pregabalin for consecutive three days after VATS effectively reduces the incidence of PSD and improves the quality of sleep.

Lack of Continuous Video EEG Surveillance Results in Delayed Event Reporting

Although real-time event detection during video EEG recording is required to ensure patients' safety, it is limited by the technologists' availability. We sought to explore the efficiency of real-time event detection by the EEG technologists in a single tertiary academic center. We retrospectively reviewed events from continuous inpatient video EEGs (cEEGs) and epilepsy monitoring unit (EMU) recordings in January 2017, when real-time surveillance was only available during the night shift, and June 2017, when a dedicated neurodiagnostic EEG technologist was available for real-time monitoring during all shifts. The events were categorized into those detected immediately (eyes-on), later in the same shift (delayed) or identified on the subsequent shift (missed). Chi-square and Fisher's exact tests were used for statistical comparisons. In January 2017, there were 25 patients (117 days of monitoring) in the EMU and 54 inpatients (146 days of monitoring) on cEEG with 92 total events, (39% seizures). In June 2017, there were 30 patients (133 days of monitoring) in the EMU and 47 additional inpatients (80 days of monitoring) on cEEG with 110 total events, (39% seizures). The number of events identified in real time was low and did not significantly differ among shifts regardless of the availability of the monitoring technologist. Most events were identified at the time of subsequent EEG scanning by the EEG technologist. Partial staffing for continuous video EEG surveillance is insufficient to identify events in real time. EEG technologists are able to identify events during regular EEG scanning.

The Role of Routine Electroencephalography in the Diagnosis of Seizures in Medical Intensive Care Units

Seizures should be diagnosed and treated to ensure optimal health outcomes in critically ill patients admitted in the medical intensive care unit (MICU). Continuous electroencephalography is still infrequently used in the MICU. We investigated the effectiveness of routine EEG (rEEG) in detecting seizures in the MICU. A total of 560 patients admitted to the MICU between October 2018 and March 2023 and who underwent rEEG were reviewed. Seizure-related rEEG constituted 47% of all rEEG studies. Totally, 39% of the patients experienced clinical seizures during hospitalization; among them, 48% experienced the seizure, and 13% experienced their first seizure after undergoing an rEEG study. Seventy-seven percent of the patients had unfavorable short-term outcomes. Patients with cardiovascular diseases were the most likely to have the suppression/burst suppression (SBS) EEG pattern and the highest mortality rate. The rhythmic and periodic patterns (RPPs) and electrographic seizure (ESz) EEG pattern were associated with seizures within 24 h after rEEG, which was also related to unfavorable outcomes. Significant predictors of death were age > 59 years, the male gender, the presence of cardiovascular disease, a Glasgow Coma Scale score ≤ 5, and the SBS EEG pattern, with a predictive performance of 0.737 for death. rEEG can help identify patients at higher risk of seizures. We recommend repeated rEEG in patients with ESz or RPP EEG patterns to enable a more effective monitoring of seizure activities.

EEG Characteristics Before and After Dexmedetomidine Treatment in Severe Patients: A Prospective Study

Background. Bedside electroencephalography (EEG) can monitor the changes in brain function in critical patients. Light sedation is recommended in intensive care unit (ICU) patients, but sedation might confuse the EEG readings. There are few studies on the changes of EEG in severe patients with dexmedetomidine. This study aimed to explore the EEG characteristics before and after dexmedetomidine in severe patients in the ICU. Methods. This prospective study enrolled severe patients with sepsis who needed light sedation, we sedated the patients with dexmedetomidine. EEG was recorded for at least 60 min using a quantitative EEG (qEEG) bedside monitor. Amplitude-EEG (aEEG), relative spectral energy, alpha variation, and spectral entropy were recorded and compared before/after dexmedetomidine. Results. Sixty-three participants were enrolled. The relative spectral energy and alpha variation were not different before and after the use of dexmedetomidine (P > .05). The amplitude of the upper and lower boundaries in aEEG and spectral entropy were significantly lower after light sedation with dexmedetomidine compared with before (P < .05). When grouped according to the Glasgow Coma Scale (GCS), the amplitude of qEEG in participants with moderate GCS decreased significantly(P < .05), but not in mild or severe GCS. Conclusion. Relative spectral energy and alpha variation derived from qEEG could be used to evaluate the state of brain function even under light sedation with dexmedetomidine in severe patients during their ICU stay.

Continuous Electroencephalogram Use and Hospital Outcomes in Critically Ill Children

PURPOSE

To examine the association between CEEG use and discharge status, length of hospitalization, and health care cost in a critically ill pediatric population.

METHODS

Four thousand three hundred forty-eight critically ill children were identified from a US nationwide administrative health claims database; 212 (4.9%) of whom underwent CEEG during admissions (January 1, 2015-june 30, 2020). Discharge status, length of hospitalization, and health care cost were compared between patients with and without CEEG use. Multiple logistic regression analyzed the association between CEEG use and these outcomes, controlling for age and underlying neurologic diagnosis. Prespecified subgroups analysis was performed for children with seizures/status epilepticus, with altered mental status and with cardiac arrest.

RESULTS

Compared with critically ill children without CEEG, those who underwent CEEG were likely to have shorter hospital stays than the median (OR = 0.66; 95% CI = 0.49-0.88; P = 0.004), and also total hospitalization costs were less likely to exceed the median (OR = 0.59; 95% CI = 0.45-0.79; P < 0.001). There was no difference in odds of favorable discharge status between those with and without CEEG (OR = 0.69; 95% CI = 0.41-1.08; P = 0.125). In the subgroup of children with seizures/status epilepticus, those with CEEG were less likely to have unfavorable discharge status, compared with those without CEEG (OR = 0.51; 95% CI = 0.27-0.89; P = 0.026).

CONCLUSIONS

Among critically ill children, CEEG was associated with shorter stay and lower costs of hospitalization but was not associated with change of favorable discharge status except the subgroup with seizures/status epilepticus.

Intraoperative monitoring of the central and peripheral nervous systems: a narrative review

The central and peripheral nervous systems are the primary target organs during anaesthesia. At the time of the inception of the British Journal of Anaesthesia, monitoring of the central nervous system comprised clinical observation, which provided only limited information. During the 100 yr since then, and particularly in the past few decades, significant progress has been made, providing anaesthetists with tools to obtain real-time assessments of cerebral neurophysiology during surgical procedures. In this narrative review article, we discuss the rationale and uses of electroencephalography, evoked potentials, near-infrared spectroscopy, and transcranial Doppler ultrasonography for intraoperative monitoring of the central and peripheral nervous systems.

Characteristics and Attendance of Patients Eligible for the PASS Clinic: A Transition of Care Model After Acute Symptomatic Seizures

Background and Objectives

Most acute symptomatic seizure (ASyS) patients stay on antiseizure medications (ASM) long-term, despite low epilepsy development risk. The Post-Acute Symptomatic Seizure (PASS) clinic is a transition of care model for ASyS patients who individualize ASM management with the goal of a safe deprescription. We evaluated patients discharged on ASMs after a witnessed or suspected ASyS to analyze their PASS clinic visit attendance and its predictors.

Methods

A single-center, retrospective cohort study of adults without epilepsy who were discharged from January 1, 2019, to September 30, 2019, on first-time ASMs due to witnessed or suspected ASyS (PASS clinic-eligible). We fit a cause-specific Cox proportional hazards model to analyze factors associated with PASS clinic attendance, which depends on survival in this patient population that has a high early postdischarge mortality (a competing risk). We checked for multicollinearity and the assumption of proportional hazards.

Results

Among 307 PASS clinic-eligible patients, 95 (30.9%) attended the clinic and 136 (44.3%) died during a median follow-up of 14 months (interquartile range = 2-34). ASyS occurred in 60.2% (convulsive 47%; electrographic 26.7%) of patients. ASMs were continued in the absence of ASyS or epileptiform abnormalities (EAs) in 27% of patients. Multivariable analysis revealed that the presence of EAs (HR = 1.69, 95% CI 1.10-2.59), PASS clinic appointments provided before discharge (HR = 3.39, 95% CI 2.15-5.33), and less frequently noted ASyS etiologies such as autoimmune encephalitis (HR = 2.03, 95% CI 1.07-3.86) were associated with an increased clinic attendance rate. Medicare/Medicaid insurance (HR = 0.43, 95% CI 0.24-0.78, p = 0.005) and the presence of progressive brain injury (i.e., tumors; HR = 0.55, 95% CI 0.32-0.95, p = 0.032) were associated with reduced rate of PASS clinic attendance.

Discussion

Our real-world data highlight the need for appropriate postdischarge follow-up of ASyS patients, which can be fulfilled by the PASS clinic model. Modest PASS clinic attendance can be significantly improved by adhering to a structured discharge planning process whereby appointments are provided before discharge. Future research comparing patient outcomes, specifically safe ASM discontinuation in a PASS clinic model to routine clinical care, is needed.

Role of Intraoperative Neuromonitoring to Predict Postoperative Delirium in Cardiovascular Surgery

OBJECTIVE

Postoperative delirium (POD) can occur in up to 50% of older patients undergoing cardiovascular surgery, resulting in hospitalization and significant morbidity and mortality. This study aimed to determine whether intraoperative neurophysiologic monitoring (IONM) modalities can be used to predict delirium in patients undergoing cardiovascular surgery.

DESIGN

Adult patients undergoing cardiovascular surgery with IONM between 2019 and 2021 were reviewed retrospectively. Delirium was assessed multiple times using the Intensive Care Delirium Screening Checklist (ICDSC). Patients with an ICDSC score ≥4 were considered to have POD. Significant IONM changes were evaluated based on a visual review of electroencephalography (EEG) and somatosensory evoked potentials data and documentation of significant changes during surgery.

SETTING

University of Pittsburgh Medical Center hospitals.

PARTICIPANTS

Patients 18 years old and older undergoing cardiovascular surgery with IONM monitoring.

MEASUREMENTS AND MAIN RESULTS

Of the 578 patients undergoing cardiovascular surgery with IONM, 126 had POD (21.8%). Significant IONM changes were noted in 134 patients, of whom 49 patients had delirium (36.6%). In contrast, 444 patients had no IONM changes during surgery, of whom 77 (17.3%) patients had POD. Upon multivariate analysis, IONM changes were associated with POD (odds ratio 2.12; 95% CI 1.31-3.44; p < 0.001). Additionally, baseline EEG abnormalities were associated with POD (p = 0.002).

CONCLUSION

Significant IONM changes are associated with an increased risk of POD in patients undergoing cardiovascular surgery. These findings offer a basis for future research and analysis of EEG and somatosensory evoked potential monitoring to predict, detect, and prevent POD.

Reviving Hope: A Comprehensive Review of Post-resuscitation Care in Pediatric ICUs After Cardiac Arrest

This comprehensive review thoroughly examines post-resuscitation care in pediatric ICUs (PICUs) following cardiac arrest. The analysis encompasses adherence to resuscitation guidelines, advances in therapeutic interventions, and the nuanced management of neurological, cardiovascular, and respiratory considerations during the immediate post-resuscitation phase. Delving into the complexities of long-term outcomes, cognitive and developmental considerations, and rehabilitation strategies, the review emphasizes the importance of family-centered care for pediatric survivors. A call to action is presented, urging continuous education, research initiatives, and quality improvement efforts alongside strengthened multidisciplinary collaboration and advocacy for public awareness. Through implementing these principles, healthcare providers and systems can collectively contribute to ongoing advancements in pediatric post-resuscitation care, ultimately improving outcomes and fostering a culture of excellence in pediatric critical care.

Electroencephalography as a Biomarker of Prognosis in Acute Brain Injury

Electroencephalography (EEG) is a noninvasive tool that allows the monitoring of cerebral brain function in critically ill patients, aiding with diagnosis, management, and prognostication. Specific EEG features have shown utility in the prediction of outcomes in critically ill patients with status epilepticus, acute brain injury (ischemic stroke, intracranial hemorrhage, subarachnoid hemorrhage, and traumatic brain injury), anoxic brain injury, and toxic-metabolic encephalopathy. Studies have also found an association between particular EEG patterns and long-term functional and cognitive outcomes as well as prediction of recovery of consciousness following acute brain injury. This review summarizes these findings and demonstrates the value of utilizing EEG findings in the determination of prognosis.

Maintenance of pig brain function under extracorporeal pulsatile circulatory control (EPCC)

Selective vascular access to the brain is desirable in metabolic tracer, pharmacological and other studies aimed to characterize neural properties in isolation from somatic influences from chest, abdomen or limbs. However, current methods for artificial control of cerebral circulation can abolish pulsatility-dependent vascular signaling or neural network phenomena such as the electrocorticogram even while preserving individual neuronal activity. Thus, we set out to mechanically render cerebral hemodynamics fully regulable to replicate or modify native pig brain perfusion. To this end, blood flow to the head was surgically separated from the systemic circulation and full extracorporeal pulsatile circulatory control (EPCC) was delivered via a modified aorta or brachiocephalic artery. This control relied on a computerized algorithm that maintained, for several hours, blood pressure, flow and pulsatility at near-native values individually measured before EPCC. Continuous electrocorticography and brain depth electrode recordings were used to evaluate brain activity relative to the standard offered by awake human electrocorticography. Under EPCC, this activity remained unaltered or minimally perturbed compared to the native circulation state, as did cerebral oxygenation, pressure, temperature and microscopic structure. Thus, our approach enables the study of neural activity and its circulatory manipulation in independence of most of the rest of the organism.

Duration of constant rate infusion with diazepam or propofol for canine cluster seizures and status epilepticus

Introduction

Constant rate infusion (CRI) of benzodiazepines or propofol (PPF) is a therapeutic option for cluster seizures (CS) and status epilepticus (SE) in canine patients non-responding to first-line benzodiazepines or non-anesthetics. However, specific indications for optimal duration of CRI are lacking. The aim of this study was to determine the effect of duration of anesthetic CRI on outcome and length of hospital stay in dogs with refractory seizure activity of different etiology.

Study design

Open-label non-randomized clinical trial.

Materials and methods

Seventy-three client-owned dogs were enrolled. Two groups [experimental (EXP) vs. control (CTRL)] were compared. The EXP group received diazepam (DZP) or PPF CRI for 12 h (±1 h) and the CTRL group received DZP or PPF CRI for 24 h (±1 h) in addition to a standardized emergency treatment protocol identical for both study groups. The historical control group was made up of a population of dogs already reported in a previously published paper by the same authors. Favorable outcome was defined as seizure cessation after CRI, no seizure recurrence, and clinical recovery. Poor outcome was defined as seizure recurrence, death in hospital or no return to acceptable clinical baseline. Univariate statistical analysis was performed.

Results

The study sample was 73 dogs: 45 (62%) received DZP CRI and 28 (38%) received PPF CRI. The EXP group was 39 dogs (25 DZP CRI and 14 PPF CRI) and the CTRL group 34 dogs (20 DZP CRI and 14 PPF CRI). We found no statistically significant difference in outcomes between the groups. The median length of stay was 56 h (IQR, 40-78) for the ALL EXP group and 58.5 h (IQR, 48-74.5) for the ALL CTRL group (p = 0.8).

Conclusion

Even though a shorter DZP or PPF CRI duration was not associated with a worse outcome, the study failed to identify a clear superiority of shorter CRI duration on outcome or length of hospital stay in dogs with refractory seizure activity of different etiology.

Nonconvulsive Status Epilepticus Associated with Cerebral Hyperperfusion Syndrome after Carotid Endarterectomy: A Case Report

We report a case of a 73-year-old man who developed nonconvulsive status epilepticus as a complication of cerebral hyperperfusion syndrome after carotid endarterectomy for carotid artery stenosis. On postoperative day 1, the patient experienced headaches and vomiting. Resting N-isopropyl-p-[¹²³I] iodoamphetamine single-photon emission computed tomography showed increased cerebral blood flow to the entire right hemisphere, and the patient was diagnosed with cerebral hyperperfusion syndrome. He was treated with antihypertensive and antiseizure medications, sedated using propofol, intubated, and placed under mechanical ventilation. On postoperative day 3, computed tomography perfusion imaging showed a reduction in hyperperfusion, and propofol sedation was terminated on postoperative day 4. However, the patient exhibited prolonged impaired awareness and roving eye movements, and long-term video electroencephalographic monitoring revealed electrographic seizures. The patient was diagnosed with nonconvulsive status epilepticus. Propofol sedation was resumed, and the antiseizure medication dose was increased. Subsequently, the state of hyperperfusion in the right hemisphere diminished, and electroencephalographic findings improved, allowing sedation to be terminated on postoperative day 7. The findings from this case suggest that when clinical subtle symptoms, such as impaired awareness and roving eye movements, are observed during treatment of cerebral hyperperfusion syndrome, video electroencephalography should be performed to detect electrographic seizures.

Epileptiform activity in the acute phase of stroke predicts the outcomes in patients without seizures

Background and purpose

The abnormalities in EEG of stroke-patients increase the risk of epilepsy but their significancy for poststroke outcome is unclear. This presented study was aimed at determining the prevalence and nature of changes in EEG recordings from the stroke hemisphere and from the contralateral hemisphere. Another objective was to determine the significance of abnormalities in EEG in the first days of stroke for the post-stroke functional status on the acute and chronic phase of disease.

Methods

In all qualified stroke-patients, EEG was performed during the first 3 days of hospitalization and at discharge. The correlation between EEG abnormalities both in the stroke hemisphere and in the collateral hemisphere with the neurological and functional state in various time points was performed.

Results

One hundred thirty-one patients were enrolled to this study. Fifty-eight patients (44.27%) had abnormal EEG. The sporadic discharges and generalized rhythmic delta activity were the most common abnormalities in the EEG. The neurological status on the first day and the absence of changes in the EEG in the hemisphere without stroke were the independent factors for good neurological state (0–2 mRS) at discharge. The age-based analysis model (OR 0.981 CI 95% 0.959–1.001, p = 0.047), neurological status on day 1 (OR 0.884 CI 95% 0.82–0.942, p &lt; 0.0001) and EEG recording above the healthy hemisphere (OR 0.607 CI 95% 0.37–0.917, p = 0.028) had the highest prognostic value in terms of achieving good status 90 days after stroke.

Conclusions

Abnormalities in EEG without clinical manifestation are present in 40% of patients with acute stroke. Changes in EEG in acute stroke are associated with a poor neurological status in the first days and poor functional status in the chronic period of stroke.

Multimodal monitoring: practical recommendations (dos and don'ts) in challenging situations and uncertainty

With the advancements in modern medicine, new methods are being developed to monitor patients in the intensive care unit. Different modalities evaluate different aspects of the patient's physiology and clinical status. The complexity of these modalities often restricts their use to the realm of clinical research, thereby limiting their use in the real world. Understanding their salient features and their limitations can aid physicians in interpreting the concomitant information provided by multiple modalities to make informed decisions that may affect clinical care and outcomes. Here, we present a review of the commonly used methods in the neurological intensive care unit with practical recommendations for their use.

Personalized model to predict seizures based on dynamic and static continuous EEG monitoring data

BACKGROUND/OBJECTIVE

Early recognition of patients who may be at risk of developing acute symptomatic seizures would be useful. We aimed to determine whether continuous electroencephalography (cEEG) data using machine learning techniques such as neural networks and decision trees could predict seizure occurrence in hospitalized patients.

METHODS

This was a single center retrospective cohort analysis of cEEG data in patients aged 18-90 years who were admitted and underwent cEEG monitoring between 2010 and 2019 limited to 72 h excluding those who were seizing at the onset of recording. A total of 41,491 patients were reviewed; of these, 3874 were used to develop the static model and 1687 to develop the dynamic model (half with seizure and half without seizure in each cohort). Of these, 80% were randomly selected as derivation cohorts for each model and 20% were randomly selected as validation cohorts. Dynamic and static machine learning models (long short term memory (LSTM) and Extreme Gradient Boosting algorithm (XGBoost)) based on day-to-day dynamic EEG changes and binary static EEG features over the prior 72 h or until seizure, which ever was earlier, were used.

RESULTS

The static model was able to predict seizure occurrence based on cEEG data with sensitivity and specificity of 0.81 and 0.59, respectively, with an AUC of 0.70. The dynamic model was able to predict seizure occurrence with sensitivity and specificity of 0.72 and 0.80, respectively, and AUC of 0.81.

CONCLUSIONS

Machine learning models could be applied to cEEG data to predict seizure occurrence based on available cEEG data. Dynamic day-to-day EEG data are more useful in predicting seizures than binary static EEG data. These models could potentially be used to determine the need for ongoing cEEG monitoring and to prioritize resources.

Translational Organic Neural Interface Devices at Single Neuron Resolution

Recording from the human brain at the spatiotemporal resolution of action potentials provides critical insight into mechanisms of higher cognitive functions and neuropsychiatric disease that is challenging to derive from animal models. Here, organic materials and conformable electronics are employed to create an integrated neural interface device compatible with minimally invasive neurosurgical procedures and geared toward chronic implantation on the surface of the human brain. Data generated with these devices enable identification and characterization of individual, spatially distribute human cortical neurons in the absence of any tissue penetration (n = 229 single units). Putative single-units are effectively clustered, and found to possess features characteristic of pyramidal cells and interneurons, as well as identifiable microcircuit interactions. Human neurons exhibit consistent phase modulation by oscillatory activity and a variety of population coupling responses. The parameters are furthermore established to optimize the yield and quality of single-unit activity from the cortical surface, enhancing the ability to investigate human neural network mechanisms without breaching the tissue interface and increasing the information that can be safely derived from neurophysiological monitoring.

Pediatric Neurocritical Care

Brain injury in children is a major public health problem, causing substantial morbidity and mortality. Cause of pediatric brain injury varies widely and can be from a primary neurologic cause or as a sequela of multisystem illness. This review discusses the emerging field of pediatric neurocritical care (PNCC), including current techniques of imaging, treatment, and monitoring. Future directions of PNCC include further expansion of evidence-based practice guidelines and establishment of multidisciplinary PNCC services within institutions.

Electrographic Seizure Detection by Neuroscience Intensive Care Unit Nurses via Bedside Real-Time Quantitative EEG

Objective

Our primary objective was to determine the performance of real-time neuroscience intensive care unit (neuro-ICU) nurse interpretation of quantitative EEG (qEEG) at the bedside for seizure detection. Secondary objectives included determining nurse time to seizure detection and assessing factors that influenced nurse accuracy.

Methods

Nurses caring for neuro-ICU patients undergoing continuous EEG (cEEG) were trained using a 1-hour qEEG panel (rhythmicity spectrogram and amplitude-integrated EEG) bedside display. Nurses' hourly interpretations were compared with post hoc cEEG review by 2 neurophysiologists as the gold standard. Diagnostic performance, time to seizure detection compared with standard of care (SOC), and effects of other factors on nurse accuracy were calculated.

Results

A total of 109 patients and 65 nurses were studied. Eight patients had seizures during the study period (7%). Nurse sensitivity and specificity for the detection of seizures were 74% and 92%, respectively. Mean nurse time to seizure detection was significantly shorter than SOC by 132 minutes (Cox proportional hazard ratio 6.96). Inaccurate nurse interpretation was associated with increased hours monitored and presence of brief rhythmic discharges.

Conclusions

This prospective study of real-time nurse interpretation of qEEG for seizure detection in neuro-ICU patients showed clinically adequate sensitivity and specificity. Time to seizure detection was less than that of SOC.

Trial Registration Information

Clinical trial registration number NCT02082873.

Classification of Evidence

This study provides Class I evidence that neuro-ICU nurse interpretation of qEEG detects seizures in adults with a sensitivity of 74% and a specificity of 92% compared with traditional cEEG review.

Continuous Quantitative Electroencephalogram (EEG) Monitoring for Early Detection of Brain Herniation in Large Hemispheric Infarction (LHI): A Case Report

BACKGROUND

Computer-assisted electroencephalography (EEG) systems may improve the likelihood of detecting abnormal EEGs in adult patients with severe disease.

CASE PRESENTATION

We implemented long-range EEG monitoring in a patient with large hemispheric infarction (LHI) and explored its real-time changes in reflecting the patient's brain function. The bands of Alpha, Beta, Delta, Theta, DAR (Delta/Alpha), DTABR (Delta+Theta/Alpha+Beta), and brain symmetry index (BSI) were calculated as a ratio of total power. The test results showed that this patient presents a progressive worsening trend and developed brain herniation. The sigh at the electrophysiological level of brain herniation could be seen 6 h in advance based on the quantitative EEG (QEEG) parameters test. We calculated QEEG at both C3 and C4, electrode locations simultaneously, and the results showed that the trend of QEEG at both electrodes was consistent with the global, affected, and unaffected side.

CONCLUSIONS

QEEG parameters can reflect the trend of LHI patients in real-time and may predict the occurrence of LHI brain herniation. For LHI patients, monitoring with fewer EEG electrodes can be tried to predict the changes in conditions.

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.

Indications for Inpatient Magnetoencephalography in Children - An Institution's Experience

Magnetoencephalography (MEG) is recognized as a valuable non-invasive clinical method for localization of the epileptogenic zone and critical functional areas, as part of a pre-surgical evaluation for patients with pharmaco-resistant epilepsy. MEG is also useful in localizing functional areas as part of pre-surgical planning for tumor resection. MEG is usually performed in an outpatient setting, as one part of an evaluation that can include a variety of other testing modalities including 3-Tesla MRI and inpatient video-electroencephalography monitoring. In some clinical circumstances, however, completion of the MEG as an inpatient can provide crucial ictal or interictal localization data during an ongoing inpatient evaluation, in order to expedite medical or surgical planning. Despite well-established clinical indications for performing MEG in general, there are no current reports that discuss indications or considerations for completion of MEG on an inpatient basis. We conducted a retrospective institutional review of all pediatric MEGs performed between January 2012 and December 2020, and identified 34 cases where MEG was completed as an inpatient. We then reviewed all relevant medical records to determine clinical history, all associated diagnostic procedures, and subsequent treatment plans including epilepsy surgery and post-surgical outcomes. In doing so, we were able to identify five indications for completing the MEG on an inpatient basis: (1) super-refractory status epilepticus (SRSE), (2) intractable epilepsy with frequent electroclinical seizures, and/or frequent or repeated episodes of status epilepticus, (3) intractable epilepsy with infrequent epileptiform discharges on EEG or outpatient MEG, or other special circumstances necessitating inpatient monitoring for successful and safe MEG data acquisition, (4) MEG mapping of eloquent cortex or interictal spike localization in the setting of tumor resection or other urgent neurosurgical intervention, and (5) international or long-distance patients, where outpatient MEG is not possible or practical. MEG contributed to surgical decision-making in the majority of our cases (32 of 34). Our clinical experience suggests that MEG should be considered on an inpatient basis in certain clinical circumstances, where MEG data can provide essential information regarding the localization of epileptogenic activity or eloquent cortex, and be used to develop a treatment plan for surgical management of children with complicated or intractable epilepsy.

EEG in the Pediatric Intensive Care Unit: An Irish Experience

INTRODUCTION

Evidence for continuous EEG monitoring in the pediatric intensive care unit (PICU) is increasing. However, 24/7 access to EEG is not routinely available in most centers, and clinical management is often informed by more limited EEG resources. The experience of EEG was reviewed in a tertiary PICU where 24/7 EEG cover is unavailable.

METHODS

Retrospective EEG and clinical review of 108 PICU patients. Correlations were carried out between EEG and clinical variables including mortality. The role of EEG in clinical decision making was documented.

RESULTS

One hundred ninety-six EEGs were carried out in 108 PICU patients over 2.5 years (434 hours of recording). After exclusion of 1 outlying patient with epileptic encephalopathy, 136 EEGs (median duration, 65 minutes; range, 20 minutes to 4 hours 40 minutes) were included. Sixty-two patients (57%) were less than 12 months old. Seizures were detected in 18 of 107 patients (17%); 74% of seizures were subclinical; 72% occurred within the first 30 minutes of recording. Adverse EEG findings were associated with high mortality. Antiepileptic drug use was high in the studied population irrespective of EEG seizure detection. Prevalence of epileptiform discharges and EEG seizures diminished with increasing levels of sedation.

CONCLUSIONS

EEG provides important diagnostic information in a large proportion of PICU patients. In the absence of 24/7 EEG availability, empirical antiepileptic drug utilization is high.

Efficiency of using a neurofeedback device in determining ischaemic early electroencephalography indicators in rabbits with acute brain ischaemia

OBJECTIVES

Continuous electroencephalography (EEG) monitoring is a useful method in surgical procedures in which brain circulation is at risk. Providing this function using neurofeedback devices reduced to small dimensions may provide ease of use in the early diagnosis of brain ischaemia. The goal of this study was to demonstrate the efficiency of using a neurofeedback device in determining the early EEG indicators of ischaemia in a rabbit model of acute brain ischaemia.

METHODS

Three randomized groups-carotid ischaemia (CI), global ischaemia (GI) and a sham group-each comprising 8 rabbits, were created. In the CI group, the bilateral main carotid artery was clamped; in the GI group, the bilateral subclavian and main carotid arteries were clamped and brain ischaemia was created for 15 min. Brain reperfusion was then achieved for 30 min. In the sham group, the same surgical preparation was performed but no ischaemia occurred. The brain EEG wave activities of all subjects were recorded during the experiment. At the end of the procedure, all brain tissue was removed and apoptotic indexes were determined by histopathological examination. The statistical significance of the histopathological results and the EEG wave activities among the groups was examined.

RESULTS

There was a significant difference between the sham, CI and GI average amplitude ratios, delta (1.02, 0.69, 0.16; P < 0.001) and total wave (0.99, 0.78, 0.49; P < 0.001), respectively. There was no significant difference between the sham and CI groups in delta (sham, CI, 1.01, 0.87; P = 0.1), total wave (sham, CI, 1.22, 0.98; P = 0.2) and amplitude standard deviation rates. However, there was a significant difference in the GI group (P < 0.001). There was a significant difference between all groups in apoptotic index (sham, 17.88; CI, 40.75; GI, 55.88; P < 0.001).

CONCLUSIONS

Significant EEG wave changes resulting from experimental brain ischaemia were analysed with the use of a neurofeedback device. The results indicated that the change in the delta and the total wave standard deviations may be an additional indicator in the formation of permanent brain damage.

Seizures and Sepsis: A Narrative Review

Patients with sepsis-associated encephalopathy (SAE) can develop convulsive or nonconvulsive seizures. The cytokine storm and the overwhelming systemic inflammation trigger the electric circuits that promote seizures. Several neurologic symptoms, associated with this disease, range from mild consciousness impairment to coma. Focal or generalized convulsive seizures are frequent in sepsis, although nonconvulsive seizures (NCS) are often misdiagnosed and prevalent in SAE. In order to map the trigger zone in all patients that present focal or generalized seizures and also to detect NCS, EEG is indicated but continuous EEG (cEEG) is not very widespread; timing, duration, and efficacy of this tool are still unknown. The long-term risk of seizures in survivors is increased. The typical stepwise approach of seizures management begins with benzodiazepines and follows with anticonvulsants up to anesthetic drugs such as propofol or thiopental, which are able to induce burst suppression and interrupt the pathological electrical circuits. This narrative review discusses pathophysiology, clinical presentation, diagnosis and treatment of seizures in sepsis.

Anesthetic Management of Patients Undergoing Open Suboccipital Surgery

The posterior cranial fossa with its complex anatomy houses key pathways regulating consciousness, autonomic functions, motor and sensory pathways, and cerebellar centers regulating balance and gait. The most common posterior fossa pathologies for which neurosurgical intervention may be necessary include cerebellopontine angle tumors, aneurysms, and metastatic lesions. The posterior cranial fossa can be accessed from variations of the supine, lateral, park-bench, prone, and sitting positions. Notable complications from positioning include venous air embolism, paradoxic air embolism, tension pneumocephalus, nerve injuries, quadriplegia, and macroglossia. An interdisciplinary approach with careful planning, discussion, and clinical management contributes to improved outcomes and reduced complications.

Post-cardiac arrest care and targeted temperature management: A consensus of scientific statement from the Taiwan Society of Emergency & Critical Care Medicine, Taiwan Society of Critical Care Medicine and Taiwan Society of Emergency Medicine

BACKGROUND

Post-cardiac arrest care is critically important in bringing cardiac arrest patients to functional recovery after the detrimental event. More high quality studies are published and evidence is accumulated for the post-cardiac arrest care in the recent years. It is still a challenge for the clinicians to integrate these scientific data into the real clinical practice for such a complicated intensive care involving many different disciplines.

METHODS

With the cooperation of the experienced experts from all disciplines relevant to post-cardiac arrest care, the consensus of the scientific statement was generated and supported by three major scientific groups for emergency and critical care in post-cardiac arrest care.

RESULTS

High quality post-cardiac arrest care, including targeted temperature management, early evaluation of possible acute coronary event and intensive care for hemodynamic and respiratory care are inevitably needed to get full recovery for cardiac arrest. Management of these critical issues were reviewed and proposed in the consensus CONCLUSION: The goal of the statement is to provide help for the clinical physician to achieve better quality and evidence-based care in post-cardiac arrest period.

Continuous EEG in ICU: Not a Luxury After All

Continuous vs Routine Electroencephalogram in Critically Ill Adults With Altered Consciousness and No Recent Seizure: A Multicenter Randomized Clinical Trial

Rossetti AO, Schindler K, Sutter R, Rüegg S, Zubler F, Novy J, Oddo M, Warpelin-Decrausaz L, Alvarez V. JAMA Neurol. 2020;77(10):1-8. doi:10.1001/jamaneurol.2020.2264

Importance:

In critically ill patients with altered consciousness, continuous electroencephalogram (cEEG) improves seizure detection but is resource-consuming compared with routine EEG (rEEG). It is also uncertain whether cEEG has an effect on outcome.

Objective:

To assess whether cEEG is associated with reduced mortality compared with rEEG.

Design, Setting, and Participants:

The pragmatic multicenter Continuous EEG Randomized Trial in Adults was conducted between 2017 and 2018, with follow-up of 6 months. Outcomes were assessed by interviewers blinded to interventions. The study took place at 4 tertiary hospitals in Switzerland (intensive and intermediate care units). Depending on investigators’ availability, we pragmatically recruited critically ill adults having Glasgow Coma Scale scores of 11 or less or Full Outline of Responsiveness score of 12 or less, without recent seizures or status epilepticus. They had cerebral (eg, brain trauma, cardiac arrest, hemorrhage, or stroke) or noncerebral conditions (eg, toxic-metabolic or unknown etiology), and EEG was requested as part of standard care. An independent physician provided emergency informed consent.

Interventions:

Participants were randomized 1:1 to cEEG for 30 to 48 hours versus 2 rEEGs (20 minutes each), interpreted according to standardized American Clinical Neurophysiology Society guidelines.

Main Outcomes and Measures:

Mortality at 6 months represented the primary outcome. Secondary outcomes included interictal and ictal features detection and change in therapy.

Results:

We analyzed 364 (33% women; mean [SD] age, 63 [15] years) patients. At 6 months, mortality was 89 of 182 in those with cEEG and 88 of 182 in those with rEEG (adjusted relative risk [RR]: 1.02; 95% CI: 0.83-1.26; P = .85). Exploratory comparisons within subgroups stratifying patients according to age, premorbid disability, comorbidities on admission, deeper consciousness reduction, and underlying diagnoses revealed no significant effect modification. Continuous EEG was associated with increased detection of interictal features and seizures (adjusted RR: 1.26; 95% CI: 1.08-1.15; P = .004 and 3.37; 95% CI: 1.63-7.00; P = .001, respectively) and more frequent adaptations in anti-seizure therapy (RR: 1.84; 95% CI: 1.12-3.00; P = .01).

Conclusions and Relevance:

This pragmatic trial shows that in critically ill adults with impaired consciousness and no recent seizure, cEEG leads to increased seizure detection and modification of anti-seizure treatment but is not related to improved outcome compared with repeated rEEG. Pending larger studies, rEEG may represent a valid alternative to cEEG in centers with limited resources.

Acute Provoked Seizures-Work-Up and Management in Adults

Acute provoked seizures, also known as acute symptomatic seizures, occur secondary to a neurological or systemic precipitant, commonly presenting as a first-time seizure. In this article, we will discuss etiology, emergent protocols, medical work-up, initial treatment, and management of these seizures. The definitions, classifications, and management of convulsive status epilepticus and nonconvulsive status epilepticus in an acute setting will also be reviewed.

Does electroencephalographic burst suppression still play a role in the perioperative setting?

With the widespread use of electroencephalogram [EEG] monitoring during surgery or in the Intensive Care Unit [ICU], clinicians can sometimes face the pattern of burst suppression [BS]. The BS pattern corresponds to the continuous quasi-periodic alternation between high-voltage slow waves [the bursts] and periods of low voltage or even isoelectricity of the EEG signal [the suppression] and is extremely rare outside ICU and the operative room. BS can be secondary to increased anesthetic depth or a marker of cerebral damage, as a therapeutic endpoint [i.e., refractory status epilepticus or refractory intracranial hypertension]. In this review, we report the neurophysiological features of BS to better define its role during intraoperative and critical care settings.

Rapid annotation of seizures and interictal-ictal-injury continuum EEG patterns

BACKGROUND

Manual annotation of seizures and interictal-ictal-injury continuum (IIIC) patterns in continuous EEG (cEEG) recorded from critically ill patients is a time-intensive process for clinicians and researchers. In this study, we evaluated the accuracy and efficiency of an automated clustering method to accelerate expert annotation of cEEG.

NEW METHOD

We learned a local dictionary from 97 ICU patients by applying k-medoids clustering to 592 features in the time and frequency domains. We utilized changepoint detection (CPD) to segment the cEEG recordings. We then computed a bag-of-words (BoW) representation for each segment. We further clustered the segments by affinity propagation. EEG experts scored the resulting clusters for each patient by labeling only the cluster medoids. We trained a random forest classifier to assess validity of the clusters.

RESULTS

Mean pairwise agreement of 62.6% using this automated method was not significantly different from interrater agreements using manual labeling (63.8%), demonstrating the validity of the method. We also found that it takes experts using our method 5.31 ± 4.44 min to label the 30.19 ± 3.84 h of cEEG data, more than 45 times faster than unaided manual review, demonstrating efficiency.

COMPARISON WITH EXISTING METHODS

Previous studies of EEG data labeling have generally yielded similar human expert interrater agreements, and lower agreements with automated methods.

CONCLUSIONS

Our results suggest that long EEG recordings can be rapidly annotated by experts many times faster than unaided manual review through the use of an advanced clustering method.

Detecting Seizures and Epileptiform Abnormalities in Acute Brain Injury

PURPOSE OF REVIEW

Acute brain injury (ABI) is a broad category of pathologies, including traumatic brain injury, and is commonly complicated by seizures. Electroencephalogram (EEG) studies are used to detect seizures or other epileptiform patterns. This review seeks to clarify EEG findings relevant to ABI, explore practical barriers limiting EEG implementation, discuss strategies to leverage EEG monitoring in various clinical settings, and suggest an approach to utilize EEG for triage.

RECENT FINDINGS

Current literature suggests there is an increased morbidity and mortality risk associated with seizures or patterns on the ictal-interictal continuum (IIC) due to ABI. Further, increased use of EEG is associated with better clinical outcomes. However, there are many logistical barriers to successful EEG implementation that prohibit its ubiquitous use. Solutions to these limitations include the use of rapid EEG systems, non-expert EEG analysis, machine learning algorithms, and the incorporation of EEG data into prognostic models.

A Trial of Real-Time Electrographic Seizure Detection by Neuro-ICU Nurses Using a Panel of Quantitative EEG Trends

BACKGROUND

Non-convulsive seizures (NCS) are a common occurrence in the neurologic intensive care unit (Neuro-ICU) and are associated with worse outcomes. Continuous electroencephalogram (cEEG) monitoring is necessary for the detection of NCS; however, delays in interpretation are a barrier to early treatment. Quantitative EEG (qEEG) calculates a time-compressed simplified visual display from raw EEG data. This study aims to evaluate the performance of Neuro-ICU nurses utilizing bedside, real-time qEEG interpretation for detecting recurrent NCS.

METHODS

This is a prospective, single-institution study of patients admitted to the Duke Neuro-ICU between 2016 and 2018 who had NCS identified on traditional cEEG review. The accuracy of recurrent seizure detection on hourly qEEG review by bedside Neuro-ICU nurses was compared to the gold standard of cEEG interpretation by two board-certified neurophysiologists. The nurses first received brief qEEG training, individualized for their specific patient. The bedside qEEG display consisted of rhythmicity spectrogram (left and right hemispheres) and amplitude-integrated EEG (left and right hemispheres) in 1-h epochs.

RESULTS

Twenty patients were included and 174 1-h qEEG blocks were analyzed. Forty-seven blocks contained seizures (27%). The sensitivity was 85.1% (95% CI 71.1-93.1%), and the specificity was 89.8% (82.8-94.2%) for the detection of seizures for each 1-h block when compared to interpretation of conventional cEEG by two neurophysiologists. The false positive rate was 0.1/h. Hemispheric seizures (> 4 unilateral EEG electrodes) were more likely to be correctly identified by nurses on qEEG than focal seizures (≤ 4 unilateral electrodes) (p = 0.03).

CONCLUSIONS

After tailored training sessions, Neuro-ICU nurses demonstrated a good sensitivity for the interpretation of bedside real-time qEEG for the detection of recurrent NCS with a low false positive rate. qEEG is a promising tool that may be used by non-neurophysiologists and may lead to earlier detection of NCS.

Recommandations Formalisées d’Experts SRLF/SFMU : Prise en charge des états de mal épileptiques en préhospitalier, en structure d’urgence et en réanimation dans les 48 premières heures (A l’exclusion du nouveau-né et du nourrisson)

La Société de réanimation de langue française et la Société française de médecine d’urgence ont décidé d’élaborer de nouvelles recommandations sur la prise en charge de l’état mal épileptique (EME) avec l’ambition de répondre le plus possible aux nombreuses questions pratiques que soulèvent les EME : diagnostic, enquête étiologique, traitement non spécifique et spécifique. Vingt-cinq experts ont analysé la littérature scientifique et formulé des recommandations selon la méthodologie GRADE. Les experts se sont accordés sur 96 recommandations. Les recommandations avec le niveau de preuve le plus fort ne concernent que l’EME tonico-clonique généralisé (EMTCG) : l’usage des benzodiazépines en première ligne (clonazépam en intraveineux direct ou midazolam en intramusculaire) est recommandé, répété 5 min après la première injection (à l’exception du midazolam) en cas de persistance clinique. En cas de persistance 5 min après cette seconde injection, il est proposé d’administrer la seconde ligne thérapeutique : valproate de sodium, (fos-)phénytoïne, phénobarbital ou lévétiracétam. La persistance avérée de convulsions 30 min après le début de l’administration du traitement de deuxième ligne signe l’EMETCG réfractaire. Il est alors proposé de recourir à un coma thérapeutique au moyen d’un agent anesthésique intraveineux de type midazolam ou propofol. Des recommandations spécifiques à l’enfant et aux autres EME sont aussi énoncées.

EEG signal varies with different outcomes in comatose patients: A quantitative method of electroencephalography reactivity

BACKGROUND

Electroencephalographic reactivity (EEG-R) is a major predictor of outcome in comatose patients; however, the inter-rater reliability is limited due to the lack of homogeneous stimuli and quantitative interpretation.

NEW METHODS

EEG-R testing was employed in comatose patients by quantifiable electrical stimulation. Reactivity at different frequency bands was computed as the difference between pre- and post-stimulations in power spectra and connectivity function (including magnitude squared coherence and transfer entropy). The clinical outcomes were dichotomized as good and poor according to the recovery of consciousness. Signal discrimination of EEG-R was compared between the two groups.

RESULTS

A total of 18 patients (43%) regained consciousness at a 3-month follow-up. In the patients who regained consciousness, the EEG power increased significantly (P < 0.05) at the Alpha and Beta frequency bands after stimulation as compared to those with no behavioral awakening. Also, connectivity enhancement (including linear and nonlinear analysis) in the Beta and Gamma bands and connectivity decrease (nonlinear transfer entropy analysis) in the Delta band after stimulus were observed in the good outcome group.

COMPARISON WITH EXISTING METHOD(S)

In this study, the combined use of quantifiable stimulation and quantitative analysis shed new light on differentiating brain responses in comatose patients with good and poor outcomes as well as exploring the nature of EEG changes concerning the recovery of consciousness.

CONCLUSIONS

The combination of quantifiable electrical stimulation and quantitative analysis with spectral power and connectivity for the EEG-R may be a promising method to predict the outcome of comatose patients.

Evaluation of a new wireless technique for continuous electroencephalography monitoring in neurological intensive care patients

A novel wireless eight-channel electroencephalography (EEG) headset specially developed for ICUs was tested in regard of comparability with standard 10/20 EEG systems. The continuous EEG (cEEG) derivations via CerebAir EEG headset (Nihon Kohden Europe, Rosbach, Germany) and internationally standardized 10/20 reference EEGs as the diagnostic standard were performed in a mixed collective on a neurointensive care unit (neuro-ICU). The derivations were verified for comparability in detection of EEG background activity, epileptiform discharges, and seizure patterns. Fifty-two patients with vigilance reduction following serious neurological or metabolic diseases were included, and both methods were applied and further analyzed in 47. EEG background activity matched in 24 of 45 patients (53%; p = 0.126), epileptiform discharges matched in 32 (68%) patients (p = 0.162), and seizure activity matched in 98%. Overall, in 89% of the patients, cEEG detected the same or additional ICU-relevant EEG patterns. The tested wireless cEEG headset is a useful monitoring tool in patients with consciousness disorders. The present study indicates that long-term measurements with the wireless eight-channel cEEG lead to a higher seizure and epileptiform discharge detection compared to intermittent 10/20 EEG derivations in the ICU setting.

Burden of Epileptiform Activity Predicts Discharge Neurologic Outcomes in Severe Acute Ischemic Stroke

BACKGROUND/OBJECTIVES

Clinical seizures following acute ischemic stroke (AIS) appear to contribute to worse neurologic outcomes. However, the effect of electrographic epileptiform abnormalities (EAs) more broadly is less clear. Here, we evaluate the impact of EAs, including electrographic seizures and periodic and rhythmic patterns, on outcomes in patients with AIS.

METHODS

This is a retrospective study of all patients with AIS aged ≥ 18 years who underwent at least 18 h of continuous electroencephalogram (EEG) monitoring at a single center between 2012 and 2017. EAs were classified according to American Clinical Neurophysiology Society (ACNS) nomenclature and included seizures and periodic and rhythmic patterns. EA burden for each 24-h epoch was defined using the following cutoffs: EA presence, maximum daily burden < 10% versus > 10%, maximum daily burden < 50% versus > 50%, and maximum daily burden using categories from ACNS nomenclature ("rare" < 1%; "occasional" 1-9%; "frequent" 10-49%; "abundant" 50-89%; "continuous" > 90%). Maximum EA frequency for each epoch was dichotomized into ≥ 1.5 Hz versus < 1.5 Hz. Poor neurologic outcome was defined as a modified Rankin Scale score of 4-6 (vs. 0-3 as good outcome) at hospital discharge.

RESULTS

One hundred and forty-three patients met study inclusion criteria. Sixty-seven patients (46.9%) had EAs. One hundred and twenty-four patients (86.7%) had poor outcome. On univariate analysis, the presence of EAs (OR 3.87 [1.27-11.71], p = 0.024) and maximum daily burden > 10% (OR 12.34 [2.34-210], p = 0.001) and > 50% (OR 8.26 [1.34-122], p = 0.035) were associated with worse outcomes. On multivariate analysis, after adjusting for clinical covariates (age, gender, NIHSS, APACHE II, stroke location, stroke treatment, hemorrhagic transformation, Charlson comorbidity index, history of epilepsy), EA presence (OR 5.78 [1.36-24.56], p = 0.017), maximum daily burden > 10% (OR 23.69 [2.43-230.7], p = 0.006), and maximum daily burden > 50% (OR 9.34 [1.01-86.72], p = 0.049) were associated with worse outcomes. After adjusting for covariates, we also found a dose-dependent association between increasing EA burden and increasing probability of poor outcomes (OR 1.89 [1.18-3.03] p = 0.009). We did not find an independent association between EA frequency and outcomes (OR: 4.43 [.98-20.03] p = 0.053). However, the combined effect of increasing EA burden and frequency ≥ 1.5 Hz (EA burden * frequency) was significantly associated with worse outcomes (OR 1.64 [1.03-2.63] p = 0.039).

CONCLUSIONS

Electrographic seizures and periodic and rhythmic patterns in patients with AIS are associated with worse outcomes in a dose-dependent manner. Future studies are needed to assess whether treatment of this EEG activity can improve outcomes.

Adaptive Sedation Monitoring From EEG in ICU Patients With Online Learning

Sedative medications are routinely administered to provide comfort and facilitate clinical care in critically ill ICU patients. Prior work shows that brain monitoring using electroencephalography (EEG) to track sedation levels may help medical personnel to optimize drug dosing and avoid the adverse effects of oversedation and undersedation. However, the performance of sedation monitoring methods proposed to date deal poorly with individual variability across patients, leading to inconsistent performance. To address this challenge we develop an online learning approach based on Adaptive Regularization of Weight Vectors (AROW). Our approach adaptively updates a sedation level prediction algorithm under a continuously evolving data distribution. The prediction model is gradually calibrated for individual patients in response to EEG observations and routine clinical assessments over time. The evaluations are performed on a population of 172 sedated ICU patients whose sedation levels were assessed using the Richmond Agitation-Sedation Scale (scores between -5 = comatose and 0 = awake). The proposed adaptive model achieves better performance than the same model without adaptation (average accuracies with tolerance of one level difference: 68.76% vs. 61.10%). Moreover, our approach is shown to be robust to sudden changes caused by label noise. Medication administrations have different effects on model performance. We find that the model performs best in patients receiving only propofol, compared to patients receiving no sedation or multiple simultaneous sedative medications.