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

Electroencephalogram-based machine learning models to predict neurologic outcome after cardiac arrest: A systematic review

AIM OF THE REVIEW

The primary aim of this systematic review was to investigate the most common electroencephalogram (EEG)-based machine learning (ML) model with the highest Area Under Receiver Operating Characteristic Curve (AUC) in two ML categories, conventional ML and Deep Neural Network (DNN), to predict the neurologic outcomes after cardiac arrest; the secondary aim was to investigate common EEG features applied to ML models.

METHODS

Systematic search of medical literature from PubMed and engineering literature from Compendex up to June 2, 2023. One reviewer screened studies that used EEG-based ML models to predict the neurologic outcomes after cardiac arrest. Four reviewers validated that the studies met selection criteria. Nine variables were manually extracted. The top-five common EEG features were calculated. We evaluated each study's risk of bias using the Quality in Prognosis Studies guideline.

RESULTS

Out of 351 identified studies, 17 studies met the inclusion criteria. Random Forest (RF) (n = 7) was the most common ML model in the conventional ML category (n = 11), followed by Convolutional Neural Network (CNN) (n = 4) in the DNN category (n = 6). The AUCs for RF ranged between 0.8 and 0.97, while CNN had AUCs between 0.7 and 0.92. The top-three commonly used EEG features were band power (n = 12), Shannon's Entropy (n = 11), burst-suppression ratio (n = 9).

CONCLUSIONS

RF and CNN were the two most common ML models with the highest AUCs for predicting the neurologic outcomes after cardiac arrest. Using a multimodal model that combines EEG features and electronic health record data may further improve prognostic performance.

Prognostic value of Salzburg nonconvulsive status epilepticus criteria: The SACE score

OBJECTIVE

This study was undertaken to investigate the association between the Salzburg nonconvulsive status epilepticus (NCSE) criteria and in-hospital outcome, to determine the predictive accuracy of the Status Epilepticus Severity Score (STESS), modified STESS (mSTESS), Epidemiology-Based Mortality Score in Status Epilepticus (EMSE), and END-IT (encephalitis, NCSE, diazepam resistance, imaging features, and tracheal intubation) in NCSE patients, and to develop a new prognostic score specifically designed for NCSE patients.

METHODS

Clinical and electroencephalographic (EEG) data of adult patients treated for NCSE from 2020 to 2023 were retrospectively assessed. Age, sex, modified Rankin Scale at admission, comorbidities, history of seizures, etiology, status epilepticus type, and outcome were collected from the patients' digital charts. EEG data were assessed and categorized applying the Salzburg NCSE criteria. In-hospital death was defined as the primary outcome.

RESULTS

A total of 116 NCSE patients were included. Multivariable logistic regression revealed that Salzburg NCSE criterion A2 (ictal morphological, spatial, and temporal evolution) was associated with in-hospital survival. The best STESS cutoff was ≥4 (sensitivity = .62, specificity = .69, accuracy = 67%). mSTESS ≥ 5 reached a sensitivity of .68, a specificity of .57, and an overall accuracy of 60%, EMSE ≥ 64 a sensitivity of .82, a specificity of .39, and an overall accuracy of 52%, and END-IT ≥ 3 a sensitivity of .65, a specificity of .44, and an overall accuracy of 50%. Through a hypothesis-generating approach, we developed the SACE score, which integrates EEG features (criterion A2) with patient age (with a 75-year cutoff), history of seizures, and level of consciousness. With a cutoff of ≥3, it had a sensitivity of .77, a specificity of .74, and an overall accuracy of 76%, performing better than other prognostic scores.

SIGNIFICANCE

We developed a new user-friendly scoring system, the SACE score, which integrates EEG features with other established outcome-related variables assessable in early stages, to assist neurologists and neurointensivists in making more tailored prognostic decisions for NCSE patients.

Postoperative hypernatremia is associated with worse brain injuries on EEG and MRI following pediatric cardiac surgery

Objectives

Dysnatremia is a common electrolyte disturbance after cardiopulmonary bypass (CPB) surgery for congenital heart disease (CHD) and a known risk factor for adverse neurological events and clinical outcomes. The objective of this study was to evaluate the association of dysnatremia with worse abnormal EEG patterns, brain injuries detected by magnetic resonance imaging (MRI) and early adverse outcomes.

Methods

We monitored continuous EEG in 340 children during the initial 48 h following cardiac surgery. Demographics and clinical characteristics were recorded. Sodium concentrations were measured in the arterial blood gas analysis every 6 h. Hyponatremia and hypernatremia were classified by the average of sodium concentrations over 48 h. Postoperative cerebral MRI was performed before hospital discharge.

Results

In our patient cohort, dysnatremia was present in 46 (13.5%) patients. Among them, hyponatremia occurred in 21 (6.2%) and hypernatremia in 25 (7.4%). When compared to patients with normonatremia, hyponatremia was not associated with EEG abnormalities and early adverse outcomes (Ps ≥ .14). In hypernatremia group, the CPB time was significantly longer and more frequent use of DHCA (Ps ≤ .049). After adjusting for time, CPB time and the use of DHCA, hypernatremia was significantly associated with worse EEG abnormalities (including background, seizures and pathological delta brushes), more severe brain injuries on MRI (Ps ≤ .04) and trended to be associated with longer postoperative mechanical ventilation time (P = .06).

Conclusion

Hypernatremia and hyponatremia were common in children after cardiac surgery. Hypernatremia, but not hyponatremia, was significantly associated with worse EEG abnormalities and more severe brain injuries on MRI and extended postoperative mechanical ventilation time.

Rapid modeling of an ultra-rare epilepsy variant in wild-type mice by in utero prime editing

Generating animal models for individual patients within clinically-useful timeframes holds great potential toward enabling personalized medicine approaches for genetic epilepsies. The ability to rapidly incorporate patient-specific genomic variants into model animals recapitulating elements of the patient's clinical manifestations would enable applications ranging from validation and characterization of pathogenic variants to personalized models for tailoring pharmacotherapy to individual patients. Here, we demonstrate generation of an animal model of an individual epilepsy patient with an ultra-rare variant of the NMDA receptor subunit GRIN2A, without the need for germline transmission and breeding. Using in utero prime editing in the brain of wild-type mice, our approach yielded high in vivo editing precision and induced frequent, spontaneous seizures which mirrored specific elements of the patient's clinical presentation. Leveraging the speed and versatility of this approach, we introduce PegAssist, a generalizable workflow to generate bedside-to-bench animal models of individual patients within weeks. The capability to produce individualized animal models rapidly and cost-effectively will reduce barriers to access for precision medicine, and will accelerate drug development by offering versatile in vivo platforms to identify compounds with efficacy against rare neurological conditions.

Combination strategy for prognostication in patients undergoing post-resuscitation care after cardiac arrest

This study investigated the prognostic performance of combination strategies using a multimodal approach in patients treated after cardiac arrest. Prospectively collected registry data were used for this retrospective analysis. Poor outcome was defined as a cerebral performance category of 3-5 at 6 months. Predictors of poor outcome were absence of ocular reflexes (PR/CR) without confounding factors, a highly malignant pattern on the most recent electroencephalography, defined as suppressed background with or without periodic discharges and burst-suppression, high neuron-specific enolase (NSE) after 48 h, and diffuse injury on imaging studies (computed tomography or diffusion-weighted imaging [DWI]) at 72-96 h. The prognostic performances for poor outcomes were analyzed for sensitivity and specificity. A total of 130 patients were included in the analysis. Of these, 68 (52.3%) patients had poor outcomes. The best prognostic performance was observed with the combination of absent PR/CR, high NSE, and diffuse injury on DWI [91.2%, 95% confidence interval (CI) 80.7-97.1], whereas the combination strategy of all available predictors did not improve prognostic performance (87.8%, 95% CI 73.8-95.9). Combining three of the predictors may improve prognostic performance and be more efficient than adding all tests indiscriminately, given limited medical resources.

Prognosis of comatose patients with reduced EEG montage by combining quantitative EEG features in various domains

Objective

As the frontoparietal network underlies recovery from coma, a limited frontoparietal montage was used, and the prognostic values of EEG features for comatose patients were assessed.

Methods

Collected with a limited frontoparietal EEG montage, continuous EEG recordings of 81 comatose patients in ICU were used retrospectively. By the 60-day Glasgow outcome scale (GOS), the patients were dichotomized into favorable and unfavorable outcome groups. Temporal-, frequency-, and spatial-domain features were automatically extracted for comparison. Partial correlation analysis was applied to eliminate redundant factors, and multiple correspondence analysis was used to explore discrimination between groups. Prognostic characteristics were calculated to assess the performance of EEG feature-based predictors established by logistic regression. Analyses were performed on all-patients group, strokes subgroup, and traumatic brain injury (TBI) subgroup.

Results

By analysis of all patients, raised burst suppression ratio (BSR), suppressed root mean square (RMS), raised power ratio of β to α rhythm (β/α), and suppressed phase-lag index between F3 and P4 (PLI [F3, P4]) were associated with unfavorable outcome, and yielded AUC of 0.790, 0.811, 0.722, and 0.844, respectively. For the strokes subgroup, the significant variables were BSR, RMS, θ/total, θ/δ, and PLI (F3, P4), while for the TBI subgroup, only PLI (F3, P4) was significant. BSR combined with PLI (F3, P4) gave the best predictor by cross-validation analysis in the all-patients group (AUC = 0.889, 95% CI: 0.819-0.960).

Conclusion

Features extracted from limited frontoparietal montage EEG served as valuable coma prognostic tools, where PLI (F3, P4) was always significant. Combining PLI (F3, P4) with features in other domains may achieve better performance.

Significance

A limited-montage EEG coupled with an automated algorithm is valuable for coma prognosis.

Added value of advanced workup after the first seizure: A 7-year cohort study

OBJECTIVE

This study was undertaken to establish whether advanced workup including long-term electroencephalography (LT-EEG) and brain magnetic resonance imaging (MRI) provides an additional yield for the diagnosis of new onset epilepsy (NOE) in patients presenting with a first seizure event (FSE).

METHODS

In this population-based study, all adult (≥16 years) patients presenting with FSE in the emergency department (ED) between March 1, 2010 and March 1, 2017 were assessed. Patients with obvious nonepileptic or acute symptomatic seizures were excluded. Routine EEG, LT-EEG, brain computed tomography (CT), and brain MRI were performed as part of the initial workup. These examinations' sensitivity and specificity were calculated on the basis of the final diagnosis after 2 years, along with the added value of advanced workup (MRI and LT-EEG) over routine workup (routine EEG and CT).

RESULTS

Of the 1010 patients presenting with FSE in the ED, a definite diagnosis of NOE was obtained for 501 patients (49.6%). Sensitivity of LT-EEG was higher than that of routine EEG (54.39% vs. 25.5%, p < .001). Similarly, sensitivity of MRI was higher than that of CT (67.98% vs. 54.72%, p = .009). Brain MRI showed epileptogenic lesions in an additional 32% compared to brain CT. If only MRI and LT-EEG were considered, five would have been incorrectly diagnosed as nonepileptic (5/100, 5%) compared to patients with routine EEG and MRI (25/100, 25%, p = .0001). In patients with all four examinations, advanced workup provided an overall additional yield of 50% compared to routine workup.

SIGNIFICANCE

Our results demonstrate the remarkable added value of the advanced workup launched already in the ED for the diagnosis of NOE versus nonepileptic causes of seizure mimickers. Our findings suggest the benefit of first-seizure tracks or even units with overnight EEG, similar to stroke units, activated upon admission in the ED.

Common Data Elements for Disorders of Consciousness: Recommendations from the Electrophysiology Working Group

BACKGROUND

Electroencephalography (EEG) has long been recognized as an important tool in the investigation of disorders of consciousness (DoC). From inspection of the raw EEG to the implementation of quantitative EEG, and more recently in the use of perturbed EEG, it is paramount to providing accurate diagnostic and prognostic information in the care of patients with DoC. However, a nomenclature for variables that establishes a convention for naming, defining, and structuring data for clinical research variables currently is lacking. As such, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups composed of experts in the field to construct common data elements (CDEs) to provide recommendations for DoC, with the main goal of facilitating data collection and standardization of reporting. This article summarizes the recommendations of the electrophysiology DoC working group.

METHODS

After assessing previously published pertinent CDEs, we developed new CDEs and categorized them into "disease core," "basic," "supplemental," and "exploratory." Key EEG design elements, defined as concepts that pertained to a methodological parameter relevant to the acquisition, processing, or analysis of data, were also included but were not classified as CDEs.

RESULTS

After identifying existing pertinent CDEs and developing novel CDEs for electrophysiology in DoC, variables were organized into a framework based on the two primary categories of resting state EEG and perturbed EEG. Using this categorical framework, two case report forms were generated by the working group.

CONCLUSIONS

Adherence to the recommendations outlined by the electrophysiology working group in the resting state EEG and perturbed EEG case report forms will facilitate data collection and sharing in DoC research on an international level. In turn, this will allow for more informed and reliable comparison of results across studies, facilitating further advancement in the realm of DoC research.

Measurement of thalamus and cortical damages in hypoxic ischemic encephalopathy

Background

The thalamic gray-white matter ratios (GWRs) on CT and quantitative suppression ratios (SRs) of background activities on EEG may reflect damages in the thalamus and cerebral hemispheres in patients with hypoxic-ischemic encephalopathy (HIE).

Methods

The inclusion criteria were (1) cardiac arrest patients over the age of 20 years from March 2010 to March 2020, and (2) patients who had both EEG and brain CT within 7 days after cardiac arrest. The thalamic GWRs were semi-quantitatively measured by using the region of interest (ROI). SRs of background were analyzed with the installed software (Persyst® v13) in EEG machine.

Results

175 patients were included among 686 patients with HIE and the thalamic GWRs of 168 patients were successfully measured. 155 patients (89 %) showed poor outcomes. The poor outcome group revealed not only higher SRs, but also lower thalamic GWRs. The thalamic GWRs showed a negative correlation to the SRs (ρ (rho) = -0.36, p < 0.0001 for right side, ρ (rho) = -0.31, p < 0.0001 for left side). The good outcome group showed neither beyond the cut-off values of thalamic GWRs nor SRs [40 % (59/148) VS 0 % (0/20) in right side, p = 0.0005 %, and 28 % (42/148) VS 0 % (0/20) in left side, p = 0.0061].

Conclusion

The thalamic GWRs and SRs may reflect the damage in the thalamus and cerebral hemispheres in patients with HIE. Insults in the thalamocortical circuit (TCC) or the thalamus might be responsible for the poor outcome.

Practice Standards for the Use of Multimodality Neuromonitoring: A Delphi Consensus Process

OBJECTIVES

To address areas in which there is no consensus for the technologies, effort, and training necessary to integrate and interpret information from multimodality neuromonitoring (MNM).

DESIGN

A three-round Delphi consensus process.

SETTING

Electronic surveys and virtual meeting.

SUBJECTS

Participants with broad MNM expertise from adult and pediatric intensive care backgrounds.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Two rounds of surveys were completed followed by a virtual meeting to resolve areas without consensus and a final survey to conclude the Delphi process. With 35 participants consensus was achieved on 49% statements concerning MNM. Neurologic impairment and the potential for MNM to guide management were important clinical considerations. Experts reached consensus for the use of MNM-both invasive and noninvasive-for patients in coma with traumatic brain injury, aneurysmal subarachnoid hemorrhage, and intracranial hemorrhage. There was consensus that effort to integrate and interpret MNM requires time independent of daily clinical duties, along with specific skills and expertise. Consensus was reached that training and educational platforms are necessary to develop this expertise and to provide clinical correlation.

CONCLUSIONS

We provide expert consensus in the clinical considerations, minimum necessary technologies, implementation, and training/education to provide practice standards for the use of MNM to individualize clinical care.

Machine Learning and Artificial Intelligence Applications to Epilepsy: a Review for the Practicing Epileptologist

PURPOSE OF REVIEW

Machine Learning (ML) and Artificial Intelligence (AI) are data-driven techniques to translate raw data into applicable and interpretable insights that can assist in clinical decision making. Some of these tools have extremely promising initial results, earning both great excitement and creating hype. This non-technical article reviews recent developments in ML/AI in epilepsy to assist the current practicing epileptologist in understanding both the benefits and limitations of integrating ML/AI tools into their clinical practice.

RECENT FINDINGS

ML/AI tools have been developed to assist clinicians in almost every clinical decision including (1) predicting future epilepsy in people at risk, (2) detecting and monitoring for seizures, (3) differentiating epilepsy from mimics, (4) using data to improve neuroanatomic localization and lateralization, and (5) tracking and predicting response to medical and surgical treatments. We also discuss practical, ethical, and equity considerations in the development and application of ML/AI tools including chatbots based on Large Language Models (e.g., ChatGPT). ML/AI tools will change how clinical medicine is practiced, but, with rare exceptions, the transferability to other centers, effectiveness, and safety of these approaches have not yet been established rigorously. In the future, ML/AI will not replace epileptologists, but epileptologists with ML/AI will replace epileptologists without ML/AI.

Tagging EEG features within exam reports to quickly generate databases for research purposes

OBJECTIVE

assess the effectiveness of a new method for classifying EEG recording features through the use of tags within reports. We present feature prevalence in a sample of patients with toxic-metabolic encephalopathy and discuss the advantages of this approach over existing classification systems.

METHODS

during EEG report creation, tags reflecting background activity, epileptiform features and periodic discharges were selected according to the findings of each recording. Reports including the tags have been collected and processed by the EEG report parser script written in PHP language. The resulting spreadsheet was analysed to calculate the prevalence and type of EEG features in a sample group of patients with toxic-metabolic encephalopathy.

RESULTS

tag checking and extraction were very little time-consuming processes. Considering 5784 EEG recordings performed either in inpatients or outpatients over 2 years, toxic-metabolic aetiology was tagged in 218 (3.8 %). The most frequent background feature was severe slowing (5-6 Hz frequency), occurring in 79 (36.2 %). Epileptiform abnormalities were rare, reaching a maximum of 10 (4.6 %). Triphasic waves were tagged in 43 (19.7 %) recordings.

CONCLUSIONS

tagging and parsing processes are very fast and integrated into the daily routine. Sample analysis in patients with toxic-metabolic encephalopathies showed EEG slowing as the prevalent feature, while triphasic waves occurred in a minority of recordings. Existing software such as "SCORE" (Holberg EEG) requires the replacement of the currently used software for EEG reporting, minimizing additional costs and training. EEG Report Parser is free and open-source software, so it can be freely adopted, modified and redistributed, allowing further improvement and adaptability.

The predictive value of EEG reactivity by electrical stimulation and quantitative analysis in critically ill patients with large hemispheric infarction

PURPOSE

The intensive care of critically ill patients with large hemispheric infarction improves the survival rate. However, established prognostic markers for neurological outcome show variable accuracy. We aimed to assess the value of electrical stimulation and quantitative analysis of EEG reactivity for early prognostication in this critically ill population.

MATERIALS AND METHODS

We prospectively enrolled consecutive patients between January 2018 and December 2021. EEG reactivity was randomly performed by pain or electrical stimulation via visual and quantitative analysis. Neurological outcome within 6-month was dichotomized as good (modified Rankin Scale, mRS 0-3) or poor (mRS 4-6).

RESULTS

Ninety-four patients were admitted, and 56 were included in the final analysis. EEG reactivity using electrical stimulation was superior to pain stimulation for good outcome prediction (visual analysis: AUC 0.825 vs. 0.763, P = 0.143; quantitative analysis: AUC 0.931 vs. 0.844, P = 0.058). The AUC of EEG reactivity by pain stimulation with visual analysis was 0.763, which increased to 0.931 by electrical stimulation with quantitative analysis (P = 0.006). When using quantitative analysis, the AUC of EEG reactivity increased (pain stimulation 0.763 vs. 0.844, P = 0.118; electrical stimulation 0.825 vs. 0.931, P = 0.041).

CONCLUSION

EEG reactivity by electrical stimulation and quantitative analysis seems a promising prognostic factor in these critical patients.

Effects of Sodium Lactate Infusion in Two Girls with Glucose Transporter 1 Deficiency Syndrome

BACKGROUND

Glucose is an important fuel for the brain. In glucose transporter 1 deficiency syndrome (GLUT1DS), the transport of glucose across the blood-brain barrier is limited. Most individuals with GLUT1DS present with developmental problems, epilepsy, and (paroxysmal) movement disorders, and respond favorably to the ketogenic diet. Similar to ketones, lactate is an alternative energy source for the brain. The aim of this study is to investigate whether intravenous infusion of sodium lactate in children with GLUT1DS has beneficial effects on their epilepsy.

METHODS

We performed a proof of principle study with two subjects with GLUT1DS who were not on a ketogenic diet and suffered from absence epilepsy. After overnight fasting, sodium lactate (600 mmol/L) was infused during 120 minutes, under video electroencephalographic (EEG) recording and monitoring of serum lactate, glucose, electrolytes, and pH. Furthermore, the EEGs were compared with pre-/postprandial EEGs of both subjects, obtained shortly before the study.

RESULTS

Fasting EEGs of both subjects showed frequent bilateral, frontocentral polyspike and wave complexes. In one subject, no more epileptic discharges were seen postprandially and after the start of lactate infusion. The EEG of the other subject did not change, neither postprandially nor after lactate infusion. Serum pH, lactate, and sodium changed temporarily during the study.

CONCLUSION

This study suggests that sodium lactate infusion is possible in individuals with GLUT1DS, and may have potential therapeutic effects. Cellular abnormalities, beyond neuronal energy failure, may contribute to the underlying disease mechanisms of GLUT1DS, explaining why not all individuals respond to the supplementation of alternative energy sources.

Periodic discharges plus fast activity on electroencephalogram predict worse outcomes in poststroke epilepsy

OBJECTIVE

Postseizure functional decline is a concern in poststroke epilepsy (PSE). However, data on electroencephalogram (EEG) markers associated with functional decline are scarce. Thus, we investigated whether periodic discharges (PDs) and their specific characteristics are associated with functional decline in patients with PSE.

METHODS

In this observational study, patients admitted with seizures of PSE and who had scalp EEGs were included. The association between the presence or absence of PDs and postseizure short-term functional decline lasting 7 days after admission was investigated. In patients with PD, EEG markers were explored for risk stratification of short-term functional decline, according to the American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology. The association between EEG markers and imaging findings and long-term functional decline at discharge and 6 months after discharge, defined as an increase in the modified Rankin Scale score compared with the baseline, was evaluated.

RESULTS

In this study, 307 patients with PSE (median age = 75 years, range = 35-97 years, 64% males; hemorrhagic stroke, 47%) were enrolled. Compared with 247 patients without PDs, 60 patients with PDs were more likely to have short-term functional decline (12 [20%] vs. 8 [3.2%], p < .001), with an adjusted odds ratio (OR) of 4.26 (95% confidence interval [CI] = 1.44-12.6, p = .009). Patients with superimposed fast-activity PDs (PDs+F) had significantly more localized (rather than widespread) lesions (87% vs. 58%, p = .003), prolonged hyperperfusion (100% vs. 62%, p = .023), and a significantly higher risk of short-term functional decline than those with PDs without fast activity (adjusted OR = 22.0, 95% CI = 1.87-259.4, p = .014). Six months after discharge, PDs+F were significantly associated with long-term functional decline (adjusted OR = 4.21, 95% CI = 1.27-13.88, p = .018).

SIGNIFICANCE

In PSE, PDs+F are associated with sustained neuronal excitation and hyperperfusion, which may be a predictor of postseizure short- and long-term functional decline.

The Long-Term Use of Diagnostic Subdural Electroencephalogram Electrodes and Subdural Hematoma: A Prospective Cohort Study

OBJECTIVES

Seizures and status epilepticus (SE) are frequent complications of acute subdural hematoma (aSDH) associated with increased morbidity and mortality. Therefore, we aimed to evaluate whether invasive subdural electroencephalogram recording leads to earlier seizure detection and treatment initiation in patients with aSDH.

DESIGN

Prospective, single-center, cohort trial.

SETTING

Neurologic and neurosurgical ICUs of one academic hospital in Germany.

PATIENTS

Patients with aSDH undergoing surgical treatment. In total, 76 patients were enrolled in this study, 31 patients (40.8%) were assigned to the invasive electroencephalogram (iEEG) monitoring group and 45 patients (59.2%) to control group.

INTERVENTIONS

The electrode group was implanted with a subdural strip electrode providing up to 7 days of real-time electroencephalogram recording in the neurointensive care unit, whereas the control group received regular normal surface electroencephalograms during the 7-day period. The primary outcomes were the prevalence and time to seizures and SE occurrence. Secondary outcomes included neurologic outcomes assessed using the Glasgow Outcome Scale (GOS) at discharge and 6-month follow-up and the prevalence of focal structural epilepsy within 2 years after discharge.

MEASUREMENTS AND MAIN RESULTS

The trial was stopped after a study committee meeting when the prespecified criteria were met. The iEEG and control groups were well-matched for clinical characteristics at admission. Frequencies of seizures and SE detection were significantly higher in the iEEG group than in the control group (61% vs 15.6%; p < 0.001 and 38.7% vs 11.1%; p = 0.005). Time to seizure and SE detection was significantly earlier (median 29.2 vs 83.8 hr; p = 0.018 and 17.2 vs 83.8 hr; p = 0.033) in the iEEG group than in the control group. Favorable outcomes (GOS 4-5) were more frequently achieved in the iEEG group than in the control group (58% vs 31%; p = 0.065). No significant differences were detected in long-term mortality or post-traumatic epilepsy.

CONCLUSIONS

Invasive subdural electroencephalogram monitoring is valuable and safe for early seizure/SE detection and treatment and might improve outcomes in the neurocritical care of patients with aSDH.

SREDA: An Uncommon and Misleading EEG Rhythm

Subclinical Rhythmic Electroencephalographic Discharges of Adults (SREDA) is a benign EEG variant characterized by sharply contoured rhythmic theta activity occurring bilaterally with maximum activity over the parietal or the posterior head region. These paroxysms are not associated with any objective or subjective clinical manifestations. SREDA, the rarest and last reported benign EEG pattern with no known clinical significance yet, is detailed in this case report. We provide the case of a gentleman with epilepsy who underwent vEEG recording in our lab. The described case is interesting due to its EEG characteristics as well as its clinical picture, which misled us for at least a while. It provides an illustration of how over interpretation of normal EEG patterns may result in an incorrect diagnosis.

Risk assessment of long-term epilepsy after de novo status epilepticus with clinical and electroencephalographic biomarkers: The AFTER score

BACKGROUND

The risk of developing epilepsy after de novo status epilepticus (SE) is nonnegligible. The individualized management of patients with high risk of subsequent epilepsy could improve long-term quality of life and cognitive impairment. We aimed to ascertain potential biomarkers of subsequent epilepsy and to construct a scoring system possessing predictive value for the diagnosis of post-SE epilepsy during follow-up.

METHODS

The study data were obtained from a prospective registry of all SE episodes occurring in patients over 16 years attended in our tertiary center from February 2011 to April 2022. Clinical data, electroencephalography findings, treatment, and long-term clinical data were prospectively recorded. We selected SE patients at risk of developing epilepsy (acute symptomatic and cryptogenic etiologies with no previous history of epilepsy) and analyzed the risk of developing subsequent epilepsy.

RESULTS

We included 230 patients. Median age was 65 years ± 16.9 SD and 112/230 (48.7 %) were women. One-hundred ninety-eight patients (86.1 %) had an acute symptomatic SE, whereas 32 patients (13.9 %) presented with a cryptogenic SE. A total of 55 patients (23.9 %) developed an unprovoked remote seizure and were diagnosed with epilepsy. After adjusting for identifiable confounders in a multivariable Cox regression analysis cryptogenic etiology (HR 2.24 [1.13-4.46], p = 0.022), first-line treatment initiation ≥1 h (HR 2.12 [1.03-4.36], p = 0.041], RDA/LPD/GPD EEG patterns (HR 1.88 [1.07-3.32], p = 0.028), and super-refractoriness (HR 2.90 [1.40-5.99], p = 0.004) emerged as independent predictors of post-SE epilepsy. Based on these findings, we constructed the AFTER score (1 point for each item) with a robust capability to predict post-SE epilepsy at 5 years (AUC 74.3 %, 95 %CI 64.3-84.3 %, p < 0.001).

CONCLUSIONS

The AFTER score is a robust predictor of the development of epilepsy after new onset SE using clinical and electroencephalographic biomarkers (such as etiology, time to first-line treatment initiation, EEG pattern and super-refractoriness). Prospective studies are warranted to validate the score in other populations.

Amplitude Integrated Electroencephalography: Simulated Assessment of Neonatal Seizure Detection in PICU Patients

OBJECTIVES

Amplitude integrated electroencephalography (aEEG) is a mainstay of care in neonatal ICUs; however, knowledge gaps exist in relation to its accuracy for identifying seizures in older children. We aimed to review the diagnostic accuracy of existing neonatal seizure detection criteria for seizure detection in older children in hospital.

DESIGN

Retrospective study.

SETTING

PICU/Neurophysiology Department in Dublin.

PATIENTS

One hundred twenty patients (2 mo to 16 yr old) were chosen from a database of formal 10-20 system, 21-lead electroencephalography recordings (2012-2020), comprising 30 studies with seizures, 90 without.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Electroencephalography studies containing electrographic seizures (ESzs) were annotated to describe number, duration, distribution, and spread. Two-channel aEEG (using leads C3-P3, C4-P4) recordings were generated and independently reviewed by a professional specialist in clinical neurophysiology blinded to outcome and without reference to the raw electroencephalography trace. Logistic regression was used to identify factors associated with correct seizure identification on aEEG. Median patient age was 6.1 years. Abnormal recordings featured 123 seizures. Status epilepticus (SE) was evident by electroencephalography in 10 cases. Using neonatal criteria, aEEG had a sensitivity of 70% and negative predictive value of 90% for identifying any ESz. Accurate detection of individual seizures was diminished when seizures were very short or occurred during waking. Sensitivity for individual seizures was 81% when seizures less than 1 minute were excluded. aEEG correctly identified SE in 70% of the 10 cases, although ESz were confirmed to be present in 80% of this subpopulation.

CONCLUSIONS

aEEG criteria for neonatal seizure identification can be applied with caution to older children and should be supplemented by formal electroencephalography. Seizure identification is better for longer seizures and those arising from sleep. SE is not always recognized by aEEG among older children.

Review of Noninvasive Neuromonitoring Modalities in Children II: EEG, qEEG

Critically ill children with acute neurologic dysfunction are at risk for a variety of complications that can be detected by noninvasive bedside neuromonitoring. Continuous electroencephalography (cEEG) is the most widely available and utilized form of neuromonitoring in the pediatric intensive care unit. In this article, we review the role of cEEG and the emerging role of quantitative EEG (qEEG) in this patient population. cEEG has long been established as the gold standard for detecting seizures in critically ill children and assessing treatment response, and its role in background assessment and neuroprognostication after brain injury is also discussed. We explore the emerging utility of both cEEG and qEEG as biomarkers of degree of cerebral dysfunction after specific injuries and their ability to detect both neurologic deterioration and improvement.

Cardiac Abnormalities in Refractory Status Epilepticus-an Exploratory Study

Background and Purpose

Cardiac abnormalities have been reported during ongoing seizures and refractory status epilepticus (RSE). Reduced heart rate variability (HRV) and cardiac arrhythmias may contribute to sudden unexpected death in epilepsy. We sought to explore the utility of electrocardiographic and echocardiographic changes in patients with RSE prognosis and functional outcome.

Methods

Patients of RSE underwent electrocardiogram (ECG), holter, troponin-I (Trop I), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and 2-dimensional echocardiogram (2D Echo) along with continuous electroencephalogram in first 24 hours and admission. Heart rate changes/arrhythmias, corrected QT interval (QTc) and HRV, ventricular dysfunction or regional motion wall abnormality were studied on 2D Echo. These parameters were also at baseline, at discharge or death and 30 days post discharge.

Results

This prospective observational study conducted over 18 months enrolled 20 patients with RSE, fulfilling the inclusion criteria. Mean age was 47.75±17.2 years with male: female ratio of 1:1. Mean time to presentation from seizure onset was 8.80±7.024 hours. Central nervous system infection (35.0%), autoimmune encephalitis (20.0%) and cerebrovascular disease (20.0%) were the common etiologies. Amongst cardiac injury markers, cardiac enzymes and QTc prolongation were the commonest abnormalities in RSE. Both reduced HRV and presence of cardiac injury markers had significant correlation with poor outcome along with poor Glasgow coma scale (GCS) and modified Rankin scale (mRS) at presentation, and presence of non convulsive status epilepticus (NCSE).

Conclusions

Presence of poor GCS, poor mRS, markers of cardiac injury, reduced HRV and occurrence of NCSE have a consistent correlation with mortality and poor clinical outcome. Therefore, routine assessment of cardiac abnormalities using affordable, easily accessible and non-invasive tools such as ECG, 2D Echo, holter NT-proBNP and Trop I is recommended in RSE patients.

Subclinical epileptiform activity and sleep disturbances in Alzheimer's disease

INTRODUCTION

Subclinical epileptiform activity (SEA) and sleep disturbances are frequent in Alzheimer's disease (AD). Both have an important relation to cognition and potential therapeutic implications. We aimed to study a possible relationship between SEA and sleep disturbances in AD.

METHODS

In this cross-sectional study, we performed a 24-h ambulatory EEG and polysomnography in 48 AD patients without diagnosis of epilepsy and 34 control subjects.

RESULTS

SEA, mainly detected in frontotemporal brain regions during N2 with a median of three spikes/night [IQR1-17], was three times more prevalent in AD. AD patients had lower sleep efficacy, longer wake after sleep onset, more awakenings, more N1%, less REM sleep and a higher apnea-hypopnea index (AHI) and oxygen desaturation index (ODI). Sleep was not different between AD subgroup with SEA (AD-Epi+) and without SEA (AD-Epi-); however, compared to controls, REM% was decreased and AHI and ODI were increased in the AD-Epi+ subgroup.

DISCUSSION

Decreased REM sleep and more severe sleep-disordered breathing might be related to SEA in AD. These results could have diagnostic and therapeutic implications and warrant further study at the intersection between sleep and epileptiform activity in AD.

Post-hypoxic status epilepticus - A distinct subtype of status epilepticus with poor prognosis

OBJECTIVE

To evaluate the clinical outcome of patients with possible and definitive post-hypoxic status epilepticus (SE) and to describe the SE types in patients with definitive post-hypoxic SE.

METHODS

Patients with definitive or possible SE resulting from hypoxic brain injury after cardiac arrest (CA) were prospectively recruited. Intermittent EEG was used for the diagnosis of SE according to clinical practice. Two raters blinded to outcome analyzed EEGs retrospectively for possible and definitive SE patterns and background features (frequency, continuity, reactivity, and voltage). Definitive SE was classified according to semiology (ILAE). Mortality and Cerebral Performance Categories (CPC) score were evaluated 1 month after CA.

RESULTS

We included 64 patients of whom 92% died. Among the survivors, only one patient had a good neurological outcome (CPC 1). No patient survived with a burst suppression pattern, low voltage, or electro-cerebral silence in any EEG. Possible or definitive SE was diagnosed in a median of 47 h (IQR 39-72 h) after CA. EEG criteria for definitive electrographic SE were fulfilled in 39% of patients; in 38% - for electroclinical SE and in 23% - for ictal-interictal continuum (IIC). The outcome did not differ significantly between the three groups. The only patient with good functional outcome belonged to the IIC group. Comatose non-convulsive SE (NCSE) without subtle motor phenomenon occurred in 20% of patients with definitive electrographic SE and outcome was similar to other types of SE.

SIGNIFICANCE

Possible or definitive SE due to hypoxic brain injury is associated with poor prognosis. The outcome of patients with electrographic SE, electroclinical SE, and IIC did not differ significantly. Outcome was similar in patients with definitive electrographic SE with and without prominent motor features.

Brain microstate spatio-temporal dynamics as a candidate endotype of consciousness

Consciousness can be defined as a phenomenological experience continuously evolving. Current research showed how conscious mental activity can be subdivided into a series of atomic brain states converging to a discrete spatiotemporal pattern of global neuronal firing. Using the high temporal resolution of EEG recordings in patients with a severe Acquired Brain Injury (sABI) admitted to an Intensive Rehabilitation Unit (IRU), we detected a novel endotype of consciousness from the spatiotemporal brain dynamics identified via microstate analysis. Also, we investigated whether microstate features were associated with common neurophysiological alterations. Finally, the prognostic information comprised in such descriptors was analysed in a sub-cohort of patients with prolonged Disorder of Consciousness (pDoC). Occurrence of frontally-oriented microstates (C microstate), likelihood of maintaining such brain state or transitioning to the C topography and complexity were found to be indicators of consciousness presence and levels. Features of left-right asymmetric microstates and transitions toward them were found to be negatively correlated with antero-posterior brain reorganization and EEG symmetry. Substantial differences in microstates' sequence complexity and presence of C topography were found between groups of patients with alpha dominant background, cortical reactivity and antero-posterior gradient. Also, transitioning from left-right to antero-posterior microstates was found to be an independent predictor of consciousness recovery, stronger than consciousness levels at IRU's admission. In conclusions, global brain dynamics measured with scale-free estimators can be considered an indicator of consciousness presence and a candidate marker of short-term recovery in patients with a pDoC.

Continuous versus Routine Electroencephalography in the Intensive Care Unit: A Review of Current Evidence

BACKGROUND

Electroencephalography (EEG) has long been used to detect seizures in patients with disorders of consciousness. In recent years, there has been a drastically increased adoption of continuous EEG (cEEG) in the intensive care units (ICUs). Given the resources necessary to record and interpret cEEG, this is still not available in every center and widespread recommendations to use continuous instead of routine EEG (typically lasting 20 min) are still a matter of some debate. Considering recent literature and personal experience, this review offers a rationale and practical advice to address this question.

SUMMARY

Despite the development of increasingly performant imaging techniques and several validated biomarkers, EEG remains central to clinicians in the intensive care unit and has been experiencing expanding popularity for at least 2 decades. Not only does EEG allow seizure or status epilepticus detection, which in the ICU often present without clinical movements, but it is also paramount for the prognostic evaluation of comatose patients, especially after cardiac arrest, and for detecting delayed ischemia after subarachnoid hemorrhage. At the end of the last Century, improvements of technical and digital aspects regarding recording and storage of EEG tracings have progressively led to the era of cEEG and automated quantitative analysis.

KEY MESSAGES

As compared to repeated rEEG, cEEG in comatose patients does not seem to improve clinical prognosis to a relevant extent, despite allowing a more performant of detection ictal events and consequent therapeutic modifications. The choice between cEEG and rEEG must therefore always be patient-tailored.

Validation of a Model for Targeted EEG Monitoring Duration in Critically Ill Children

PURPOSE

Continuous EEG monitoring (CEEG) to identify electrographic seizures (ES) in critically ill children is resource intense. Targeted strategies could enhance implementation feasibility. We aimed to validate previously published findings regarding the optimal CEEG duration to identify ES in critically ill children.

METHODS

This was a prospective observational study of 1,399 consecutive critically ill children with encephalopathy. We validated the findings of a multistate survival model generated in a published cohort ( N = 719) in a new validation cohort ( N = 680). The model aimed to determine the CEEG duration at which there was <15%, <10%, <5%, or <2% risk of experiencing ES if CEEG were continued longer. The model included baseline clinical risk factors and emergent EEG risk factors.

RESULTS

A model aiming to determine the CEEG duration at which a patient had <10% risk of ES if CEEG were continued longer showed similar performance in the generation and validation cohorts. Patients without emergent EEG risk factors would undergo 7 hours of CEEG in both cohorts, whereas patients with emergent EEG risk factors would undergo 44 and 36 hours of CEEG in the generation and validation cohorts, respectively. The <10% risk of ES model would yield a 28% or 64% reduction in CEEG hours compared with guidelines recommending CEEG for 24 or 48 hours, respectively.

CONCLUSIONS

This model enables implementation of a data-driven strategy that targets CEEG duration based on readily available clinical and EEG variables. This approach could identify most critically ill children experiencing ES while optimizing CEEG use.

EEG criteria for diagnosing nonconvulsive status epilepticus in comatose - An unsolved puzzle: A narrative review

Introduction

Nonconvulsive status epilepticus (NCSE) is an important and often unrecognized cause of impaired awareness especially in critically ill patients, which can easily be missed. Electroencephalography (EEG) findings in clinically suspected cases are the mainstay of diagnosis.

Review summary

The EEG diagnostic criteria for NCSE have evolved over the past three decades. Furthermore, recent advancements in EEG technologies such as continuous EEG monitoring, and emergency department EEG, along with development of different diagnostic criteria, have increased the detection rate for NCSE in suspected cases. However, treating physicians should have a higher index of clinical suspicion and a lower threshold for recommending this valuable investigation. The introduction of different diagnostic criteria has made it easier for electroencephalographers to report NCSE; nevertheless, diagnosis is not always straightforward. This narrative review aimed to define and discuss the available literature on different EEG diagnostic criteria for NCSE.

Conclusion

There is a need for further prospective research to strengthen the diagnostic accuracy of the available diagnostic criteria, the modified Salzburg Consensus Criteria for NCSE (mSCNC) and updated American Clinical Neurophysiology Society (ACNS) 21 criteria, to verify their accuracy to detect NCSE in comatose patients.

Drug-resistant temporal lobe epilepsy with temporal encephaloceles: How far to resect

PURPOSE

This study sought to evaluate the impact of surgical extent on seizure outcome in drug-resistant temporal lobe epilepsy (DR-TLE) with temporal encephaloceles (TE).

METHODS

This was a single-institution retrospective study of patients who underwent surgery for DR-TLE with TE between January 2008 and December 2020. The impact of surgical extent on seizure outcome was evaluated. In a subset with dominant DR-TLE, the impact of surgical extent on neuropsychometric outcome was evaluated.

RESULTS

Thirty-four patients were identified (female, 56%; median age at surgery, 43 years). TE were frequently overlooked on initial magnetic resonance imaging (MRI), with encephaloceles only detected after repeat or expert re-review of MRI, additional multi-modal imaging, or intra-operatively in 31 (91%). Sixteen (47%) underwent limited resections, including encephalocele resection only (n = 5) and encephalocele resection with more extensive temporal corticectomy sparing the amygdala and hippocampus (n = 11). The remainder (n = 18, 53%) underwent standard anterior temporal lobectomy and amygdalohippocampectomy (ATLAH). Limited resection was performed more frequently on the left (12/17 vs. 4/17, p = 0.015). Twenty-seven patients (79%) had a favourable outcome (Engel I/II), and 17 (50%) were seizure-free at the last follow-up (median seizure-free survival of 27.3 months). There was no statistically significant difference in seizure-free outcomes between limited resection and ATLAH. In dominant DR-TLE, verbal memory decline was more likely after ATLAH than limited resection (3/4 vs. 0/9, p = 0.014).

CONCLUSION

Expert re-review of imaging and multi-modal advanced imaging improved TE identification. There was no statistical difference in seizure-free outcomes based on surgical extent. Preservation of verbal memory supports limited resection in dominant temporal cases.

Analysis of Electrocorticography in Epileptic Patients With Responsive Neurostimulation Undergoing Scalp Electroencephalography Monitoring

PURPOSE

To describe the relationship of electrocorticography events detected by a brain-responsive neurostimulation system (RNS) and their association with ictal and interictal activity detected on simultaneous scalp EEG.

METHODS

We retrospectively identified patients with drug-resistant epilepsy implanted with RNS who subsequently underwent long-term scalp EEG monitoring. RNS detections were correlated to simultaneous activity recorded on scalp EEG to determine the characteristics of electrocorticography-stored long episodes associated with seizures or other findings on scalp EEG.

RESULTS

Eleven patients were included with an average of 3.6 days of monitoring. Most RNS detections were of very brief duration (<10 seconds, 92.9%) and received one stimulation therapy (80.8%). A high proportion of long episodes (67.1%) were not identified as electrographic seizures on scalp EEG. Of those ictal-appearing (71.2%) long episodes, 68.2% had seizure correlates. Long episodes associated with seizures on scalp EEG had a longer median duration compared with those without (39.7 vs. 16.8 seconds, P < 0.002) and had broader spread pattern and were of higher amplitude on electrocorticography. Brief potentially ictal rhythmic discharges were the most common EEG findings associated with long episodes that did not have scalp EEG seizure correlates (100% for ictal- and 50% for non-ictal-appearing long episodes).

CONCLUSIONS

Longer, broader spread and higher amplitude intracranial RNS detections are more likely to manifest as electrographic seizures on scalp EEG. Brief potentially ictal rhythmic discharges may serve as a scalp EEG biomarker of ictal intracranial episodes that are detected as long episodes by the RNS but not identified as electrographic seizures on scalp EEG.

Assessing 72 h vs. 24 h of long-term video-EEG monitoring to confirm the diagnosis of epilepsy: a retrospective observational study

Introduction

Paroxysmal seizure-like events can be a diagnostic challenge. Inpatient video-electroencephalography (EEG) monitoring (VEM) can be a valuable diagnostic tool, but recommendations for the minimal duration of VEM to confirm or rule out epilepsy are inconsistent. In this study, we aim to determine whether VEM of 48 or 72 h was superior to 24 h.

Methods

In this monocentric, retrospective study, we included 111 patients with paroxysmal, seizure-like events who underwent at least 72 h of VEM. Inclusion criteria were as follows: (1) Preliminary workup was inconclusive; (2) VEM admission occurred to confirm a diagnosis; (3) At discharge, the diagnosis of epilepsy was conclusively established. We analyzed the VEM recordings to determine the exact time point of the first occurrence of epileptic abnormalities (EAs; defined as interictal epileptiform discharges or electrographic seizures). Subgroup analyses were performed for epilepsy types and treatment status.

Results

In our study population, 69.4% (77/111) of patients displayed EAs during VEM. In this group, the first occurrence of EAs was observed within 24 h in 92.2% (71/77) of patients and within 24-72 h in 7.8% (6/77). There was no statistically significant difference in the incidence of EA between medicated and non-medicated patients or between focal, generalized epilepsies and epilepsies of unknown type. Of the 19 recorded spontaneous electroclinical seizures, 6 (31.6%) occurred after 24 h.

Discussion

A VEM of 24 h may be sufficient in the diagnostic workup of paroxysmal seizure-like events under most circumstances. Considering the few cases of first EA in the timeframe between 24 and 72 h, a prolonged VEM may be useful in cases with a high probability of epilepsy or where other strategies like sleep-EEG or ambulatory EEG show inconclusive results. Prolonged VEM increases the chance of recording spontaneous seizures. Our study also highlights a high share of subjects with epilepsy that do not exhibit EAs during 72 h of VEM.

The spectrum of sepsis-associated encephalopathy: a clinical perspective

Sepsis-associated encephalopathy is a severe neurologic syndrome characterized by a diffuse dysfunction of the brain caused by sepsis. This review provides a concise overview of diagnostic tools and management strategies for SAE at the acute phase and in the long term. Early recognition and diagnosis of SAE are crucial for effective management. Because neurologic evaluation can be confounded by several factors in the intensive care unit setting, a multimodal approach is warranted for diagnosis and management. Diagnostic tools commonly employed include clinical evaluation, metabolic tests, electroencephalography, and neuroimaging in selected cases. The usefulness of blood biomarkers of brain injury for diagnosis remains limited. Clinical evaluation involves assessing the patient's mental status, motor responses, brainstem reflexes, and presence of abnormal movements. Electroencephalography can rule out non-convulsive seizures and help detect several patterns of various severity such as generalized slowing, epileptiform discharges, and triphasic waves. In patients with acute encephalopathy, the diagnostic value of non-contrast computed tomography is limited. In septic patients with persistent encephalopathy, seizures, and/or focal signs, magnetic resonance imaging detects brain injury in more than 50% of cases, mainly cerebrovascular complications, and white matter changes. Timely identification and treatment of the underlying infection are paramount, along with effective control of systemic factors that may contribute to secondary brain injury. Upon admission to the ICU, maintaining appropriate levels of oxygenation, blood pressure, and metabolic balance is crucial. Throughout the ICU stay, it is important to be mindful of the potential neurotoxic effects associated with specific medications like midazolam and cefepime, and to closely monitor patients for non-convulsive seizures. The potential efficacy of targeted neurocritical care during the acute phase in optimizing patient outcomes deserves to be further investigated. Sepsis-associated encephalopathy may lead to permanent neurologic sequelae. Seizures occurring in the acute phase increase the susceptibility to long-term epilepsy. Extended ICU stays and the presence of sepsis-associated encephalopathy are linked to functional disability and neuropsychological sequelae, underscoring the necessity for long-term surveillance in the comprehensive care of septic patients.

Comparison of neurological manifestation in children with and without coronavirus 2019 experiencing seizures with fever

Whether neurologic symptoms due to SARS-CoV-2 differ from those of non-SARS-CoV-2 viral infection is unclear. We aimed to describe these neurological manifestations and compare the clinical characteristics and treatments in children with seizures and fever with or without COVID-19. We retrospectively analyzed data from 105 hospitalized children (<18 years) with clinical seizures and fever between September 2021 and August 2022. We compared the clinical characteristics and treatments between the COVID-19 (n = 20) and non-COVID-19 (n = 85) groups. Patients with COVID-19 were older than those without (32.5 [20-86] months vs. 20 [16-32] months, p = 0.029). Seizure type and duration and impaired consciousness duration did not differ between groups. Six and 32 patients experienced status epilepticus lasting 30 min in the COVID-19 and non-COVID-19 groups, respectively. Most treatments did not differ between groups; however, electroencephalography was used less frequently for COVID-19. Neurological sequelae occurred in one and four patients in the COVID-19 and non-COVID-19 groups, respectively. In conclusion, seizures with fever due to SARS-CoV-2 were more common in older children. Seizure characteristics and neurologic sequelae did not differ in children with and those without COVID-19. In general, electroencephalography was used less during COVID-19 for infection control measures.

Quantitative EEG and brain network analysis: predicting awakening from early coma after cardiopulmonary resuscitation

OBJECTIVE

For patients in early coma after cardiopulmonary resuscitation (CPR), quantitative electroencephalogram (EEG) and brain network analysis was performed to identify relevant indicators of awakening.

METHODS

A prospective cohort study was conducted on comatose patients after CPR in the neuro-critical care unit. The included patients received clinical evaluation. The bedside high-density (64-lead) EEG monitoring was performed for visual grading and calculation of power spectrum and brain network parameters. A 3-month prognostic assessment was performed and the patients were dichotomized into the awakening group and the unawakening group.

RESULTS

A total of 25 patients were included. The awakening group had higher GCS score, more slow wave pattern and reactive EEG than the unawakening group (P = 0.003, P < 0.001, P < 0.001, respectively). Compared with the unawakening group, (1) the awakening group had significantly higher absolute and relative θ power and slow/fast band ratio of the whole brain (P < 0.05), (2) the awakening group had stronger connection based on coherence, phase synchronization, phase lag index and cross-correlation (P < 0.05), (3) the awakening group had higher small-worldness, clustering coefficient and average path length based on graph theory (P < 0.05).

CONCLUSIONS

The power spectrum and brain network characteristics in patients in early coma after CPR have predictive value for recovery.

Nonconvulsive Status Epilepticus: A Review for Emergency Clinicians

BACKGROUND

Status epilepticus is associated with significant morbidity and mortality and is divided into convulsive status epilepticus and nonconvulsive status epilepticus (NCSE).

OBJECTIVE

This review provides a focused evaluation of NCSE for emergency clinicians.

DISCUSSION

NCSE is a form of status epilepticus presenting with prolonged seizure activity. This disease is underdiagnosed, as it presents with nonspecific signs and symptoms, most commonly change in mental status without overt convulsive motor activity. Causes include epilepsy, cerebral pathology or injury, any systemic insult such as infection, and drugs or toxins. Mortality is primarily related to the underlying condition. Patients most commonly present with altered mental status, but other signs and symptoms include abnormal ocular movements and automatisms such as lip smacking or subtle motor twitches in the face or extremities. The diagnosis is divided into electrographic and electroclinical, and although electroencephalogram (EEG) is recommended for definitive diagnosis, emergency clinicians should consider this disease in patients with prolonged postictal state after a seizure with no improvement in mental status, altered mental status with acute cerebral pathology (e.g., stroke, hypoxic brain injury), and unexplained altered mental status. Assessment includes laboratory evaluation and neuroimaging with EEG. Management includes treating life-threatening conditions, including compromise of the airway, hypoglycemia, hyponatremia, and hypo- or hyperthermia, followed by rapid cessation of the seizure activity with benzodiazepines and other antiseizure medications.

CONCLUSIONS

An understanding of the presentation and management of NCSE can assist emergency clinicians in the care of these patients.

Automated Seizure Detection in Patients with Cardiac Arrest: A Retrospective Review of Ceribell™ Rapid-EEG Recordings

BACKGROUND

In patients with cardiac arrest who remain comatose after return of spontaneous circulation, seizures and other abnormalities on electroencephalogram (EEG) are common. Thus, guidelines recommend urgent initiation of EEG for the evaluation of seizures in this population. Point-of-care EEG systems, such as Ceribell™ Rapid Response EEG (Rapid-EEG), allow for prompt initiation of EEG monitoring, albeit through a reduced-channel montage. Rapid-EEG incorporates an automated seizure detection software (Clarity™) to measure seizure burden in real time and alert clinicians at the bedside when a high seizure burden, consistent with possible status epilepticus, is identified. External validation of Clarity is still needed. Our goal was to evaluate the real-world performance of Clarity for the detection of seizures and status epilepticus in a sample of patients with cardiac arrest.

METHODS

This study was a retrospective review of Rapid-EEG recordings from all the patients who were admitted to the medical intensive care unit at Kent Hospital (Warwick, RI) between 6/1/2021 and 3/18/2022 for management after cardiac arrest and who underwent Rapid-EEG monitoring as part of their routine clinical care (n = 21). Board-certified epileptologists identified events that met criteria for seizures or status epilepticus, as per the 2021 American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology, and evaluated any seizure burden detections generated by Clarity.

RESULTS

In this study, 4 of 21 patients with cardiac arrest (19.0%) who underwent Rapid-EEG monitoring had multiple electrographic seizures, and 2 of those patients (9.5%) had electrographic status epilepticus within the first 24 h of the study. None of these ictal abnormalities were detected by the Clarity seizure detection system. Clarity showed 0% seizure burden throughout the entirety of all four Rapid-EEG recordings, including the EEG pages that showed definite seizures or status epilepticus.

CONCLUSIONS

The presence of frequent electrographic seizures and/or status epilepticus can go undetected by Clarity. Timely and careful review of all raw Rapid-EEG recordings by a qualified human EEG reader is necessary to guide clinical care, regardless of Clarity seizure burden measurements.

Continuous Electroencephalography (EEG) Protocol Improves Seizure Detection in Children on Extracorporeal Membrane Oxygenation

BACKGROUND / OBJECTIVE

Seizures are a complication for pediatric patients requiring extracorporeal membrane oxygenation (ECMO). There are no standardized guidelines regarding continuous electroencephalography (EEG) monitoring to detect seizures in these patients, and the impact of protocolized monitoring has not been evaluated. Here we examined the effects of continuous EEG protocol implementation in our pediatric ECMO population.

METHODS

Retrospective chart reviews were conducted on 57 patients who underwent extracorporeal membrane oxygenation and concurrent continuous EEG out of 165 patients supported on extracorporeal membrane oxygenation. Timing of continuous EEG initiation and seizures detected by continuous EEG was determined for 5 years prior to and 15 months after protocol implementation.

RESULTS

Protocol implementation was associated with increased ECMO-supported patients who were concurrently monitored by continuous EEG. Time from ECMO cannulation to continuous EEG initiation was shorter (median 7 hours after versus 16.2 hours before; P < .001). Patients who had ongoing seizures at the start of continuous EEG recording decreased from 64% preprotocol to 0% postprotocol (P < .001), and there was an associated earlier time to break in status epilepticus postprotocol. Seizures were detected past 48 hours after cannulation in 50% of patients in the postprotocol group.

CONCLUSIONS

Protocol implementation resulted in earlier continuous EEG initiation and more EEGs initiated before seizure onset with evidence of altered seizure dynamics. Although current recommendations suggest that continuous EEG duration of 24-48 hours results in seizure detection for >90% of critically ill adults, longer monitoring may be needed to reliably detect seizures in children supported with ECMO, particularly if monitoring is initiated earlier in the post-cannulation period.

AWAreness during REsuscitation - II: A multi-center study of consciousness and awareness in cardiac arrest

INTRODUCTION

Cognitive activity and awareness during cardiac arrest (CA) are reported but ill understood. This first of a kind study examined consciousness and its underlying electrocortical biomarkers during cardiopulmonary resuscitation (CPR).

METHODS

In a prospective 25-site in-hospital study, we incorporated a) independent audiovisual testing of awareness, including explicit and implicit learning using a computer and headphones, with b) continuous real-time electroencephalography(EEG) and cerebral oxygenation(rSO2) monitoring into CPR during in-hospital CA (IHCA). Survivors underwent interviews to examine for recall of awareness and cognitive experiences. A complementary cross-sectional community CA study provided added insights regarding survivors' experiences.

RESULTS

Of 567 IHCA, 53(9.3%) survived, 28 of these (52.8%) completed interviews, and 11(39.3%) reported CA memories/perceptions suggestive of consciousness. Four categories of experiences emerged: 1) emergence from coma during CPR (CPR-induced consciousness [CPRIC]) 2/28(7.1%), or 2) in the post-resuscitation period 2/28(7.1%), 3) dream-like experiences 3/28(10.7%), 4) transcendent recalled experience of death (RED) 6/28(21.4%). In the cross-sectional arm, 126 community CA survivors' experiences reinforced these categories and identified another: delusions (misattribution of medical events). Low survival limited the ability to examine for implicit learning. Nobody identified the visual image, 1/28(3.5%) identified the auditory stimulus. Despite marked cerebral ischemia (Mean rSO2 = 43%) normal EEG activity (delta, theta and alpha) consistent with consciousness emerged as long as 35-60 minutes into CPR.

CONCLUSIONS

Consciousness. awareness and cognitive processes may occur during CA. The emergence of normal EEG may reflect a resumption of a network-level of cognitive activity, and a biomarker of consciousness, lucidity and RED (authentic "near-death" experiences).

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Determining ICU EEG periodic patterns and why it matters

Historically, periodic EEG patterns were described as any pattern with stereotyped paroxysmal complexes occurring at regular intervals, i.e., the period (T). T is the sum of the duration of the waveform (t1) and, eventually, the duration of the interval between two consecutive waves (t2). The American Clinical Neurophysiology Society introduced the concept of a clearly discernible inter-discharge interval between consecutive waveforms (i.e., t2). As this definition was not applied to what have previously been termed triphasic waves and in some cases of lateralized periodic discharges, we propose reconsideration of terminology that includes historical use of definitions. This will allow the development and usage of the concept for periodic EEG patterns as any runs of stereotyped paroxysmal waveforms separated by nearly identical intervals and prolonged repetitive complexes on the EEG. Prolonged expression means EEG is recorded for a sufficient period of time to prove that the pattern is repetitive, thus resulting in a monomorphic/monotonous pattern. More important than the inter-discharge interval (t2), periodic EEG patterns occur at time regular intervals (T). As a result, periodic EEG activity should be considered along a continuum and not the opposite of rhythmic EEG activity where no interval activity exists between consecutive waveforms.

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.

Focal aware somatosensory seizures with paresis as a complication of surgery for chronic subdural hematoma

There has been only one previous published report of focal aware somatosensory seizures with paresis as a postoperative complication of chronic subdural hematoma (cSDH). This is the second case report of this condition captured on electroencephalography (EEG) as a postoperative complication of cSDH. A 76-year-old man with no history of epilepsy was taken to the emergency department of Shiga University of Medical Science Hospital because of transient weakness of the lower extremities. Head computed tomography showed bilateral cSDH that was larger on the left. Seven days after burr-hole evacuation of the left cSDH, the patient experienced a brief clonic seizure of the right hand without postoperative recurrence of cSDH. He then experienced a tingling sensation in, followed by clumsiness and weakness of, the right upper extremity without fluctuations in consciousness or convulsive movements. These symptoms appeared repeatedly, with intermittent improvement, persisting for 6 days after onset. Scalp EEG showed an electrographic seizure in the left central area, suggesting that the symptoms corresponded to focal aware somatosensory seizures with paresis. The symptoms and epileptiform patterns and electrographic seizures on the EEG disappeared with antiseizure medications.

Migraine Aura-Catch Me If You Can with EEG and MRI-A Narrative Review

Roughly one-third of migraine patients suffer from migraine with aura, characterized by transient focal neurological symptoms or signs such as visual disturbance, sensory abnormalities, speech problems, or paresis in association with the headache attack. Migraine with aura is associated with an increased risk for stroke, epilepsy, and with anxiety disorder. Diagnosis of migraine with aura sometimes requires exclusion of secondary causes if neurological deficits present for the first time or are atypical. It was the aim of this review to summarize EEG an MRI findings during migraine aura in the context of pathophysiological concepts. This is a narrative review based on a systematic literature search. During visual auras, EEG showed no consistent abnormalities related to aura, although transient focal slowing in occipital regions has been observed in quantitative studies. In contrast, in familial hemiplegic migraine (FHM) and migraine with brain stem aura, significant EEG abnormalities have been described consistently, including slowing over the affected hemisphere or bilaterally or suppression of EEG activity. Epileptiform potentials in FHM are most likely attributable to associated epilepsy. The initial perfusion change during migraine aura is probably a short lasting hyperperfusion. Subsequently, perfusion MRI has consistently demonstrated cerebral hypoperfusion usually not restricted to one vascular territory, sometimes associated with vasoconstriction of peripheral arteries, particularly in pediatric patients, and rebound hyperperfusion in later phases. An emerging potential MRI signature of migraine aura is the appearance of dilated veins in susceptibility-weighted imaging, which may point towards the cortical regions related to aura symptoms ("index vein"). Conclusions: Cortical spreading depression (CSD) cannot be directly visualized but there are probable consequences thereof that can be captured Non-invasive detection of CSD is probably very challenging in migraine. Future perspectives will be elaborated based on the studies summarized.

Spectrum of EEG Findings in Patients with Leptomeningeal Carcinomatosis and Seizures: Correlation with Neurodiagnostic Results and Outcome

Purpose: Leptomeningeal carcinomatosis (LC) is a devastating condition in patients with systemic malignancies or primary brain tumors. Although much is known about neuro-radiologic investigations, there is very little information about EEG findings in these patients. Whether EEG is correlated with cranial magnetic resonance imaging (MRI) results and survival has not been investigated. Methods: Medical records of 2340 adult patients with the diagnosis of brain tumor, either metastatic (Group 1) or primary (Group 2), between 2000-2021 were reviewed for the presence of LC and seizures. Demographic and clinical features, laboratory results and Karnofsky performance scores of included patients were noted. Available routine EEG recordings were re-evaluated. Any possible correlation between EEG findings-MRI and EEG findings-survival were investigated statistically. Results: Sixty-six patients with LC and seizures were identified. The most common malignancies were lung cancer and glioblastoma multiforme. Twenty-six EEG recordings of 17 patients in Group 1, and 13 EEGs of 9 patients in Group 2 were available for final analysis. The most common EEG characteristic was background slowing (73%). The most frequent findings were rhythmic periodic patterns or spike wave activity (27%). Sporadic epileptiform discharges (8%) or ictal recordings (4%) were very rare. None of the EEG features correlated with MRI results or survival. Conclusion: There are various EEG patterns in patients with LC and seizures. The most common findings are related to background activity, with rhythmic periodic patterns or spike wave activity being observed less commonly. EEG characteristics do not predict MRI findings or survival.

Developing a Standardized Approach to Grading the Level of Brain Dysfunction on EEG

PURPOSE

To assess variability in interpretation of electroencephalogram (EEG) background activity and qualitative grading of cerebral dysfunction based on EEG findings, including which EEG features are deemed most important in this determination.

METHODS

A web-based survey (Qualtrics) was disseminated to electroencephalographers practicing in institutions participating in the Critical Care EEG Monitoring Research Consortium between May 2017 and August 2018. Respondents answered 12 questions pertaining to their training and EEG interpretation practices and graded 40 EEG segments (15-second epochs depicting patients' most stimulated state) using a 6-grade scale. Fleiss' Kappa statistic evaluated interrater agreement.

RESULTS

Of 110 respondents, 78.2% were attending electroencephalographers with a mean of 8.3 years of experience beyond training. Despite 83% supporting the need for a standardized approach to interpreting the degree of dysfunction on EEG, only 13.6% used a previously published or an institutional grading scale. The overall interrater agreement was fair ( k = 0.35). Having Critical Care EEG Monitoring Research Consortium nomenclature certification (40.9%) or EEG board certification (70%) did not improve interrater agreement ( k = 0.26). Predominant awake frequencies and posterior dominant rhythm were ranked as the most important variables in grading background dysfunction, followed by continuity and reactivity.

CONCLUSIONS

Despite the preference for a standardized grading scale for background EEG interpretation, the lack of interrater agreement on levels of dysfunction even among experienced academic electroencephalographers unveils a barrier to the widespread use of EEG as a clinical and research neuromonitoring tool. There was reasonable agreement on the features that are most important in this determination. A standardized approach to grading cerebral dysfunction, currently used by the authors, and based on this work, is proposed.

Diagnosing nonconvulsive status epilepticus: Defining electroencephalographic and clinical response to diagnostic intravenous antiseizure medication trials

OBJECTIVE

The Salzburg criteria for nonconvulsive status epilepticus (NCSE) and the American Clinical Neurophysiology Society (ACNS) Standardized Critical Care EEG Terminology 2021 include a diagnostic trial with intravenous (IV) antiseizure medications (ASMs) to assess electroencephalographic (EEG) and clinical response as a diagnostic criterion for definite NCSE and possible NCSE. However, how to perform this diagnostic test and assessing the EEG and clinical responses have not been operationally defined.

METHODS

We performed a Delphi process involving six experts to standardize the diagnostic administration of IV ASM and propose operational criteria for EEG and clinical response.

RESULTS

Either benzodiazepines (BZDs) or non-BZD ASMs can be used as first choice for a diagnostic IV ASM trial. However, non-BZDs should be considered in patients who already have impaired alertness or are at risk of respiratory depression. Levetiracetam, valproate, lacosamide, brivaracetam, or (if the only feasible drug) fosphenytoin or phenobarbital were deemed appropriate for a diagnostic IV trial. The starting dose should be approximately two thirds to three quarters of the full loading dose recommended for treatment of status epilepticus, with an additional smaller dose if needed. ASMs should be administered during EEG recording under supervision. A monitoring time of at least 15 min is recommended. If there is no response, a second trial with another non-BDZ or BDZs may be considered. A positive EEG response is defined as the resolution of the ictal-interictal continuum pattern for at least three times the longest previously observed spontaneous interval of resolution (if any), but minimum of one continuous minute. For a clinical response, physicians should use a standardized examination before and after IV ASM administration. We suggest a definite time-locked improvement in a focal deficit or at least one-step improvement on a new dedicated one-domain 10-level NCSE response scale.

SIGNIFICANCE

The proposed standardized approach of a diagnostic IV ASM trial further refines the ACNS and Salzburg diagnostic criteria for NCSE.

Predictive Power of Interictal Epileptiform Discharges in Fitness-to-Drive Evaluation

BACKGROUND AND OBJECTIVES

This study aimed to evaluate and predict the effects of interictal epileptiform discharges (IEDs) on driving ability using simple reaction tests and a driving simulator.

METHODS

Patients with various epilepsies were evaluated with simultaneous EEGs during their response to visual stimuli in a single-flash test, a car-driving video game, and a realistic driving simulator. Reaction times (RTs) and missed reactions or crashes (miss/crash) during normal EEG and IEDs were measured. IEDs, as considered in this study, were a series of epileptiform potentials (>1 potential) and were classified as generalized typical, generalized atypical, or focal. RT and miss/crash in relation to IED type, duration, and test type were analyzed. RT prolongation, miss/crash probability, and odds ratio (OR) of miss/crash due to IEDs were calculated.

RESULTS

Generalized typical IEDs prolonged RT by 164 ms, compared with generalized atypical IEDs (77.0 ms) and focal IEDs (48.0 ms) (p < 0.01). Generalized typical IEDs had a session miss/crash probability of 14.7% compared with a zero median for focal and generalized atypical IEDs (p < 0.01). Long repetitive bursts of focal IEDs lasting >2 seconds had a 2.6% miss/crash probabilityIED. Cumulated miss/crash probability could be predicted from RT prolongation: 90.3 ms yielded a 20% miss/crash probability. All tests were nonsuperior to each other in detecting miss/crash probabilitiesIED (zero median for all 3 tests) or RT prolongations (flash test: 56.4 ms, car-driving video game: 75.5 ms, simulator 86.6 ms). IEDs increased the OR of miss/crash in the simulator by 4.9-fold compared with normal EEG. A table of expected RT prolongations and miss/crash probabilities for IEDs of a given type and duration was created.

DISCUSSION

IED-associated miss/crash probability and RT prolongation were comparably well detected by all tests. Long focal IED bursts carry a low risk, while generalized typical IEDs are the primary cause of miss/crash. We propose a cumulative 20% miss/crash risk at an RT prolongation of 90.3 ms as a clinically relevant IED effect. The IED-associated OR in the simulator approximates the effects of sleepiness or low blood alcohol level while driving on real roads. A decision aid for fitness-to-drive evaluation was created by providing the expected RT prolongations and misses/crashes when IEDs of a certain type and duration are detected in routine EEG.

Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest

BACKGROUND AND OBJECTIVES

Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest.

METHODS

Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months.

RESULTS

One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery.

DISCUSSION

Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.