American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology: 2021 Version

Differences in functional network between focal onset nonconvulsive status epilepticus and toxic metabolic encephalopathy: application to machine learning models for differential diagnosis

We aimed to compare network properties between focal-onset nonconvulsive status epilepticus (NCSE) and toxic/metabolic encephalopathy (TME) during periods of periodic discharge using graph theoretical analysis, and to evaluate the applicability of graph measures as markers for the differential diagnosis between focal-onset NCSE and TME, using machine learning algorithms. Electroencephalography (EEG) data from 50 focal-onset NCSE and 44 TMEs were analyzed. Epochs with nonictal periodic discharges were selected, and the coherence in each frequency band was analyzed. Graph theoretical analysis was performed to compare brain network properties between the groups. Eight different traditional machine learning methods were implemented to evaluate the utility of graph theoretical measures as input features to discriminate between the two conditions. The average degree (in delta, alpha, beta, and gamma bands), strength (in delta band), global efficiency (in delta and alpha bands), local efficiency (in delta band), clustering coefficient (in delta band), and transitivity (in delta band) were higher in TME than in NCSE. TME showed lower modularity (in delta band) and assortativity (in alpha, beta, and gamma bands) than NCSE. Machine learning algorithms based on EEG global graph measures classified NCSE and TME with high accuracy, and gradient boosting was the most accurate classification model with an area under the receiver operating characteristics curve of 0.904. Our findings on differences in network properties may provide novel insights that graph measures reflecting the network properties could be quantitative markers for the differential diagnosis between focal-onset NCSE and TME.

Electrographic seizure duration and inter-seizure intervals in focal status epilepticus

OBJECTIVE

To characterize the duration of seizures and inter-seizure intervals in focal status epilepticus (SE).

METHODS

We reviewed consecutive scalp EEG recordings from adult patients who were admitted for a first episode of focal status epilepticus. We identified electrographic seizure duration and inter-seizure intervals in the first diagnostic pretreatment EEG. We also reviewed isolated focal self-limiting seizures in epilepsy patients, as a comparison group for seizure duration.

RESULTS

We recorded 307 focal seizures in 100 consecutive focal SE episodes, with a median seizure duration of 107 s (IQR: 54-186), and 134 isolated focal self-limiting seizures in 42 epilepsy patients, with a median duration of 59 s (IQR: 30-90; p < .001). The only clinical feature of SE that significantly increased seizure duration was acute symptomatic etiology. In SE, 15% and 7% of seizures lasted longer than 300 and 600 s, respectively (t1 of the actual definition for tonic-clonic and focal SE), while only 1% of self-limiting seizures lasted longer than 300 s, and none lasted longer than 600 s. The analysis of inter-seizure intervals in SE with multiple seizures showed that 50% of the inter-seizure periods were shorter than 60 s, and 95% were shorter than 540 s (9 min). Patients who had an increase in seizure duration (last versus first) of at least 1.4 times showed an increased 30-day mortality.

SIGNIFICANCE

Focal seizures within a SE episode showed a wide range of duration, partly overlapping with the duration of focal self-limiting seizures but with a longer median duration. Inter-seizure intervals within an episode of SE were shorter than 1 min in 50% of the seizures and never lasted more than 10 min. Finally, an increase in seizure duration could represent an "electrophysiological biomarker" of a more severe SE episode, which may require more aggressive and rapid treatment.

Neural coding of autonomic functions in different states of consciousness

Detecting signs of residual neural activity in patients with altered states of consciousness is a crucial issue for the customization of neurorehabilitation treatments and clinical decision-making. With this large observational prospective study, we propose an innovative approach to detect residual signs of consciousness via the assessment of the amount of autonomic information coded within the brain. The latter was estimated by computing the mutual information (MI) between preprocessed EEG and ECG signals, to be then compared across consciousness groups, together with the absolute power and an international qualitative labeling. One-hundred seventy-four patients (73 females, 42%) were included in the study (median age of 65 years [IQR = 20], MCS +: 29, MCS -: 23, UWS: 29). Electroencephalography (EEG) information content was found to be mostly related to the coding of electrocardiography (ECG) activity, i.e., with higher MI (p < 0.05), in Unresponsive Wakefulness Syndrome and Minimally Consciousness State minus (MCS -). EEG-ECG MI, besides clearly discriminating patients in an MCS - and +, significantly differed between lesioned areas (sides) in a subgroup of unilateral hemorrhagic patients. Crucially, such an accessible and non-invasive measure of residual consciousness signs was robust across electrodes and patient groups. Consequently, exiting from a strictly neuro-centric consciousness detection approach may be the key to provide complementary insights for the objective assessment of patients' consciousness levels and for the patient-specific planning of rehabilitative interventions.

Deep learning for EEG-based prognostication after cardiac arrest: from current research to future clinical applications

Outcome prognostication in comatose patients after cardiac arrest (CA) remains to date a challenge. The major determinant of clinical outcome is the post-hypoxic/ischemic encephalopathy. Electroencephalography (EEG) is routinely used to assess neural functions in comatose patients. Currently, EEG-based outcome prognosis relies on visual evaluation by medical experts, which is time consuming, prone to subjectivity, and oblivious to complex patterns. The field of deep learning has given rise to powerful algorithms for detecting patterns in large amounts of data. Analyzing EEG signals of coma patients with deep neural networks with the goal of assisting in outcome prognosis is therefore a natural application of these algorithms. Here, we provide the first narrative literature review on the use of deep learning for prognostication after CA. Existing studies show overall high performance in predicting outcome, relying either on spontaneous or on auditory evoked EEG signals. Moreover, the literature is concerned with algorithmic interpretability, and has shown that largely, deep neural networks base their decisions on clinically or neurophysiologically meaningful features. We conclude this review by discussing considerations that the fields of artificial intelligence and neurology will need to jointly address in the future, in order for deep learning algorithms to break the publication barrier, and to be integrated in clinical practice.

Brief potentially ictal rhythmic discharges on intraoperative electrocorticography predict a good outcome of focal cortical dysplasia after surgical resection: a case report

BACKGROUND

Focal cortical dysplasia (FCD) is a common cause of drug-resistant epilepsy. Electroencephalography (EEG) biomarkers that predict good postoperative outcomes are essential for identifying patients with focal epilepsies.

CASE PRESENTATION

We report the case of a 21-year-old female with seizure onset at the age of 9, characterized by left-hand dystonic posturing and impaired awareness, which evolved to bilateral tonic-clonic seizures, evaluated in a neurological referral center in Lima, Peru. During 6-h video-EEG, interictal EEG revealing focal brief potentially ictal rhythmic discharges (BIRDs) over the right frontal central region, lasting less than 10 s. The ictal features were characterized by low-voltage fast activity over the same area. Brain magnetic resonance imaging (MRI) demonstrated a focal lesion of focal cortical dysplasia type II in the right frontal lobe. The patient underwent a lesionectomy guided by electrocorticography, which showed continuous polyspikes. BIRDs showing a brief burst of spikes lasting longer than 0.5 s, were also identified on intraoperative electrocorticography (ECoG) and helped define the extent of resection. The patient obtained an Engel Outcome Class IA at 6 years of follow-up.

CONCLUSIONS

The atypical BIRDs on ECoG can be used as a prognostic biomarker for prolonged seizure-freedom outcome in patients with epilepsy. Additional reports are needed in developing countries with and without brain MRI lesions to advance outpatient presurgical evaluations despite limited resources.

Sleep Fragmentation, Electroencephalographic Slowing, and Circadian Disarray in a Mouse Model for Intensive Care Unit Delirium

BACKGROUND

We aimed to further validate our previously published animal model for delirium by testing the hypothesis that in aged mice, Anesthesia, Surgery and simulated ICU conditions (ASI) induce sleep fragmentation, electroencephalographic (EEG) slowing, and circadian disarray consistent with intensive care unit (ICU) patients with delirium.

METHODS

A total of 41 mice were used. Mice were implanted with EEG electrodes and randomized to ASI or control groups. ASI mice received laparotomy, anesthesia, and simulated ICU conditions. Controls did not receive ASI. Sleep was recorded at the end of ICU conditions, and hippocampal tissue was collected on EEG recording. Arousals, EEG dynamics, and circadian gene expression were compared with t tests. Two-way repeated measures analysis of variance (RM ANOVA) was used to assess sleep according to light.

RESULTS

ASI mice experienced frequent arousals (36.6 ± 3.2 vs 26.5 ± 3.4; P = .044; 95% confidence interval [CI], 0.29-19.79; difference in mean ± SEM, 10.04 ± 4.62) and EEG slowing (frontal theta ratio, 0.223 ± 0.010 vs 0.272 ± 0.019; P = .026; 95% CI, -0.091 to -0.007; difference in mean ± SEM, -0.05 ± 0.02) relative to controls. In ASI mice with low theta ratio, EEG slowing was associated with a higher percentage of quiet wakefulness (38.2 ± 3.6 vs 13.4 ± 3.8; P = .0002; 95% CI, -35.87 to -13.84; difference in mean ± SEM, -24.86 ± 5.19). ASI mice slept longer during the dark phases of the circadian cycle (nonrapid eye movement [NREM], dark phase 1 [D1]: 138.9 ± 8.1 minutes vs 79.6 ± 9.6 minutes, P = .0003, 95% CI, -95.87 to -22.69, predicted mean difference ± SE: -59.28 ± 13.89; NREM, dark phase 2 (D2): 159.3 ± 7.3 minutes vs 112.6 ± 15.5 minutes, P = .006, 95% CI, -83.25 to -10.07, mean difference ± SE, -46.66 ± 13.89; rapid eye movement (REM), D1: 20.5 ± 2.1 minutes vs 5.8 ± 0.8 minutes, P = .001, 95% CI, -24.60 to -4.71, mean difference ± SE, -14. 65 ± 3.77; REM, D2: 21.0 ± 2.2 minutes vs 10.3 ± 1.4 minutes, P = .029, 95% CI, -20.64 to -0.76, mean difference ± SE, -10.70 ± 3.77). The expression of essential circadian genes was also lower in ASI mice (basic helix-loop-helix ARNT like [BMAL1] : -1.3 fold change; circadian locomotor output cycles protein kaput [CLOCK] : -1.2).

CONCLUSIONS

ASI mice experienced EEG and circadian changes mimicking those of delirious ICU patients. These findings support further exploration of this mouse approach to characterize the neurobiology of delirium.

Distinct patterns of interictal intracranial EEG in focal cortical dysplasia type I and II

OBJECTIVE

Focal cortical dysplasia (FCD) is the most common malformation causing refractory focal epilepsy. Surgical removal of the entire dysplastic cortex is crucial for achieving a seizure-free outcome. Precise presurgical distinctions between FCD types by neuroimaging are difficult, mainly in patients with normal magnetic resonance imaging findings. However, the FCD type is important for planning the extent of surgical approach and counselling.

METHODS

This study included patients with focal drug-resistant epilepsy and definite histopathological FCD type I or II diagnoses who underwent intracranial electroencephalography (iEEG). We detected interictal epileptiform discharges (IEDs) and their recruitment into repetitive discharges (RDs) to compare electrophysiological patterns characterizing FCD types.

RESULTS

Patients with FCD type II had a significantly higher IED rate (p < 0.005), a shorter inter-discharge interval within RD episodes (p < 0.003), sleep influence on decreased RD periodicity (p < 0.036), and longer RD episode duration (p < 0.003) than patients with type I. A Bayesian classifier stratified FCD types with 82% accuracy.

CONCLUSION

Temporal characteristics of IEDs and RDs reflect the histological findings of FCD subtypes and can differentiate FCD types I and II.

SIGNIFICANCE

Presurgical prediction of FCD type can help to plan a more tailored surgical approach in patients with normal magnetic resonance findings.

Neurological adverse effects of chimeric antigen receptor T-cell therapy

INTRODUCTION

Chimeric antigen receptor (CAR) T-cell is among the most prevalent approaches that act by directing T-cells toward cancer; however, they need to be optimized to minimize side effects and maximize efficacy before being used as standard treatment for malignancies. Neurotoxicity associated with CAR T-cell therapy has been well-documented in recent works.

AREAS COVERED

In this regard, two established syndromes exist. Immune effector cell-associated neurotoxicity syndrome (ICANS), previously called cytokine release encephalopathy syndrome (CRES), is a neuropsychiatric condition which can occur after therapy by immune effector cells (IEC) and T-lymphocytes utilizing treatments. Another syndrome is cytokine release syndrome (CRS), which may overlap with ICANS.

EXPERT OPINION

ICANS clinical manifestations include cerebral edema, mild lethargy, aphasia, and seizures. Notably, ICANS is associated with changes to EEG and neuroradiological findings. Therefore, it is necessary to make a timely and accurate diagnosis of neurological complications of CAR T-cells by clinical presentations, neuroimaging, and EEG. Since neurological events by different CAR T-cell products are heterogeneous, guides should be developed according to each product. Here, we provide an updated review of general information on CAR T-cell therapies and applications, neurological syndromes associated with their use, and risk factors contributing to ICANS.

Predicting posttraumatic epilepsy using admission electroencephalography after severe traumatic brain injury

OBJECTIVE

Posttraumatic epilepsy (PTE) develops in as many as one third of severe traumatic brain injury (TBI) patients, often years after injury. Analysis of early electroencephalographic (EEG) features, by both standardized visual interpretation (viEEG) and quantitative EEG (qEEG) analysis, may aid early identification of patients at high risk for PTE.

METHODS

We performed a case-control study using a prospective database of severe TBI patients treated at a single center from 2011 to 2018. We identified patients who survived 2 years postinjury and matched patients with PTE to those without using age and admission Glasgow Coma Scale score. A neuropsychologist recorded outcomes at 1 year using the Expanded Glasgow Outcomes Scale (GOSE). All patients underwent continuous EEG for 3-5 days. A board-certified epileptologist, blinded to outcomes, described viEEG features using standardized descriptions. We extracted 14 qEEG features from an early 5-min epoch, described them using qualitative statistics, then developed two multivariable models to predict long-term risk of PTE (random forest and logistic regression).

RESULTS

We identified 27 patients with and 35 without PTE. GOSE scores were similar at 1 year (p = .93). The median time to onset of PTE was 7.2 months posttrauma (interquartile range = 2.2-22.2 months). None of the viEEG features was different between the groups. On qEEG, the PTE cohort had higher spectral power in the delta frequencies, more power variance in the delta and theta frequencies, and higher peak envelope (all p < .01). Using random forest, combining qEEG and clinical features produced an area under the curve of .76. Using logistic regression, increases in the delta:theta power ratio (odds ratio [OR] = 1.3, p < .01) and peak envelope (OR = 1.1, p < .01) predicted risk for PTE.

SIGNIFICANCE

In a cohort of severe TBI patients, acute phase EEG features may predict PTE. Predictive models, as applied to this study, may help identify patients at high risk for PTE, assist early clinical management, and guide patient selection for clinical trials.

Relationship between serum neuron-specific enolase and EEG after cardiac arrest: A reappraisal

OBJECTIVE

Electroencephalogram (EEG) and serum neuron specific enolase (NSE) are frequently used prognosticators after cardiac arrest (CA). This study explored the association between NSE and EEG, considering the role of EEG timing, its background continuity, reactivity, occurrence of epileptiform discharges, and pre-defined malignancy degree.

METHODS

Retrospective analysis including 445 consecutive adults from a prospective registry, surviving the first 24 hours after CA and undergoing multimodal evaluation. EEG were interpreted blinded to NSE results.

RESULTS

Higher NSE was associated with poor EEG prognosticators, such as increasing malignancy, repetitive epileptiform discharges and lack of background reactivity, independently of EEG timing (including sedation and temperature). When stratified for background continuity, NSE was higher with repetitive epileptiform discharges, except in the case of suppressed EEGs. This relationship showed some variation according to the recording time.

CONCLUSIONS

Neuronal injury after CA, reflected by NSE, correlates with several EEG features: increasing EEG malignancy, lack of background reactivity, and presence of repetitive epileptiform discharges. The correlation between epileptiform discharges and NSE is influenced by underlying EEG background and timing.

SIGNIFICANCE

This study, describing the complex interplay between serum NSE and epileptiform features, suggests that epileptiform discharges reflect neuronal injury particularly in non-suppressed EEG.

Evaluating salvage electroconvulsive therapy for the treatment of prolonged super refractory status epilepticus: A case series

BACKGROUND AND OBJECTIVES

Clinicians have treated super refractory status epilepticus (SRSE) with electroconvulsive therapy (ECT); however, data supporting the practice are scant and lack rigorous evaluation of continuous electroencephalogram (cEEG) changes related to therapy. This study aims to describe a series of patients with SRSE treated at our institution with ECT and characterize cEEG changes using a blinded review process.

METHODS

We performed a single-center retrospective study of consecutive patients admitted for SRSE and treated with ECT from January 2014 to December 2022. Our primary outcome was the resolution of SRSE. Secondary outcomes included changes in ictal-interictal EEG patterns, anesthetic burden, treatment-associated adverse events, and changes in clinical examination. cEEG was reviewed pre- and post-ECT by blinded epileptologists.

RESULTS

Ten patients underwent treatment with ECT across 11 admissions (8 female, median age 57 years). At the time of ECT initiation, nine patients had ongoing SRSE while two had highly ictal patterns and persistent encephalopathy following anesthetic wean, consistent with late-stage SRSE. Super-refractory status epilepticus resolution occurred with a median time to cessation of 4 days (interquartile range [IQR]: 3-9 days) following ECT initiation. Background continuity improved in five patients and periodic discharge frequency decreased in six. There was a decrease in anesthetic use following the completion of ECT and an improvement in neurological exams. There were no associated adverse events.

DISCUSSION

In our cohort, ECT was associated with improvement of ictal-interictal patterns on EEG, and resolution of SRSE, and was not associated with serious adverse events. Further controlled studies are needed.

Systematic Evaluation of Research Priorities in Critical Care Electroencephalography

PURPOSE

The Critical Care EEG Monitoring Research Consortium (CCEMRC) is an international research group focusing on critical care EEG and epilepsy. As CCEMRC grew to include 50+ institutions over the past decade, members met to establish research priorities.

METHODS

The authors used an analytical hierarchy process-based research prioritization method, adapted from an approach previously applied to a Department of Defense health-related research program. Forty-six CCEMRC members identified and scored a set of eight clinical problems (CPs) and 15 research topic areas (RTAs) at an annual CCEMRC meeting. Members scored CPs on three criteria using a five-point ordinal scale: Incidence, Impact, and Gap Size; and RTAs on four additional criteria: Niche, Feasibility, Scientific Importance, and Medical Importance, each of which was assigned a weight. The first three RTA criteria were scored using a five-point scale, and CPs were mapped to RTAs using a four-point scale. The Medical Importance score was a weighted average of its mapping scores and the CP score. Finally, a Priority score was calculated for each RTA as a product of the four RTA criteria scores.

RESULTS

The CPs with the highest scores were "Altered mental status" and "Long-term neurologic disability after hospital discharge." The RTAs with the highest priority scores were "Development of risk prediction tools," "Multicenter observational studies," and "Outcome prediction."

CONCLUSIONS

Research prioritization helped CCEMRC evaluate its current research trajectory, identify high-priority near-term research pursuits, and create a roadmap for future research plans aligned with its mission. This approach may be helpful to other academic consortia and research programs.

Perioperative EEG background and discharge abnormalities in children undergoing cardiac surgery: a prospective single-centre observational study

BACKGROUND

We analysed the characteristics of abnormal electroencephalogram (EEG) patterns before, during, and 48 h after cardiac surgery in patients with heterogeneous congenital heart disease to assess their relationship to demographic and perioperative variables and to early patient outcomes.

METHODS

In 437 patients enrolled in a single centre, EEG was evaluated for background (including sleep-wake cycle) and discharge (seizures, spikes/sharp waves, pathological delta brushes) abnormalities. Clinical data (arterial blood pressure, doses of inotropic drugs, and serum lactate concentrations) were recorded every 3 h. Postoperative brain MRI was performed before discharge.

RESULTS

Preoperative, intraoperative, and postoperative EEG was monitored in 139, 215, and 437 patients, respectively. Patients with a degree of preoperative background abnormalities (n=40) had more severe intraoperative and postoperative EEG abnormalities (P<0.0001). Intraoperatively, 106/215 (49.3%) patients progressed into an isoelectric EEG. Longer durations of isoelectric EEG were associated with more severe postoperative EEG abnormalities and brain injury on MRI (Ps≤0.003). Postoperative background abnormalities occurred in 218/437 (49.9%) patients, and 119 (54.6%) of them had not recovered after surgery. Seizures occurred in 36/437 (8.2%) patients, spikes/sharp waves in 359/437 (82.2%), and pathological delta brushes in 9/437 (2.0%). Postoperative EEG abnormalities correlated with degree of brain injury on MRI (Ps≤0.02). Demographic and perioperative variables were significantly correlated with postoperative EEG abnormalities, which in turn correlated with adverse clinical outcomes.

CONCLUSIONS

Perioperative EEG abnormalities occurred frequently and correlated with numerous demographic and perioperative variables and adversely correlated with postoperative EEG abnormalities and early outcomes. The relation of EEG background and discharge abnormalities with long-term neurodevelopmental outcomes remains to be explored.

Cerebral Autoregulation Status in Relation to Brain Injury on Electroencephalogram and Magnetic Resonance Imaging in Children Following Cardiac Surgery

Background Disturbed cerebral autoregulation has been reported in children with congenital heart disease before and during cardiopulmonary bypass surgery, but not after. We sought to characterize the cerebral autoregulation status in the early postoperative period in relation to perioperative variables and brain injuries. Methods and Results A prospective and observational study was conducted in 80 patients in the first 48 hours following cardiac surgery. Cerebral oximetry/pressure index (COPI) was retrospectively calculated as a moving linear correlation coefficient between mean arterial blood pressure and cerebral oxygen saturation. Disturbed autoregulation was defined as COPI >0.3. Correlations of COPI with demographic and perioperative variables as well as brain injuries on electroencephalogram and magnetic resonance imaging and early outcomes were analyzed. Thirty-six (45%) patients had periods of abnormal COPI for 7.81 hours (3.38 hours) either at hypotension (median <45 mm Hg) or hypertension (median >90 mm Hg) or both. Overall, COPI became significantly lower over time, suggesting improved autoregulatory status during the 48 postoperative hours. All of the demographic and perioperative variables were significantly associated with COPI, which in turn was associated with the degree of brain injuries and early outcomes. Conclusions Children with congenital heart disease following cardiac surgery often have disturbed autoregulation. Cerebral autoregulation is at least partly the underlying mechanism of brain injury in those children. Careful clinical management to manipulate the related and modifiable factors, particularly arterial blood pressure, may help to maintain adequate cerebral perfusion and reduce brain injury early after cardiopulmonary bypass surgery. Further studies are warranted to determine the significance of impaired cerebral autoregulation in relation to long-term neurodevelopment outcomes.

Approaches to neuroprotection in pediatric neurocritical care

Acute neurologic injuries represent a common cause of morbidity and mortality in children presenting to the pediatric intensive care unit. After primary neurologic insults, there may be cerebral brain tissue that remains at risk of secondary insults, which can lead to worsening neurologic injury and unfavorable outcomes. A fundamental goal of pediatric neurocritical care is to mitigate the impact of secondary neurologic injury and improve neurologic outcomes for critically ill children. This review describes the physiologic framework by which strategies in pediatric neurocritical care are designed to reduce the impact of secondary brain injury and improve functional outcomes. Here, we present current and emerging strategies for optimizing neuroprotective strategies in critically ill children.

Clinical and electroencephalography characteristics of 45 patients with neonatal seizures

OBJECTIVES

The aim of our study was to retrospectively research the semiology of neonatal seizures (NSs) based on the 2021 classification scheme of the International League Against Epilepsy, and the relationship between etiology and electroclinical features.

METHODS

Patients admitted to Children's Hospital of Chongqing Medical University from May 1, 2020 to March 30, 2022 and diagnosed with NSs were included to retrospectively investigate the etiology, seizure characteristics, prognosis, and ictal and interictal video electroencephalography (EEG) characteristics.

RESULTS

Of the 45 patients, 73.3% had definite etiology. Twenty-seven patients had electro-clinical seizures, of which two had both electro-clinical and electrographic-only seizures. Electrographic-only seizures were reported in 18 patients. The tonic, clonic, and electrographic-only seizures were associated with various etiologies. Both tonic and clonic seizures occurred in acute symptomatic seizures and were associated with neonatal epilepsy. 50% of tonic seizures were related to genetic factors. Among the clonic seizures, 50.0% occurred in acute symptomatic seizures. Epileptic spasms always indicated neonatal epilepsy. There were few patients who experienced automatisms and sequential seizures, and these two seizure types were associated with brain malformation and genetic factors, respectively. Patients with a normal interictal EEG had acute symptomatic seizures. whereas the interictal EEG of patients with neonatal epilepsy mainly showed burst-suppression or multifocal discharges. The ictal EEG recordings were related to seizure semiology.

CONCLUSION

Seizure semiology and video EEG are suggestive of potential causes but do not provide a definite etiology.

Guidelines for Neuroprognostication in Comatose Adult Survivors of Cardiac Arrest

BACKGROUND

Among cardiac arrest survivors, about half remain comatose 72 h following return of spontaneous circulation (ROSC). Prognostication of poor neurological outcome in this population may result in withdrawal of life-sustaining therapy and death. The objective of this article is to provide recommendations on the reliability of select clinical predictors that serve as the basis of neuroprognostication and provide guidance to clinicians counseling surrogates of comatose cardiac arrest survivors.

METHODS

A narrative systematic review was completed using Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology. Candidate predictors, which included clinical variables and prediction models, were selected based on clinical relevance and the presence of an appropriate body of evidence. The Population, Intervention, Comparator, Outcome, Timing, Setting (PICOTS) question was framed as follows: "When counseling surrogates of comatose adult survivors of cardiac arrest, should [predictor, with time of assessment if appropriate] be considered a reliable predictor of poor functional outcome assessed at 3 months or later?" Additional full-text screening criteria were used to exclude small and lower-quality studies. Following construction of the evidence profile and summary of findings, recommendations were based on four GRADE criteria: quality of evidence, balance of desirable and undesirable consequences, values and preferences, and resource use. In addition, good practice recommendations addressed essential principles of neuroprognostication that could not be framed in PICOTS format.

RESULTS

Eleven candidate clinical variables and three prediction models were selected based on clinical relevance and the presence of an appropriate body of literature. A total of 72 articles met our eligibility criteria to guide recommendations. Good practice recommendations include waiting 72 h following ROSC/rewarming prior to neuroprognostication, avoiding sedation or other confounders, the use of multimodal assessment, and an extended period of observation for awakening in patients with an indeterminate prognosis, if consistent with goals of care. The bilateral absence of pupillary light response > 72 h from ROSC and the bilateral absence of N20 response on somatosensory evoked potential testing were identified as reliable predictors. Computed tomography or magnetic resonance imaging of the brain > 48 h from ROSC and electroencephalography > 72 h from ROSC were identified as moderately reliable predictors.

CONCLUSIONS

These guidelines provide recommendations on the reliability of predictors of poor outcome in the context of counseling surrogates of comatose survivors of cardiac arrest and suggest broad principles of neuroprognostication. Few predictors were considered reliable or moderately reliable based on the available body of evidence.

Diagnostic Accuracy of Ambulatory EEG vs Routine EEG in Patients With First Single Unprovoked Seizure

Background and Objective

To evaluate the diagnostic accuracy of the ambulatory EEG (aEEG) at detecting interictal epileptiform discharges (IEDs)/seizures compared with routine EEG (rEEG) and repetitive/second rEEG in patients with a first single unprovoked seizure (FSUS). We also evaluated the association between IED/seizures on aEEG and seizure recurrence within 1 year of follow-up.

Methods

We prospectively evaluated 100 consecutive patients with FSUS at the provincial Single Seizure Clinic. They underwent 3 sequential EEG modalities: first rEEG, second rEEG, and aEEG. Clinical epilepsy diagnosis was ascertained based on the 2014 International League Against Epilepsy definition by a neurologist/epileptologist at the clinic. An EEG-certified epileptologist/neurologist interpreted all 3 EEGs. All patients were followed up for 52 weeks until they had either second unprovoked seizure or maintained single seizure status. Accuracy measures (sensitivity, specificity, negative and positive predictive values, and likelihood ratios), receiver operating characteristic (ROC) analysis, and area under the curve (AUC) were used to evaluate the diagnostic accuracy of each EEG modality. Life tables and the Cox proportional hazard model were used to estimate the probability and association of seizure recurrence.

Results

Ambulatory EEG captured IED/seizures with a sensitivity of 72%, compared with 11% for the first rEEG and 22% for the second rEEG. The diagnostic performance of the aEEG was statistically better (AUC: 0.85) compared with the first rEEG (AUC: 0.56) and second rEEG (AUC: 0.60). There were no statistically significant differences between the 3 EEG modalities regarding specificity and positive predictive value. Finally, IED/seizure on the aEEG was associated with more than 3 times the hazard of seizure recurrence.

Discussion

The overall diagnostic accuracy of aEEG at capturing IED/seizures in people presenting with FSUS was higher than the first and second rEEGs. We also found that IED/seizures on the aEEG were associated with an increased risk of seizure recurrence.

Classification of Evidence

This study provides Class I evidence supporting that, in adults with First Single Unprovoked Seizure (FSUS), 24-h ambulatory EEG has increased sensitivity when compared with routine and repeated EEG.

Advanced Neuromonitoring Modalities on the Horizon: Detection and Management of Acute Brain Injury in Children

Timely detection and monitoring of acute brain injury in children is essential to mitigate causes of injury and prevent secondary insults. Increasing survival in critically ill children has emphasized the importance of neuroprotective management strategies for long-term quality of life. In emergent and critical care settings, traditional neuroimaging modalities, such as computed tomography and magnetic resonance imaging (MRI), remain frontline diagnostic techniques to detect acute brain injury. Although detection of structural and anatomical abnormalities remains crucial, advanced MRI sequences assessing functional alterations in cerebral physiology provide unique diagnostic utility. Head ultrasound has emerged as a portable neuroimaging modality for point-of-care diagnosis via assessments of anatomical and perfusion abnormalities. Application of electroencephalography and near-infrared spectroscopy provides the opportunity for real-time detection and goal-directed management of neurological abnormalities at the bedside. In this review, we describe recent technological advancements in these neurodiagnostic modalities and elaborate on their current and potential utility in the detection and management of acute brain injury.

Thalamocortical circuits in generalized epilepsy: Pathophysiologic mechanisms and therapeutic targets

Generalized epilepsy affects 24 million people globally; at least 25% of cases remain medically refractory. The thalamus, with widespread connections throughout the brain, plays a critical role in generalized epilepsy. The intrinsic properties of thalamic neurons and the synaptic connections between populations of neurons in the nucleus reticularis thalami and thalamocortical relay nuclei help generate different firing patterns that influence brain states. In particular, transitions from tonic firing to highly synchronized burst firing mode in thalamic neurons can cause seizures that rapidly generalize and cause altered awareness and unconsciousness. Here, we review the most recent advances in our understanding of how thalamic activity is regulated and discuss the gaps in our understanding of the mechanisms of generalized epilepsy syndromes. Elucidating the role of the thalamus in generalized epilepsy syndromes may lead to new opportunities to better treat pharmaco-resistant generalized epilepsy by thalamic modulation and dietary therapy.

Quantitative assessment of burst suppression as a predictor of seizure recurrence in refractory status epilepticus

OBJECTIVE

To determine whether quantitative EEG analysis of burst suppression can predict seizure recurrence in patients with refractory status epilepticus (RSE) being treated with anesthetic doses of continuous IV antiseizure medications (cIVASM).

METHODS

Quantitative assessment of burst suppression (including epileptiform discharges [EDs] and evolution) in 31 occasions (from 27 patients), and correlation with seizure recurrence up to 48 hours post sedative wean.

RESULTS

Occasions resulting in seizure recurrence (vs. no seizure recurrence) had lower burst (8.4 vs. 10.6 µV) and interburst interval (IBI) (4.2 vs. 4.8 µV) average amplitude, duration (bursts 2.8 vs. 3.6 s: IBIs 3.6 vs. 4.4 s); and burst total power (0.4 vs. 0.7 µV2). Bursts (0.86 vs. 0.60) and IBIs (0.28 vs. 0.07) with EDs, higher number of EDs within bursts (mean 2.1 vs. 1.4) and IBIs (0.6 vs. 0.2), and positive evolution measures all predicted seizure recurrence, although EDs had the greatest adjusted odds ratio on multivariate analysis.

CONCLUSIONS

For patients in burst suppression, successful wean of cIVASM was not determined by classical burst suppression measures, but instead how "epileptiform" bursts and IBIs were, as determined by EDs in both bursts and IBIs and surrogates for evolution within bursts.

SIGNIFICANCE

If confirmed, these objective measures could be used during clinical care to help determine when to wean cIVASM in patients with RSE.

Pediatric Cerebral Sinovenous Thrombosis and Risk for Epilepsy

BACKGROUND

Cerebral sinovenous thrombosis (CSVT) is a rare form of pediatric stroke with significant morbidity. We determined cumulative incidence and predictors of acute seizures, remote seizures, and epilepsy after pediatric CSVT.

METHODS

Retrospective analysis of 131 neonates and children with neuroimaging-confirmed CSVT enrolled between 2008 and 2020 from a single-center prospective consecutive cohort. Acute seizures occurred within 7 days of CSVT. Remote seizures occurred >7 days after CSVT. Epilepsy was defined as 2 or more remote seizures at least 24 hours apart. Survival methods determined the incidence of and risk factors for remote seizures and epilepsy.

RESULTS

Acute seizures occurred in 14/33 neonates (42%) and 19/98 children (19%). Among children, hemorrhage predicted acute seizures (OR 6.6, 95% CI 1.9 to 22.4, P = 0.003). Remote seizures occurred in six neonates; five developed epilepsy. Remote seizures occurred in 14 children; 10 developed epilepsy. In neonates, 1- and 3-year epilepsy-free survival were 86% (95% CI 62% to 95%) and 66% (95% CI 32% to 87%). One- and 3-year epilepsy-free survival in children were 88% (95% CI 76% to 92%) and 84% (95% CI 59% to 86%). In multivariable analysis for children, acute seizures predicted epilepsy (HR 3.8, 95% CI 1.1-13.3, P = 0.039). In both cohorts, Pediatric Stroke Outcome Measure scores at last follow-up were worse in those with epilepsy compared to those without.

CONCLUSIONS

Acute seizures occurred in approximately one quarter of our cohort and are an epilepsy risk factor in children with CSVT. Neonates and children with epilepsy had worse outcomes than those without.

Association Between Induced Burst Suppression and Clinical Outcomes in Patients With Refractory Status Epilepticus: A 9-Year Cohort Study

BACKGROUND AND OBJECTIVES

To investigate the frequency of induced EEG burst suppression pattern during continuous IV anesthesia (IVAD) and associated outcomes in adult patients treated for refractory status epilepticus (RSE).

METHODS

Patients with RSE treated with anesthetics at a Swiss academic care center from 2011 to 2019 were included. Clinical data and semiquantitative EEG analyses were assessed. Burst suppression was categorized as incomplete burst suppression (with ≥20% and <50% suppression proportion) or complete burst suppression (with ≥50% suppression proportion). The frequency of induced burst suppression and association of burst suppression with outcomes (persistent seizure termination, in-hospital survival, and return to premorbid neurologic function) were the endpoints.

RESULTS

We identified 147 patients with RSE treated with IVAD. Among 102 patients without cerebral anoxia, incomplete burst suppression was achieved in 14 (14%) with a median of 23 hours (interquartile range [IQR] 1-29) and complete burst suppression was achieved in 21 (21%) with a median of 51 hours (IQR 16-104). Age, Charlson comorbidity index, RSE with motor symptoms, the Status Epilepticus Severity Score and arterial hypotension requiring vasopressors were identified as potential confounders in univariable comparisons between patients with and without any burst suppression. Multivariable analyses revealed no associations between any burst suppression and the predefined endpoints. However, among 45 patients with cerebral anoxia, induced burst suppression was associated with persistent seizure termination (72% without vs 29% with burst suppression, p = 0.004) and survival (50% vs 14% p = 0.005).

DISCUSSION

In adult patients with RSE treated with IVAD, burst suppression with ≥50% suppression proportion was achieved in every fifth patient and not associated with persistent seizure termination, in-hospital survival, or return to premorbid neurologic function.

The association between the presence and burden of periodic discharges and outcome in septic patients: an observational prospective study

BACKGROUND

Sepsis-associated encephalopathy (SAE) is frequent in septic patients. Electroencephalography (EEG) is very sensitive to detect early epileptic abnormalities, such as seizures and periodic discharges (PDs), and to quantify their duration (the so-called burden). However, the prevalence of these EEG abnormalities in septic patients, as well as their effect on morbidity and mortality, are still unclear. The aims of this study were to assess whether the presence of electrographic abnormalities (i.e. the absence of reactivity, the presence and burden of seizures and PDs) was associated with functional outcome and mortality in septic patients and whether these abnormalities were associated with sepsis-associated encephalopathy (SAE).

METHODS

We prospectively included septic patients, without known chronic or acute intracranial disease or pre-existing acute encephalopathy, requiring ICU admission in a tertiary academic centre. Continuous EEG monitoring was started within 72 h after inclusion and performed for up to 7 days. A comprehensive assessment of consciousness and delirium was performed twice daily by a trained neuropsychologist. Primary endpoints were unfavourable functional outcome (UO, defined as a Glasgow Outcome Scale-Extended-GOSE-score < 5), and mortality collected at hospital discharge and secondary endpoint was the association of PDs with SAE. Mann-Whitney, Fisher's exact and χ2 tests were used to assess differences in variables between groups, as appropriate. Multivariable logistic regression analysis with in-hospital mortality, functional outcome, SAE or PDs as the dependent variables were performed.

RESULTS

We included 92 patients. No seizures were identified. Nearly 25% of patients had PDs. The presence of PDs and PDs burden was associated with UO in univariate (n = 15 [41%], p = 0.005 and p = 0.008, respectively) and, for PDs presence, also in multivariate analysis after correcting for disease severity (OR 3.82, IC 95% [1.27-11.49], p = 0.02). The PDs burden negatively correlated with GOSE (Spearman's coefficient ρ = - 0.2, p = 0.047). The presence of PDs was also independently associated with SAE (OR 8.98 [1.11-72.8], p = 0.04). Reactivity was observed in the majority of patients and was associated with outcomes (p = 0.044 for both functional outcome and mortality).

CONCLUSION

Our findings suggest that PDs and PDs burden are associated with SAE and might affect outcome in septic patients.

Use of Prognostication Instruments in Prognostication Procedures of Postanoxic Coma Patients over Time: A Retrospective Study

BACKGROUND

Many survivors of cardiovascular arrest remain in a postanoxic coma. The neurologist's task is to provide the most accurate assessment of the patient's neurologic prognosis through a multimodal approach of clinical and technical tests. The aim of this study is to analyze differences and developments in the concept of neurological prognosis assessment and in-hospital outcome of patients over a five year-period.

METHODS

This retrospective observational study included 227 patients with postanoxic coma treated in the medical intensive care unit of the University Hospital, Mannheim from January 2016 to May 2021. We retrospectively analyzed patient characteristics, post-cardiac arrest care, and the use of clinical and technical tests for neurological prognosis assessment and patient outcome.

RESULTS

Over the observation period, 215 patients received a completed neurological prognosis assessment. Regarding the multimodal prognostic assessment, patients with poor prognosis (54%) received significantly fewer diagnostic modalities than patients with very likely poor (20.5%), indeterminate (24.2%), or good prognosis (1.4%; p = 0.001). The update of the DGN guidelines in 2017 had no effect on the number of performed prognostic parameters per patient. The finding of bilaterally absent pupillary light reflexes or severe anoxic injury on CT contributed most to a poor prognosis category (OR 8.38, 95%CI 4.01-7.51 and 12.93, 95%CI 5.55-30.13, respectively), whereas a malignant EEG pattern and NSE > 90 µg/L at 72 h resulted in the lowest OR (5.11, 95%CI 2.32-11.25, and 5.89, 95%CI 3.14-11.06, respectively) for a poor prognosis category. Assessment of baseline NSE significantly increased over the years (OR 1.76, 95%CI 1.4-2.22, p < 0.001), and assessment of follow-up NSE at 72 h trended to increase (OR 1.19, 95%CI 0.99-1.43, p = 0.06). In-hospital mortality was high (82.8%), remained unchanged over the observation period, and corresponded to the number of patients in whom life-sustaining measures were discontinued.

CONCLUSIONS

Among comatose survivors of cardiac arrest, the prognosis remains poor. Prognostication of a poor outcome led nearly exclusively to withdrawal of care. Prognostic modalities varied considerably with regard to their contribution to a poor prognosis category. Increasing enforcement of a standardized prognosis assessment and standardized evaluation of diagnostic modalities are needed to avoid false-positive prognostication of poor outcomes.

CAR t-cell therapy in BOlogNa-NEUrotoxicity TReatment and Assessment in Lymphoma (CARBON-NEUTRAL): proposed protocol and results from an Italian study

OBJECTIVE

To investigate neurotoxicity clinical and instrumental features, incidence, risk factors, and early and long-term prognosis in lymphoma patients who received CAR T-cell therapy.

METHODS

In this prospective study, consecutive refractory B-cell non-Hodgkin lymphoma patients who received CAR T-cell therapy were included. Patients were comprehensively evaluated (neurological examination, EEG, brain MRI, and neuropsychological test) before and after (two and twelve months) CAR T-cells. From the day of CAR T-cells infusion, patients underwent daily neurological examinations to monitor the development of neurotoxicity.

RESULTS

Forty-six patients were included in the study. The median age was 56.5 years, and 13 (28%) were females. Seventeen patients (37%) developed neurotoxicity, characterized by encephalopathy frequently associated with language disturbances (65%) and frontal lobe dysfunction (65%). EEG and brain FDG-PET findings also supported a predominant frontal lobe involvement. The median time at onset and duration were five and eight days, respectively. Baseline EEG abnormalities predicted ICANS development in the multivariable analysis (OR 4.771; CI 1.081-21.048; p = 0.039). Notably, CRS was invariably present before or concomitant with neurotoxicity, and all patients who exhibited severe CRS (grade ≥ 3) developed neurotoxicity. Serum inflammatory markers were significantly higher in patients who developed neurotoxicity. A complete neurological resolution following corticosteroids and anti-cytokines monoclonal antibodies was reached in all patients treated, except for one patient developing a fatal fulminant cerebral edema. All surviving patients completed the 1-year follow-up, and no long-term neurotoxicity was observed.

CONCLUSIONS

In the first prospective Italian real-life study, we presented novel clinical and investigative insights into ICANS diagnosis, predictive factors, and prognosis.

Development of Expert-Level Classification of Seizures and Rhythmic and Periodic Patterns During EEG Interpretation

BACKGROUND AND OBJECTIVES

Seizures (SZs) and other SZ-like patterns of brain activity can harm the brain and contribute to in-hospital death, particularly when prolonged. However, experts qualified to interpret EEG data are scarce. Prior attempts to automate this task have been limited by small or inadequately labeled samples and have not convincingly demonstrated generalizable expert-level performance. There exists a critical unmet need for an automated method to classify SZs and other SZ-like events with expert-level reliability. This study was conducted to develop and validate a computer algorithm that matches the reliability and accuracy of experts in identifying SZs and SZ-like events, known as "ictal-interictal-injury continuum" (IIIC) patterns on EEG, including SZs, lateralized and generalized periodic discharges (LPD, GPD), and lateralized and generalized rhythmic delta activity (LRDA, GRDA), and in differentiating these patterns from non-IIIC patterns.

METHODS

We used 6,095 scalp EEGs from 2,711 patients with and without IIIC events to train a deep neural network, SPaRCNet, to perform IIIC event classification. Independent training and test data sets were generated from 50,697 EEG segments, independently annotated by 20 fellowship-trained neurophysiologists. We assessed whether SPaRCNet performs at or above the sensitivity, specificity, precision, and calibration of fellowship-trained neurophysiologists for identifying IIIC events. Statistical performance was assessed by the calibration index and by the percentage of experts whose operating points were below the model's receiver operating characteristic curves (ROCs) and precision recall curves (PRCs) for the 6 pattern classes.

RESULTS

SPaRCNet matches or exceeds most experts in classifying IIIC events based on both calibration and discrimination metrics. For SZ, LPD, GPD, LRDA, GRDA, and "other" classes, SPaRCNet exceeds the following percentages of 20 experts-ROC: 45%, 20%, 50%, 75%, 55%, and 40%; PRC: 50%, 35%, 50%, 90%, 70%, and 45%; and calibration: 95%, 100%, 95%, 100%, 100%, and 80%, respectively.

DISCUSSION

SPaRCNet is the first algorithm to match expert performance in detecting SZs and other SZ-like events in a representative sample of EEGs. With further development, SPaRCNet may thus be a valuable tool for an expedited review of EEGs.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that among patients with epilepsy or critical illness undergoing EEG monitoring, SPaRCNet can differentiate (IIIC) patterns from non-IIIC events and expert neurophysiologists.

Non-convulsive status epilepticus possibly induced by a rapid correction of severe hyperkalemia: a case report and literature review

BACKGROUND

Patients with chronic kidney disease frequently develop neurological complications including confusion and altered consciousness. Non-convulsive status epilepticus, which is characterized by a change in behavior and/or mental process accompanied by epileptiform discharges on electroencephalogram in the absence of convulsive seizures, is one of the overlooked causes of altered consciousness. The incidence and precise pathophysiological mechanism of non-convulsive status epilepticus in patients with kidney disease, and especially in patients with electrolyte disturbances, remains unknown. We recently treated an older patient with chronic kidney disease and severe hyperkalemia in whom non-convulsive status epilepticus developed following a correction of severe hyperkalemia.

CASE PRESENTATION

An 82-year-old male was admitted to our hospital at midnight because of weakness of all four limbs (Day 1). He underwent urgent hemodialysis for severe hyperkalemia (9.84 mEq/L) and his serum potassium concentration decreased to 4.97 mEq/L. He regained full consciousness and his limb weakness improved on the morning of Day 2, but he became confused in the evening. Electroencephalogram revealed repeated low-voltage ictal discharges in the right occipital region and a diagnosis of non-convulsive status epilepticus was made. Following medication with fosphenytoin and phenytoin, the patient became fully alert and orientated on Day 8.

CONCLUSION

We speculate that a rapid correction of hyperkalemia was the possible cause of non-convulsive status epilepticus development. To our knowledge, this is the first report of non-convulsive status epilepticus from a potassium abnormality. We described a case of this condition in detail and summarized 78 previous case reports of non-convulsive status epilepticus with kidney disease or electrolyte disturbances.

Critical care EEG monitoring: improving access and unravelling potentially epileptic patterns

PURPOSE OF REVIEW

The major advances in critical care EEG have been the development of rapid response EEG, major revision of the American Clinical Neurophysiology Society's (ACNS) standardized critical care EEG terminology, and the commencement of treatment trials on rhythmic and periodic patterns (RPPs) that do not qualify as seizures.

RECENT FINDINGS

Rapid response EEG (rEEG) has proven an important supplement to full montage continuous EEG monitoring (cEEG). This EEG can be applied in a few minutes and provides excellent ability to exclude seizures, selecting those where conversion to cEEG would have the greatest diagnostic yield. Once cEEG has been commenced, the durations required to adequately exclude seizures have been refined. The ACNS provided major revision and expansion to the standardized critical care EEG terminology, which paved the way for determining with great accuracy the RPPs that are associated with seizures and that are capable of causing neurologic symptoms and/or secondary neuronal injury. The current limitations to multicenter treatment trials of these patterns have been highlighted.

SUMMARY

Novel methods of EEG in critical care have been expanding access to all patients where clinically indicated. Standardized EEG terminology has provided the framework to determine what patterns in which presenting causes warrant treatment vs. those that do not.

Neuroprognostication in the Post Cardiac Arrest Patient: A Canadian Cardiovascular Society Position Statement

Cardiac arrest (CA) is associated with a low rate of survival with favourable neurologic recovery. The most common mechanism of death after successful resuscitation from CA is withdrawal of life-sustaining measures on the basis of perceived poor neurologic prognosis due to underlying hypoxic-ischemic brain injury. Neuroprognostication is an important component of the care pathway for CA patients admitted to hospital but is complex, challenging, and often guided by limited evidence. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system to evaluate the evidence underlying factors or diagnostic modalities available to determine prognosis, recommendations were generated in the following domains: (1) circumstances immediately after CA; (2) focused neurologic exam; (3) myoclonus and seizures; (4) serum biomarkers; (5) neuroimaging; (6) neurophysiologic testing; and (7) multimodal neuroprognostication. This position statement aims to serve as a practical guide to enhance in-hospital care of CA patients and emphasizes the adoption of a systematic, multimodal approach to neuroprognostication. It also highlights evidence gaps.

EEG Correlates of Qualitative Hypermetabolic FDG-PET in Patients With Neurologic Disorders

Background and Objectives

Case reports and case series have described fluorodeoxyglucose (FDG)-PET findings in critically ill patients with rhythmic or periodic EEG patterns, with one reporting that metabolic activity increases with increasing lateralized periodic discharge (LPD) frequency. However, larger studies examining the relationship between FDG-PET hypermetabolism and rhythmic or periodic EEG patterns are lacking. The goal of this study was to investigate the association of FDG-PET hypermetabolism with electroencephalographic features in patients with neurologic disorders.

Methods

This was a single-center, retrospective study of adult patients admitted with acute neurologic symptoms who underwent FDG-PET imaging and EEG monitoring within 24 hours. Subjects were divided into 2 groups based on their FDG-PET metabolism pattern: hypermetabolic activity vs hypometabolic or normal metabolic activity. Chi-square tests and logistic regression were used to determine the relationship of FDG-PET metabolism and EEG findings.

Results

Sixty patients met the inclusion criteria and underwent 63 FDG-PET studies and EEGs. Twenty-seven studies (43%) showed hypermetabolism while 36 studies (57%) showed either hypometabolism or no abnormalities on FDG-PET. Subjects with hypermetabolic FDG-PET were more likely to have electrographic seizures (44% vs 8%, p = 0.001) and LPDs with/without seizures (44% vs 14%, p = 0.007), but not other rhythmic or periodic EEG patterns (lateralized rhythmic delta activity, generalized periodic discharges, or generalized rhythmic delta activity). Subjects with hypermetabolism and LPDs were more likely to have concurrent electrographic seizures (58% vs 0%, p = 0.03), fast activity associated with the discharges (67% vs 0, p = 0.01), or spike morphology (67% vs 0, p = 0.03), compared with subjects with hypometabolic FDG-PET and LPDs.

Discussion

Adults admitted with acute neurologic symptoms who had hypermetabolic FDG-PET were more likely to show electrographic seizures and LPDs, but not other rhythmic or periodic EEG patterns, compared with those with hypometabolic FDG-PET. Subjects with hypermetabolic FDG-PET and LPDs were more likely to have LPDs with concurrent electrographic seizures, LPDs with a spike morphology, and LPDs +F, compared with subjects with hypometabolic FDG-PET.

Brain monitoring after cardiac arrest

PURPOSE OF REVIEW

To describe the available neuromonitoring tools in patients who are comatose after resuscitation from cardiac arrest because of hypoxic-ischemic brain injury (HIBI).

RECENT FINDINGS

Electroencephalogram (EEG) is useful for detecting seizures and guiding antiepileptic treatment. Moreover, specific EEG patterns accurately identify patients with irreversible HIBI. Cerebral blood flow (CBF) decreases in HIBI, and a greater decrease with no CBF recovery indicates poor outcome. The CBF autoregulation curve is narrowed and right-shifted in some HIBI patients, most of whom have poor outcome. Parameters derived from near-infrared spectroscopy (NIRS), intracranial pressure (ICP) and transcranial Doppler (TCD), together with brain tissue oxygenation, are under investigation as tools to optimize CBF in patients with HIBI and altered autoregulation. Blood levels of brain biomarkers and their trend over time are used to assess the severity of HIBI in both the research and clinical setting, and to predict the outcome of postcardiac arrest coma. Neuron-specific enolase (NSE) is recommended as a prognostic tool for HIBI in the current postresuscitation guidelines, but other potentially more accurate biomarkers, such as neurofilament light chain (NfL) are under investigation.

SUMMARY

Neuromonitoring provides essential information to detect complications, individualize treatment and predict prognosis in patients with HIBI.

Cefepime-Induced Neurotoxicity or Nonconvulsive Status Epilepticus (NCSE): A Controversy Revisited

Neurotoxicity is a well-known side effect of cefepime among patients commonly present with altered mental status and typical electroencephalogram (EEG) findings of generalized periodic discharges (GPDs). Some practitioners consider this pattern as encephalopathy and often treat it with the withdrawal of cefepime only, while others are at times concerned with non-convulsive status epilepticus (NCSE) and treat it with antiseizure medications (ASMs) in addition to the withdrawal of cefepime to accelerate the recovery. We present a case series of two patients who developed cefepime-induced altered mental status and EEG findings of GPDs at a rate of 2-2.5 Hz concerning for the ictal-interictal continuum (IIC). Both cases were treated as possible NCSE with ASMs in addition to the withdrawal of cefepime, resulting in different clinical outcomes. The first case showed clinical and EEG improvement shortly after the administration of parenteral benzodiazepines and ASMs. The other case showed electrographic improvement but did not show significant improvement in mentation, and the patient died eventually.

Electroencephalographic patterns in a mechanically ventilated cat with permethrin intoxication

Case summary

A 1-year-old male castrated domestic shorthair cat was presented in a condition of status epilepticus following incidental permethrin spot-on administration by its owner. General anaesthesia and mechanical positive pressure control ventilation were necessary to control the epileptic seizures and a progressive condition of hypoventilation. The cat was managed with an intravenous constant rate infusion of midazolam, propofol and ketamine associated with a low-dose intravenous lipid emulsion. A condition of non-convulsive status epilepticus was detected by serial continuous electroencephalogram (cEEG) monitoring. Initial cEEG showed paroxysmal epileptiform discharges; thus, antiseizure treatment with phenobarbital was added and a bolus of hypertonic saline solution was administered to treat suspected intracranial hypertension. A second cEEG performed 24 h later showed the presence of rare spikes and a burst-suppression pattern, so the decision was made to discontinue propofol. A third cEEG, 72 h post-hospitalisation, showed a normal encephalographic pattern; therefore, anaesthetic drugs were progressively tapered, and the patient was extubated. Five days after admission the cat was discharged on phenobarbital treatment, which was gradually tapered during the following months.

Relevance and novel information

This is the first reported case to describe cEEG monitoring during hospitalisation for feline permethrin intoxication. cEEG should be encouraged in cats with altered mental status that have previously suffered cluster seizures or status epilepticus, which could guide clinicians in the choice of antiseizure drugs.

Heart rate variability for the evaluation of patients with disorders of consciousness

OBJECTIVE

Clinical responsiveness of patients with a Disorder of Consciousness (DoC) correlates to sympathetic/parasympathetic homeostatic balance. Heart Rate Variability (HRV) metrics result in non-invasive proxies of modulation capabilities of visceral states. In this work, our aim was to evaluate whether HRV measures could improve the differential diagnosis between Unresponsive Wakefulness Syndrome (UWS) and Minimally Conscious State (MCS) with respect to multivariate models based on standard clinical electroencephalography (EEG) labeling only in a rehabilitation setting.

METHODS

A prospective observational study was performed consecutively enrolling 82 DoC patients. Polygraphic recordings were performed. HRV-metrics and EEG descriptors derived from the American Clinical Neurophysiology Society's Standardized Critical Care terminology were included. Descriptors entered univariate and then multivariate logistic regressions with the target set to the UWS/MCS diagnosis.

RESULTS

HRV measures resulted significantly different between UWS and MCS patients, with higher values being associated with better consciousness levels. Specifically, adding HRV-related metrics to ACNS EEG descriptors increased the Nagelkerke R² from 0.350 (only EEG descriptors) to 0.565 (HRV-EEG combination) with the outcome set to the consciousness diagnosis.

CONCLUSIONS

HRV changes across the lowest states of consciousness. Rapid changes in heart rate, occurring in better consciousness levels, confirm the mutual correlation between visceral state functioning patterns and consciousness alterations.

SIGNIFICANCE

Quantitative analysis of heart rate in patients with a DoC paves the way for the implementation of low-cost pipelines supporting medical decisions within multimodal consciousness assessments.

EEG: Current relevance and promising quantitative analyses

Electroencephalography (EEG) remains an essential tool, characterized by an excellent temporal resolution and offering a real window on cerebral functions. Surface EEG signals are mainly generated by the postsynaptic activities of synchronously activated neural assemblies. EEG is also a low-cost tool, easy to use at bed-side, allowing to record brain electrical activities with a low number or up to 256 surface electrodes. For clinical purpose, EEG remains a critical investigation for epilepsies, sleep disorders, disorders of consciousness. Its temporal resolution and practicability also make EEG a necessary tool for cognitive neurosciences and brain-computer interfaces. EEG visual analysis is essential in clinical practice and the subject of recent progresses. Several EEG-based quantitative analyses may complete the visual analysis, such as event-related potentials, source localizations, brain connectivity and microstates analyses. Some developments in surface EEG electrodes appear also, potentially promising for long term continuous EEGs. We overview in this article some recent progresses in visual EEG analysis and promising quantitative analyses.

Get a New Perspective on EEG: Convolutional Neural Network Encoders for Parametric t-SNE

t-distributed stochastic neighbor embedding (t-SNE) is a method for reducing high-dimensional data to a low-dimensional representation, and is mostly used for visualizing data. In parametric t-SNE, a neural network learns to reproduce this mapping. When used for EEG analysis, the data are usually first transformed into a set of features, but it is not known which features are optimal. The principle of t-SNE was used to train convolutional neural network (CNN) encoders to learn to produce both a high- and a low-dimensional representation, eliminating the need for feature engineering. To evaluate the method, the Temple University EEG Corpus was used to create three datasets with distinct EEG characters: (1) wakefulness and sleep; (2) interictal epileptiform discharges; and (3) seizure activity. The CNN encoders produced low-dimensional representations of the datasets with a structure that conformed well to the EEG characters and generalized to new data. Compared to parametric t-SNE for either a short-time Fourier transform or wavelet representation of the datasets, the developed CNN encoders performed equally well in separating categories, as assessed by support vector machines. The CNN encoders generally produced a higher degree of clustering, both visually and in the number of clusters detected by k-means clustering. The developed principle is promising and could be further developed to create general tools for exploring relations in EEG data.

Electrocardiographic Changes at the Early Stage of Status Epilepticus: First Insights From the ICTAL Registry

OBJECTIVES

To describe early electrocardiogram (ECG) abnormalities after status epilepticus (SE) and evaluate their association with 90-day neurological outcomes.

DESIGN

Retrospective analysis of a multicenter, national prospective registry between February 2018 and June 2020.

SETTING

Sixteen ICUs in France, IctalGroup Research Network.

PATIENTS

Adults with available ECG performed less than or equal to 24 hours after the onset of SE and less than or equal to 12 hours after its resolution.

INTERVENTION

Double-blinded review of all ECGs was performed by two independent cardiologists. ECGs were categorized as normal/abnormal and then with minor/major early ECG abnormalities according to the Novacode ECG Classification system.

MEASUREMENTS AND MAIN RESULTS

Among 155 critically ill patients with SE, early ECG abnormalities were encountered in 145 (93.5%), categorized as major in 91 of 145 (62.8%). In addition to sinus tachycardia, the main abnormalities were in the ST segment (elevation [16.6%] or depression [17.9%]) or negative T waves (42.1%). Major early ECG abnormalities were significantly associated with respiratory distress and sinus tachycardia at the scene and hyperlactatemia at ICU admission. By multivariable analysis, three variables were significantly associated with 90-day poor outcome: age, preexisting ultimately fatal comorbidity, and cerebral insult as the cause of SE. Early major ECG abnormalities were not independently associated with 90-day functional outcome.

CONCLUSIONS

In our study, early ECG abnormalities in the acute phase of SE were frequent, often unrecognized and were associated with clinical and biological stigma of hypoxemia. Although they were not independently associated with 90-day functional outcome, ECG changes at the early stage of SE should be systematically evaluated.

TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT03457831 .

Systemic inflammatory markers and EEG features of children with FIRES receiving anakinra

In a retrospective case series of 10 children with cryptogenic FIRES, we sought to describe the early clinical course and potential biomarkers following anakinra initiation. Six children achieved anesthetic withdrawal within 3 weeks of therapy and one in week four. Of the available cEEG (six children), CRP (10 children), and serum cytokine (six children) studies, there were temporal changes in highly epileptiform bursts (observed in three children), CRP, IL-6, and IL-10 levels that might parallel clinical progression. These observations may represent candidate biomarkers for monitoring clinical progression and therapeutic interventions including anakinra, which merits further investigation in future studies.

Multimodal Neuromonitoring in Pediatric Neurocritical Care: Current Perspectives

Children with neurological illness in the critical care unit are always at higher risk of developing secondary brain injury (SBI). Brain insult can lead to changes in cerebral autoregulation, intracranial pressure (ICP), cerebral oxygenation, and metabolism. This can cause a raised ICP, cerebral ischemia, hypoxia, excitotoxicity, cellular energy failure, and nonconvulsive status epilepticus. Simultaneous and continuous assessment of these parameters will help to improve patient care and neurological outcomes. Even though clinical examination and neuroimaging can help in the initial diagnosis of the neurological illness, they may not be helpful in continuous monitoring of cerebral pathophysiological changes. The ideal single neuromonitoring device to detect these real-time changes is currently unavailable. However, a range of invasive and noninvasive monitors are available to monitor these cerebral functional parameters. Invasive monitoring techniques include invasive ICP monitoring, cerebral autoregulation monitoring, brain tissue partial oxygen pressure, and cerebral microdialysis. Noninvasive-monitoring techniques include pupillometry, brain and ocular ultrasonography, near-infrared spectroscopy, and electrophysiological monitoring. Multimodal (MM) neuromonitoring involves incorporating these techniques and tools for the early identification and treatment of primary and secondary brain insults. The utility and feasibility of most of these techniques are well described in adult neurocritical care. Even though the evidence on their usage in children is primarily available in pediatric traumatic brain injury, the emerging data help to further expand their utility in pediatric nontraumatic coma. MM neuromonitoring aims to provide clinical and pathophysiological information to the intensivists to improve their understanding of the child's neurological status and to formulate patient-specific treatment approaches.

Continuous electroencephalography in the intensive care unit: A critical review and position statement from an Australian and New Zealand perspective

Objectives

This article aims to critically review the literature on continuous electroencephalography (cEEG) monitoring in the intensive care unit (ICU) from an Australian and New Zealand perspective and provide recommendations for clinicians.

Design and review methods

A taskforce of adult and paediatric neurologists, selected by the Epilepsy Society of Australia, reviewed the literature on cEEG for seizure detection in critically ill neonates, children, and adults in the ICU. The literature on routine EEG and cEEG for other indications was not reviewed. Following an evaluation of the evidence and discussion of controversial issues, consensus was reached, and a document that highlighted important clinical, practical, and economic considerations regarding cEEG in Australia and New Zealand was drafted.

Results

This review represents a summary of the literature and consensus opinion regarding the use of cEEG in the ICU for detection of seizures, highlighting gaps in evidence, practical problems with implementation, funding shortfalls, and areas for future research.

Conclusion

While cEEG detects electrographic seizures in a significant proportion of at-risk neonates, children, and adults in the ICU, conferring poorer neurological outcomes and guiding treatment in many settings, the health economic benefits of treating such seizures remain to be proven. Presently, cEEG in Australian and New Zealand ICUs is a largely unfunded clinical resource that is subsequently reserved for the highest-impact patient groups. Wider adoption of cEEG requires further research into impact on functional and health economic outcomes, education and training of the neurology and ICU teams involved, and securement of the necessary resources and funding to support the service.

An Extraordinary EEG Phenomenon Misdiagnosed as Nonconvulsive Status Epilepticus: Frequent Subclinical Periodic Discharges Terminated by Sudden Auditory Stimuli

Triggering or modulation of seizures and rhythmic EEG patterns by external stimuli are well-known with the most common clinical appearance of stimulus induced periodic discharges (SI- PDs) patterns which are elicited by physical or auditory stimulation. However, stimulus terminated periodic discharges (ST-PDs), in other words, the periodic discharges stopped by external stimuli is an extremely rare electroencephalographic (EEG) finding. We report a 20-year-old woman with a marked psychomotor developmental delay of unknown cause, with frequent EEG patterns of long-lasting (10-60 s) bilateral paroxysmal high-voltage slow waves with occasional spikes, misdiagnosed as non-convulsive status epilepticus. However, no apparent clinical change was noted by the technician, physician, and her mother during these subclinical ictal EEG recordings. Interestingly, however, these epileptic discharges were abruptly interrupted by sudden verbal stimuli on the EEG, repeatedly. Whole exome sequencing and genotyping were performed to investigate possible genetic etiology that revealed two sequence variants, a frameshift variant of CACNA1H NM_021098.3:c.1701del;p.Asp568ThrfsTer15 and a missense variant of GRIN2D NM_000836.4:c.1783A>T;p.Thr595Ser as well as a copy number variant part deletion of ATP6V1A gene arr [hg19]3q13.31(113,499,698_113,543,081)x1 as possible pathogenic candidates. The subclinical periodic discharges terminated by verbal stimuli, is a very rare manifestation and needs particular attention. External modulation of ictal-appearing EEG patterns is important to identify stimulus terminated EEG patterns.

Prevalence, electroclinical spectrum and effect on the outcome of non-convulsive status epilepticus in critically ill patients; the utility of routine electroencephalogram

OBJECTIVES

To highlight the importance of routine electroencephalogram (rEEG) in detecting non-convulsive status epilepticus (NCSE), describing the electroclinical spectrum and effect on outcome in critically ill patients with altered mental status (CIPAMS).

METHODS

This retrospective study was conducted at King Fahd University Hospital. Clinical data and EEG recordings of CIPAMS to rule out NCSE were reviewed. All patients had at least 30 minutes of EEG recording. The Salzburg Consensus criteria (SCC) were applied to diagnose NCSE. The data analysis was performed using SPSS version 22.0. The chi-squared test was used to compare categorical variables such as etiologies, EEG findings, and functional outcomes. Multivariable analysis was performed to identify the predictors of unfavorable outcomes.

RESULTS

A total of 323 CIPAMS referred to rule out NCSE were enrolled (mean age 57.8 ± 20 years). Nonconvulsive status epilepticus was diagnosed in 54 (16.7%) patients. A significant association was found between subtle clinical features and NCSE (P =< 0.01). Acute ischemic stroke (18.5%), sepsis (18.5%), and hypoxic brain injury (22.2%) were the main etiologies. The previous history of epilepsy was significantly associated with NCSE (P = 0.01). Acute stroke, cardiac arrest, mechanical ventilation, and NCSE were statistically associated with unfavorable outcomes. Nonconvulsive status epilepticus was an independent predictor of unfavorable outcomes (P = 0.02, OR = 2.75, CI = 1.16-6.48) during multivariable analysis. Sepsis was associated with higher mortality (P =< 0.01, OR = 2.4, CI = 1.4-4.0).

SIGNIFICANCE

Our study findings suggest that the utility of rEEG in detecting NCSE in CIPAMS should not be underestimated. Important observations further indicate that repeating rEEG is advisable, as this would increase the likelihood of identifying NCSE. Thus, physicians should consider and repeat rEEG when evaluating CIPAMS in order to detect NCSE, which is an independent predictor of unfavorable outcomes. Nonetheless, further studies comparing rEEG and cEEG yields are required to augment the current understanding of the electroclinical spectrum and better describe NCSE in CIPAMS.

[Sequential arterial spin labeling findings of status epilepticus showing generalized periodic discharges on EEG following acute infarction in the right occipital lobe]

In addition to electroencephalogram (EEG), arterial spin labeling (ASL) perfusion images with the dual postlabeling delay (PLD) method are useful for evaluating the hemodynamic state of status epilepticus (SE). A 72-year-old man suffered from an acute infarction in the right occipital lobe, resulting in SE with general periodic discharges on EEG with a higher amplitude on the right side. On ASL, blood flow was increased at a wide area of the right hemisphere centered on this infarct. With improvement of SE, sequential ASL with dual PLD method clearly demonstrated not only the reduction of the signal both in intensity and area but also the decrease of the blood flow velocity.

Glioma genetic profiles associated with electrophysiologic hyperexcitability

Distinct genetic alterations determine glioma aggressiveness, however the diversity of somatic mutations contributing to peritumoral hyperexcitability and seizures is uncertain. In a large cohort of patients with sequenced gliomas (n=1716), we used discriminant analysis models to identify somatic mutation variants associated with electrographic hyperexcitability in a subset with continuous EEG recording (n=206). Overall tumor mutational burdens were similar between patients with and without hyperexcitability. A cross-validated model trained exclusively on somatic mutations classified the presence or absence of hyperexcitability with an overall accuracy of 70.9%, and improved estimates of hyperexcitability and anti-seizure medication failure in multivariate analysis incorporating traditional demographic factors and tumor molecular classifications. Somatic mutation variants of interest were also over-represented in patients with hyperexcitability compared to internal and external reference cohorts. These findings implicate diverse mutations in cancer genes associated with the development of hyperexcitability and response to treatment.

Electroencephalography for prognostication of outcome in adults with severe herpes simplex encephalitis

BACKGROUND

Electroencephalography (EEG) is recommended for the practical approach to the diagnosis and prognosis of encephalitis. We aimed to investigate the prognostic value of standard EEG (_stdEEG) in adult patients with severe herpes simplex encephalitis.

METHODS

We performed a retrospective analysis of consecutive ICU patients with severe herpes simplex encephalitis in 38 French centers between 2006 and 2016. Patients with at least one _stdEEG study performed at ICU admission were included. _stdEEG findings were reviewed independently by two investigators. The association between _stdEEG findings (i.e., background activity, lateralized periodic discharges, seizures/status epilepticus, and reactivity to painful/auditory stimuli) and poor functional outcome, defined by a score on the modified Rankin Scale (mRS) of 3 to 6 (moderate to severe disability or death) at 90 days, were investigated.

RESULTS

We included 214 patients with at least one available _stdEEG study. The first _stdEEG was performed after a median time of one (interquartile range (IQR) 0 to 2) day from ICU admission. At the time of recording, 138 (64.5%) patients were under invasive mechanical ventilation. Lateralized periodic discharges were recorded in 91 (42.5%) patients, seizures in 21 (9.8%) and status epilepticus in 16 (7.5%). In the whole population, reactivity to auditory/noxious stimuli was tested in 140/214 (65.4%) patients and was absent in 71/140 (33.2%) cases. In mechanically ventilated patients, _stdEEG reactivity was tested in 91/138 (65.9%) subjects, and was absent in 53/91 (58.2%) cases. Absence of reactivity was the only independent _stdEEG finding associated with poor functional outcome in the whole population (OR 2.80, 95% CI 1.19 to 6.58) and in the subgroup of mechanically ventilated patients (OR 4.99, 95% CI 1.6 to 15.59). Adjusted analyses for common clinical predictors of outcome and sedation at time of _stdEEG revealed similar findings in the whole population (OR 2.03, 95% CI 1.18 to 3.49) and in mechanically ventilated patients (OR 2.62, 95% CI 1.25 to 5.50).

CONCLUSIONS

Absence of EEG reactivity to auditory/noxious stimuli is an independent marker of poor functional outcome in severe herpes simplex encephalitis.

Repurposing of cholesterol-lowering agents in status epilepticus: A neuroprotective effect of simvastatin

The increase of cholesterol synthesis after a status epilepticus may lead to excitotoxic processes, neuronal loss and favor the appearance of spontaneous epileptic seizures. Lowering cholesterol content could be a neuroprotective strategy. Here, we evaluated the protective effect of simvastatin administrated daily for 14 days, after the induction of a status epilepticus by intrahippocampal injection of kainic acid in mice. The results were compared to those obtained from mice showing a kainic acid-induced status epilepticus, treated daily with a saline solution, and from mice injected with a control phosphate-buffered solution without any status epilepticus. We first assessed the antiseizure effects of simvastatin by performing video-electroencephalographic recordings during the first three hours after kainic acid injection and continuously between the fifteenth and the thirty-first days. Mice treated with simvastatin had significantly fewer generalized seizures during the first three hours without a significant effect on generalized seizures after two weeks. There was a trend for fewer hippocampal electrographic seizures after two weeks. Secondly, we evaluated the neuroprotective and anti-inflammatory effects of simvastatin by measuring the fluorescence of neuronal and astrocyte markers on the thirtieth day after status onset. We found that simvastatin reduced CA1 reactive astrocytosis, demonstrated by a significant 37% decrease in GFAP-positive cells, and that simvastatin prevented the neuronal loss in CA1, demonstrated by a significant 42% increase in the NeuN-positive cells, as compared to the findings in mice with kainic acid-induced status epilepticus treated by a saline solution. Our study confirms the interest of cholesterol-lowering agents, and in particular simvastatin, in status epilepticus and paves the way for a clinical pilot study to prevent neurological sequelae after status epilepticus. This paper was presented at the 8th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures held in September 2022.