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

2021 European Resuscitation Council/European Society of Intensive Care Medicine Algorithm for Prognostication of Poor Neurological Outcome After Cardiac Arrest-Can Entry Criteria Be Broadened?

OBJECTIVES

To explore broadened entry criteria of the 2021 European Resuscitation Council/European Society of Intensive Care Medicine (ERC/ESICM) algorithm for neuroprognostication including patients with ongoing sedation and Glasgow Coma Scale-Motor score (GCS-M) scores 4-5.

DESIGN

Retrospective multicenter observational study.

SETTING

Four ICUs, Skane, Sweden.

PATIENTS

Postcardiac arrest patients managed at targeted temperature 36°C, 2014-2018. Neurologic outcome was assessed after 2-6 months according to the Cerebral Performance Category scale.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

In 794 included patients, median age was 69.5 years (interquartile range, 60.6-77.0 yr), 241 (30.4%) were female, 550 (69.3%) had an out-of-hospital cardiac arrest, and 314 (41.3%) had a shockable rhythm. Four hundred ninety-five patients were dead at follow-up, 330 of 495 died after a decision on withdrawal of life-sustaining therapies. At 72 hours after cardiac arrest 218 patients remained unconscious. The entry criteria of the original algorithm (GCS-M 1-3) was fulfilled by 163 patients and 115 patients with poor outcome were identified, with false positive rate (FPR) of 0% (95% CI, 0-79.4%) and sensitivity of 71.0% (95% CI, 63.6-77.4%). Inclusion of patients with ongoing sedation identified another 13 patients with poor outcome, generating FPR of 0% (95% CI, 0-65.8%) and sensitivity of 69.6% (95% CI, 62.6-75.8%). Inclusion of all unconscious patients (GCS-M 1-5), regardless of sedation, identified one additional patient, generating FPR of 0% (95% CI, 0-22.8) and sensitivity of 62.9% (95% CI, 56.1-69.2). The few patients with true negative prediction (patients with good outcome not fulfilling guideline criteria of a poor outcome) generated wide 95% CI for FPR.

CONCLUSION

The 2021 ERC/ESICM algorithm for neuroprognostication predicted poor neurologic outcome with a FPR of 0%. Broadening inclusion criteria to include all unconscious patients regardless of ongoing sedation identified an additional small number of patients with poor outcome but did not affect the FPR. Results are limited by high rate of withdrawal of life-sustaining therapies and few patients with true negative prediction.

Multimodal neuromonitoring in the pediatric intensive care unit

Neuromonitoring is used to assess the central nervous system in the intensive care unit. The purpose of neuromonitoring is to detect neurologic deterioration and intervene to prevent irreversible nervous system dysfunction. Neuromonitoring starts with the standard neurologic examination, which may lag behind the pathophysiologic changes. Additional modalities including continuous electroencephalography (CEEG), multiple physiologic parameters, and structural neuroimaging may detect changes earlier. Multimodal neuromonitoring now refers to an integrated combination and display of non-invasive and invasive modalities, permitting tailored treatment for the individual patient. This chapter reviews the non-invasive and invasive modalities used in pediatric neurocritical care.

Optimizing EEG monitoring in critically ill children at risk for electroencephalographic seizures

OBJECTIVE

Strategies are needed to optimally deploy continuous EEG monitoring (CEEG) for electroencephalographic seizure (ES) identification and management due to resource limitations. We aimed to construct an efficient multi-stage prediction model guiding CEEG utilization to identify ES in critically ill children using clinical and EEG covariates.

METHODS

The largest prospective single-center cohort of 1399 consecutive children undergoing CEEG was analyzed. A four-stage model was developed and trained to predict whether a subject required additional CEEG at the conclusion of each stage given their risk of ES. Logistic regression, elastic net, random forest, and CatBoost served as candidate methods for each stage and were evaluated using cross validation. An optimal multi-stage model consisting of the top-performing stage-specific models was constructed.

RESULTS

When evaluated on a test set, the optimal multi-stage model achieved a cumulative specificity of 0.197 and cumulative F1 score of 0.326 while maintaining a high minimum cumulative sensitivity of 0.938. Overall, 11 % of test subjects with ES were removed from the model due to a predicted low risk of ES (falsely negative subjects). CEEG utilization would be reduced by 32 % and 47 % compared to performing 24 and 48 h of CEEG in all test subjects, respectively. We developed a web application called EEGLE (EEG Length Estimator) that enables straightforward implementation of the model.

CONCLUSIONS

Application of the optimal multi-stage ES prediction model could either reduce CEEG utilization for patients at lower risk of ES or promote CEEG resource reallocation to patients at higher risk for ES.

Delayed Deterioration of Electroencephalogram in Patients with Cardiac Arrest: A Cohort Study

BACKGROUND

The aim of this study was to assess the prevalence of delayed deterioration of electroencephalogram (EEG) in patients with cardiac arrest (CA) without early highly malignant patterns and to determine their associations with clinical findings.

METHODS

This was a retrospective study of adult patients with CA admitted to the intensive care unit (ICU) of a university hospital. We included all patients with CA who had a normal voltage EEG, no more than 10% discontinuity, and absence of sporadic epileptic discharges, periodic discharges, or electrographic seizures. Delayed deterioration was classified as the following: (1) epileptic deterioration, defined as the appearance, at least 24 h after CA, of sporadic epileptic discharges, periodic discharges, and status epilepticus; or (2) background deterioration, defined as increasing discontinuity or progressive attenuation of the background at least 24 h after CA. The end points were the incidence of EEG deteriorations and their association with clinical features and ICU mortality.

RESULTS

We enrolled 188 patients in the analysis. The ICU mortality was 46%. Overall, 30 (16%) patients presented with epileptic deterioration and 9 (5%) patients presented with background deterioration; of those, two patients presented both deteriorations. Patients with epileptic deterioration more frequently had an out-of-hospital CA, and higher time to return of spontaneous circulation and less frequently had bystander resuscitation than others. Patients with background deterioration showed a predominantly noncardiac cause, more frequently developed shock, and had multiple organ failure compared with others. Patients with epileptic deterioration presented with a higher ICU mortality (77% vs. 41%; p < 0.01) than others, whereas all patients with background deterioration died in the ICU.

CONCLUSIONS

Delayed EEG deterioration was associated with high mortality rate. Epileptic deterioration was associated with worse characteristics of CA, whereas background deterioration was associated with shock and multiple organ failure.

Combined depth and scalp electroencephalographic monitoring in acute brain injury: Yield and prognostic value

BACKGROUND AND PURPOSE

Depth electroencephalography (dEEG) is an emerging neuromonitoring technology in acute brain injury (ABI). We aimed to explore the concordances between electrophysiological activities on dEEG and on scalp EEG (scEEG) in ABI patients.

METHODS

Consecutive ABI patients who received dEEG monitoring between 2018 and 2022 were included. Background, sporadic epileptiform discharges, rhythmic and periodic patterns (RPPs), electrographic seizures, brief potentially ictal rhythmic discharges, ictal-interictal continuum (IIC) patterns, and hourly RPP burden on dEEG and scEEG were compared.

RESULTS

Sixty-one ABI patients with a median dEEG monitoring duration of 114 h were included. dEEG significantly showed less continuous background (75% vs. 90%, p = 0.03), higher background amplitude (p < 0.001), more frequent rhythmic spike-and-waves (16% vs. 3%, p = 0.03), more IIC patterns (39% vs. 21%, p = 0.03), and greater hourly RPP burden (2430 vs. 1090 s/h, p = 0.01), when compared to scEEG. Among five patients with seizures on scEEG, one patient had concomitant seizures on dEEG, one had periodic discharges (not concomitant) on dEEG, and three had no RPPs on dEEG. Features and temporal occurrence of electrophysiological activities observed on dEEG and scEEG are not strongly associated. Patients with seizures and IIC patterns on dEEG seemed to have a higher rate of poor outcomes at discharge than patients without these patterns on dEEG (42% vs. 25%, p = 0.37).

CONCLUSIONS

dEEG can detect abnormal electrophysiological activities that may not be seen on scEEG and can be used as a complement in the neuromonitoring of ABI patients.

Ketamine in the treatment of refractory and super-refractory status epilepticus: Experience from two centres

PURPOSE

There is insufficient evidence on the management of refractory status epilepticus (RSE) and super-RSE (SRSE). Ketamine is a N-methyl-d-aspartate receptor antagonist in the treatment of these entities. Our objectives were to study the effectiveness and safety of ketamine in the treatment of adult patients with RSE and SRSE, to determine the factors that can influence the response to ketamine, and to explore its use in patients without mechanical ventilation.

METHODS

Adult patients who had received intravenous ketamine for the treatment of RSE or SRSE at Hospital Universitario Clínico San Carlos (Madrid, Spain) or Hospital Universitari Vall d'Hebron (Barcelona, Spain) from 2017 to 2023 were retrospectively analysed.

RESULTS

This study included 58 adult patients, mean (standard deviation) age 60.2 (15.7) years, of whom 41 (70.7 %) were male; 33 (56.9 %) patients responded to ketamine without recurrence, with a low rate of adverse effects (8.6 %). The presence of SRSE at the time of ketamine initiation (OR 0.287, p = 0.028) and the time elapsed between status epilepticus onset and ketamine administration (OR 0.991, p = 0.034) were associated with worse response to ketamine. Patients treated without mechanical ventilation had similar rates of response without recurrence (62.5% vs 56.9 %) and lower mortality (37.5% vs 53.5 %) compared to the overall group.

CONCLUSION

Ketamine is an effective drug with few adverse effects. Prompt administration should be considered in patients with RSE requiring anaesthesia, in patients with SRSE, and in patients with RSE who do not respond to standard antiseizure drugs and in whom mechanical ventilation is not advised.

Aberrant brain-heart coupling is associated with the severity of post cardiac arrest brain injury

OBJECTIVE

To investigate autonomic nervous system activity measured by brain-heart interactions in comatose patients after cardiac arrest in relation to the severity and prognosis of hypoxic-ischemic brain injury.

METHODS

Strength and complexity of bidirectional interactions between EEG frequency bands (delta, theta, and alpha) and ECG heart rate variability frequency bands (low frequency, LF and high frequency, HF) were computed using a synthetic data generation model. Primary outcome was the severity of brain injury, assessed by (i) standardized qualitative EEG classification, (ii) somatosensory evoked potentials (N20), and (iii) neuron-specific enolase levels. Secondary outcome was the 3-month neurological status, assessed by the Cerebral Performance Category score [good (1-2) vs. poor outcome (3-4-5)].

RESULTS

Between January 2007 and July 2021, 181 patients were admitted to ICU for a resuscitated cardiac arrest. Poor neurological outcome was observed in 134 patients (74%). Qualitative EEG patterns suggesting high severity were associated with decreased LF/HF. Severity of EEG changes were proportional to higher absolute values of brain-to-heart coupling strength (p < 0.02 for all brain-to-heart frequencies) and lower values of alpha-to-HF complexity (p = 0.049). Brain-to-heart coupling strength was significantly higher in patients with bilateral absent N20 and correlated with neuron-specific enolase levels at Day 3. This aberrant brain-to-heart coupling (increased strength and decreased complexity) was also associated with 3-month poor neurological outcome.

INTERPRETATION

Our results suggest that autonomic dysfunctions may well represent hypoxic-ischemic brain injury post cardiac arrest pathophysiology. These results open avenues for integrative monitoring of autonomic functioning in critical care patients.

Status epilepticus: what's new for the intensivist

PURPOSE OF REVIEW

Status epilepticus (SE) is a common neurologic emergency affecting about 36.1/100 000 person-years that frequently requires intensive care unit (ICU) admission. There have been advances in our understanding of epidemiology, pathophysiology, and EEG monitoring of SE, and there have been large-scale treatment trials, discussed in this review.

RECENT FINDINGS

Recent changes in the definitions of SE have helped guide management protocols and we have much better predictors of outcome. Observational studies have confirmed the efficacy of benzodiazepines and large treatment trials indicate that all routinely used second line treatments (i.e., levetiracetam, valproate and fosphenytoin) are equally effective. Better understanding of the pathophysiology has indicated that nonanti-seizure medications aimed at underlying pathological processes should perhaps be considered in the treatment of SE; already immunosuppressant treatments are being more widely used in particular for new onset refractory status epilepticus (NORSE) and Febrile infection-related epilepsy syndrome (FIRES) that sometimes revealed autoimmune or paraneoplastic encephalitis. Growing evidence for ICU EEG monitoring and major advances in automated analysis of the EEG could help intensivist to assess the control of electrographic seizures.

SUMMARY

Research into the morbi-mortality of SE has highlighted the potential devastating effects of this condition, emphasizing the need for rapid and aggressive treatment, with particular attention to cardiorespiratory and neurological complications. Although we now have a good evidence-base for the initial status epilepticus management, the best treatments for the later stages are still unclear and clinical trials of potentially disease-modifying therapies are long overdue.

Recent advances in clinical electroencephalography

PURPOSE OF REVIEW

Clinical electroencephalography (EEG) is a conservative medical field. This explains likely the significant gap between clinical practice and new research developments. This narrative review discusses possible causes of this discrepancy and how to circumvent them. More specifically, we summarize recent advances in three applications of clinical EEG: source imaging (ESI), high-frequency oscillations (HFOs) and EEG in critically ill patients.

RECENT FINDINGS

Recently published studies on ESI provide further evidence for the accuracy and clinical utility of this method in the multimodal presurgical evaluation of patients with drug-resistant focal epilepsy, and opened new possibilities for further improvement of the accuracy. HFOs have received much attention as a novel biomarker in epilepsy. However, recent studies questioned their clinical utility at the level of individual patients. We discuss the impediments, show up possible solutions and highlight the perspectives of future research in this field. EEG in the ICU has been one of the major driving forces in the development of clinical EEG. We review the achievements and the limitations in this field.

SUMMARY

This review will promote clinical implementation of recent advances in EEG, in the fields of ESI, HFOs and EEG in the intensive care.

Mapping of the central sulcus using non-invasive ultra-high-density brain recordings

Brain mapping is vital in understanding the brain's functional organization. Electroencephalography (EEG) is one of the most widely used brain mapping approaches, primarily because it is non-invasive, inexpensive, straightforward, and effective. Increasing the electrode density in EEG systems provides more neural information and can thereby enable more detailed and nuanced mapping procedures. Here, we show that the central sulcus can be clearly delineated using a novel ultra-high-density EEG system (uHD EEG) and somatosensory evoked potentials (SSEPs). This uHD EEG records from 256 channels with an inter-electrode distance of 8.6 mm and an electrode diameter of 5.9 mm. Reconstructed head models were generated from T1-weighted MRI scans, and electrode positions were co-registered to these models to create topographical plots of brain activity. EEG data were first analyzed with peak detection methods and then classified using unsupervised spectral clustering. Our topography plots of the spatial distribution from the SSEPs clearly delineate a division between channels above the somatosensory and motor cortex, thereby localizing the central sulcus. Individual EEG channels could be correctly classified as anterior or posterior to the central sulcus with 95.2% accuracy, which is comparable to accuracies from invasive intracranial recordings. Our findings demonstrate that uHD EEG can resolve the electrophysiological signatures of functional representation in the brain at a level previously only seen from surgically implanted electrodes. This novel approach could benefit numerous applications, including research, neurosurgical mapping, clinical monitoring, detection of conscious function, brain-computer interfacing (BCI), rehabilitation, and mental health.

Coma Prognostication After Acute Brain Injury: A Review

Importance

Among the most impactful neurologic assessments is that of neuroprognostication, defined here as the prediction of neurologic recovery from disorders of consciousness caused by severe, acute brain injury. Across a range of brain injury etiologies, these determinations often dictate whether life-sustaining treatment is continued or withdrawn; thus, they have major implications for morbidity, mortality, and health care costs. Neuroprognostication relies on a diverse array of tests, including behavioral, radiologic, physiological, and serologic markers, that evaluate the brain's functional and structural integrity.

Observations

Prognostic markers, such as the neurologic examination, electroencephalography, and conventional computed tomography and magnetic resonance imaging (MRI), have been foundational in assessing a patient's current level of consciousness and capacity for recovery. Emerging techniques, such as functional MRI, diffusion MRI, and advanced forms of electroencephalography, provide new ways of evaluating the brain, leading to evolving schemes for characterizing neurologic function and novel methods for predicting recovery.

Conclusions and Relevance

Neuroprognostic markers are rapidly evolving as new ways of assessing the brain's structural and functional integrity after brain injury are discovered. Many of these techniques remain in development, and further research is needed to optimize their prognostic utility. However, even as such efforts are underway, a series of promising findings coupled with the imperfect predictive value of conventional prognostic markers and the high stakes of these assessments have prompted clinical guidelines to endorse emerging techniques for neuroprognostication. Thus, clinicians have been thrust into an uncertain predicament in which emerging techniques are not yet perfected but too promising to ignore. This review illustrates the current, and likely future, landscapes of prognostic markers. No matter how much prognostic markers evolve and improve, these assessments must be approached with humility and individualized to reflect each patient's values.

Association of Cerebral and Systemic Physiology With Quantitative Electroencephalographic Characteristics of Early Posttraumatic Seizures

PURPOSE

Early posttraumatic seizures (EPTS) occur after pediatric traumatic brain injury and have been associated with unfavorable outcomes. We aimed to characterize the relationship among quantitative EEG characteristics of early posttraumatic seizures, cerebral and somatic physiologic measures.

METHODS

Differences in baseline physiologic, neuroimaging, and demographic characteristics between those with and without early posttraumatic seizures were investigated using Mann-Whitney U test or Fisher exact test. Multivariable dynamic structural equations modeling was used to investigate time series associations between ictal quantitative EEG characteristics with intracranial pressure, arterial blood pressure, heart rate (HR), and cerebral regional oximetry. Quantitative EEG characteristics included amplitude, total power, spectral edge frequency, peak value frequency, complexity, and periodicity.

RESULTS

Among 72 children, 146 seizures were identified from 19 patients. Early posttraumatic seizures were associated with younger age ( P = 0.0034), increased HR ( P = 0.0018), and increased Glasgow Outcome Scale-Extended scores ( P = 0.0377). Group dynamic structural equations modeling analysis of the first seizure for patients demonstrated that intracranial pressure is negatively associated with spectral edge frequency (standardized regression coefficient -0.12, 99% credible interval [-0.21 to -0.04]), and HR is positively associated with peak value frequency (standardized regression coefficient 0.16, [0.00-0.31]). Among nine patients with seizures arising over the frontal lobe regions, HR was positively associated with peak value frequency (standardized regression coefficient 0.26 [0.02-0.50]) and complexity (standardized regression coefficient 0.14 [0.03-0.26]). Variation in strength and direction of associations was observed between subjects for relationships that were significant during group analysis.

CONCLUSIONS

Quantitative EEG characteristics of pediatric early posttraumatic seizures are associated with variable changes in cerebral and systemic physiology, with spectral edge frequency negatively associated with intracranial pressure and peak value frequency positively associated with HR.

Residual Seizure Rate of Intermittent Inpatient EEG Compared to a Continuous EEG Model

BACKGROUND

Subclinical seizures are common in hospitalized patients and require electroencephalography (EEG) for detection and intervention. At our institution, continuous EEG (cEEG) is not available, but intermittent EEGs are subject to constant live interpretation. As part of quality improvement (QI), we sought to estimate the residual missed seizure rate at a typical quaternary Canadian health care center without cEEG.

METHODS

We calculated residual risk percentages using the clinically validated 2HELPS2B score to risk-stratify EEGs before deriving a risk percentage using a MATLAB calculator which modeled the risk decay curve for each recording. We generated a range of estimated residual seizure rates depending on whether a pre-cEEG screening EEG was simulated, EEGs showing seizures were included, or repeat EEGs on the same patient were excluded.

RESULTS

Over a 4-month QI period, 499 inpatient EEGs were scored as low (n = 125), medium (n = 123), and high (n = 251) seizure risk according to 2HELPS2B criteria. Median recording duration was 1:00:06 (interquartile range, IQR 30:40-2:21:10). The model with highest residual seizure rate included recordings with confirmed electrographic seizures (median 20.83%, IQR 20.6-26.6%), while the model with lowest residual seizure rate was in seizure-free recordings (median 10.59%, IQR 4%-20.6%). These rates were significantly higher than the benchmark 5% miss-rate threshold set by 2HELPS2B (p<0.0001).

CONCLUSIONS

We estimate that intermittent inpatient EEG misses 2-4 times more subclinical seizures than the 2HELPS2B-determined acceptable 5% seizure miss-rate threshold for cEEG. Future research is needed to determine the impact of potentially missed seizures on clinical care.

Beyond Seizures: The Usefulness of EEG in Septic Patients

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Reducing Time to Electroencephalography in Pediatric Convulsive Status Epilepticus: A Quality Improvement Initiative

BACKGROUND

Pediatric convulsive status epilepticus (CSE) is a neurological emergency utilizing electroencephalography (EEG) to guide therapeutic interventions. Guidelines recommend EEG initiation within one hour of seizure onset, but logistic and structural barriers often lead to significant delays. We aimed to reduce the time to EEG in pediatric CSE.

METHODS

From 2017 to 2022, we implemented process improvements, including EEG order sets with priority-based timing guidance, technologist workflow changes, a satisfaction survey, and feedback from key stakeholder groups, over five plan-do-study-act (PDSA) cycles. Seizure start time, time of EEG order, and time to EEG initiation were extracted. Time to interpretable EEG was determined from manual review of the EEG tracing.

RESULTS

Time from EEG order to interpretable EEG decreased by nearly 50%, from a median of 90 minutes to 48 minutes. There were clinically and statistically significant improvements in time from EEG order to EEG initiation, time from EEG order to interpretable EEG, and EEG start to interpretable EEG. Ongoing provider education and guidance enabled improvements, whereas a new electronic health care record negatively impacted electronic ordering. EEG technologists reported that they understood the importance of emergent EEG for clinical care and did not find that the new workflow caused excessive disruption.

CONCLUSIONS

Timely access to EEG for pediatric patients with CSE can be improved through clinical processes that use existing devices and that maintain the benefits of full-montage EEG recordings. Similar process improvement efforts may be generalizable to other institutions to increase adherence to guidelines and provide improved care.

Nonconvulsive Status Epilepticus: Clinical Findings, EEG Features, and Prognosis in a Developing Country, Mexico

PURPOSE

There is a lack of clinical and epidemiological knowledge about nonconvulsive status epilepticus (NCSE) in developing countries including Mexico, which has the highest prevalence of epilepsy in the Americas. Our aim was to describe the clinical findings, EEG features, and outcomes of NCSE in a tertiary center in Mexico.

METHODS

We conducted a retrospective case series study (2010-2020) including patients (≥15 years old) with NCSE according to the modified Salzburg NCSE criteria 2015 with at least 6 months of follow-up. We extracted the clinical data (age, sex, history of epilepsy, antiseizure medications, clinical manifestations, triggers, and etiology), EEG patterns of NCSE, and outcome. Descriptive statistics and multinomial logistic regression were used.

RESULTS

One hundred thirty-four patients were analyzed; 74 (54.8%) women, the total mean age was 39.5 (15-85) years, and 71% had a history of epilepsy. Altered state of consciousness was found in 82% (including 27.7% in coma). A generalized NCSE pattern was the most common (32.1%). The NCSE etiology was mainly idiopathic (56%), and previous uncontrolled epilepsy was the trigger in 48% of patients. The clinical outcome was remission with clinical improvement in 54.5%. Multinomial logistic regression showed that the patient's age (P = 0.04), absence of comorbidities (P = 0.04), history of perinatal hypoxia (P = 0.04), absence of clinical manifestations (P = 0.01), and coma (P = 0.03) were negatively correlated with the outcome and only the absence of generalized slowing in the EEG (P = 0.001) had a significant positive effect on the prognosis.

CONCLUSIONS

Age, history of perinatal hypoxia, coma, and focal ictal EEG pattern influence negatively the prognosis of NCSE.

Relationship of Neonatal Seizure Burden Before Treatment and Response to Initial Antiseizure Medication

OBJECTIVE

To assess among a cohort of neonates with hypoxic-ischemic encephalopathy (HIE) the association of pretreatment maximal hourly seizure burden and total seizure duration with successful response to initial antiseizure medication (ASM).

STUDY DESIGN

This was a retrospective review of data collected from infants enrolled in the HEAL Trial (NCT02811263) between January 25, 2017, and October 9, 2019. We evaluated a cohort of neonates born at ≥36 weeks of gestation with moderate-to-severe HIE who underwent continuous electroencephalogram monitoring and had acute symptomatic seizures. Poisson regression analyzed associations between (1) pretreatment maximal hourly seizure burden, (2) pretreatment total seizure duration, (3) time from first seizure to initial ASM, and (4) successful response to initial ASM.

RESULTS

Among 39 neonates meeting inclusion criteria, greater pretreatment maximal hourly seizure burden was associated with lower chance of successful response to initial ASM (adjusted relative risk for each 5-minute increase in seizure burden 0.83, 95% CI 0.69-0.99). There was no association between pretreatment total seizure duration and chance of successful response. Shorter time-to-treatment was paradoxically associated with lower chance of successful response to treatment, although this difference was small in magnitude (relative risk 1.007, 95% CI 1.003-1.010).

CONCLUSIONS

Maximal seizure burden may be more important than other, more commonly used measures in predicting response to acute seizure treatments.

Variational mode decomposition-based EEG analysis for the classification of disorders of consciousness

Aberrant alterations in any of the two dimensions of consciousness, namely awareness and arousal, can lead to the emergence of disorders of consciousness (DOC). The development of DOC may arise from more severe or targeted lesions in the brain, resulting in widespread functional abnormalities. However, when it comes to classifying patients with disorders of consciousness, particularly utilizing resting-state electroencephalogram (EEG) signals through machine learning methods, several challenges surface. The non-stationarity and intricacy of EEG data present obstacles in understanding neuronal activities and achieving precise classification. To address these challenges, this study proposes variational mode decomposition (VMD) of EEG before feature extraction along with machine learning models. By decomposing preprocessed EEG signals into specified modes using VMD, features such as sample entropy, spectral entropy, kurtosis, and skewness are extracted across these modes. The study compares the performance of the features extracted from VMD-based approach with the frequency band-based approach and also the approach with features extracted from raw-EEG. The classification process involves binary classification between unresponsive wakefulness syndrome (UWS) and the minimally conscious state (MCS), as well as multi-class classification (coma vs. UWS vs. MCS). Kruskal-Wallis test was applied to determine the statistical significance of the features and features with a significance of p < 0.05 were chosen for a second round of classification experiments. Results indicate that the VMD-based features outperform the features of other two approaches, with the ensemble bagged tree (EBT) achieving the highest accuracy of 80.5% for multi-class classification (the best in the literature) and 86.7% for binary classification. This approach underscores the potential of integrating advanced signal processing techniques and machine learning in improving the classification of patients with disorders of consciousness, thereby enhancing patient care and facilitating informed treatment decision-making.

Clinical Implications of Various Electroencephalographic Patterns in Post-Stroke Seizures. The Utility of Routine Electroencephalogram

Objective: Post-stroke seizures (PSS) are one of the major stroke-related complications. Early therapeutic interventions are critical therefore using electroencephalography (EEG) as a predictive tool for future recurrence may be helpful. We aimed to assess frequencies of different EEG patterns in patients with PSS and their association with seizure recurrence and functional outcomes. Methods: All patients admitted with PSS were included and underwent interictal EEG recording during their admission and monitored for seizure recurrence for 24 months. Results: PSS was reported in 106 patients. Generalized slow wave activity (GSWA) was the most frequent EEG pattern observed (n  =  62, 58.5%), followed by Focal sharp wave discharges (FSWDs) (n  =  57, 55.8%), focal slow wave activity (FSWA) (n  =  56, 52.8%), periodic discharges (PDs) (n  =  13, 12.3%), and ictal epileptiform abnormalities (n  =  6, 5.7%). FSWA and ictal EAs were positively associated with seizure recurrence (p < .001 and p  =  .015 respectively) and it remained significant even after adjusting for age, sex, stroke severity, stroke subtype, or use of anti-seizure medications (ASMs). Other positive associations were status epilepticus (SE) (p  =  .015), and use of older ASM (p < .001). FSWA and GSWA in EEG were positively associated with severe functional disability (p  =  .055, p  =  .015 respectively). Other associations were; Diabetes Mellitus (p  =  .034), Chronic Kidney Disease (p  =  .002), use of older ASMs (p  =  .037), presence of late PSS (p  =  .021), and those with Ischemic stroke (p  =  .010). Conclusions: Recognition and documentation of PSS-related EEG characteristics are important, as certain EEG patterns may help to identify the patients who are at risk of developing recurrence or worse functional outcomes.

Glioma genetic profiles associated with electrophysiologic hyperexcitability

BACKGROUND

Distinct genetic alterations determine glioma aggressiveness, however, the diversity of somatic mutations contributing to peritumoral hyperexcitability and seizures over the course of the disease is uncertain. This study aimed to identify tumor somatic mutation profiles associated with clinically significant hyperexcitability.

METHODS

A single center cohort of adults with WHO grades 1-4 glioma and targeted exome sequencing (n = 1716) was analyzed and cross-referenced with a validated EEG database to identify the subset of individuals who underwent continuous EEG monitoring (n = 206). Hyperexcitability was defined by the presence of lateralized periodic discharges and/or electrographic seizures. Cross-validated discriminant analysis models trained exclusively on recurrent somatic mutations were used to identify variants associated with hyperexcitability.

RESULTS

The distribution of WHO grades and tumor mutational burdens were similar between patients with and without hyperexcitability. Discriminant analysis models classified the presence or absence of EEG hyperexcitability with an overall accuracy of 70.9%, regardless of IDH1 R132H inclusion. Predictive variants included nonsense mutations in ATRX and TP53, indel mutations in RBBP8 and CREBBP, and nonsynonymous missense mutations with predicted damaging consequences in EGFR, KRAS, PIK3CA, TP53, and USP28. This profile improved estimates of hyperexcitability in a multivariate analysis controlling for age, sex, tumor location, integrated pathologic diagnosis, recurrence status, and preoperative epilepsy. Predicted somatic mutation variants were over-represented in patients with hyperexcitability compared to individuals without hyperexcitability and those who did not undergo continuous EEG.

CONCLUSION

These findings implicate diverse glioma somatic mutations in cancer genes associated with peritumoral hyperexcitability. Tumor genetic profiling may facilitate glioma-related epilepsy prognostication and management.

Therapeutic Time Window With DWI-ADC (Diffusion-Weighted Imaging-Apparent Diffusion Coefficient) Match and Periodic Discharges for Status Epilepticus

A man in his 70s with alcoholic dementia was admitted for acute, prolonged impaired consciousness. Blood and cerebrospinal fluid findings were unremarkable. Brain MRI revealed multiple high-signal cortical regions. Following diazepam and levetiracetam administration, electroencephalography (EEG) revealed <1 Hz lateralized periodic discharges, indicating that the seizures were ceasing. The periodic discharges had disappeared during the gradual recovery process by day 10; however, cortical arterial spin labeling findings persisted only in regions exhibiting cytotoxic edema. Without additional anti-seizure medication, no seizure recurred, but cognitive dysfunction remained. He was transferred to a rehabilitation hospital with the continued oral administration of levetiracetam at 1,000 mg/day. DWI-ADC (diffusion-weighted imaging-apparent diffusion coefficient) match may suggest an indication of a missed suitable treatment window for seizures.

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group in the Pediatric Population

BACKGROUND

The fundamental gap obstructing forward progress of evidenced-based care in pediatric and neonatal disorders of consciousness (DoC) is the lack of defining consensus-based terminology to perform comparative research. This lack of shared nomenclature in pediatric DoC stems from the inherently recursive dilemma of the inability to reliably measure consciousness in the very young. However, recent advancements in validated clinical examinations and technologically sophisticated biomarkers of brain activity linked to future abilities are unlocking this previously formidable challenge to understanding the DoC in the developing brain.

METHODS

To address this need, the first of its kind international convergence of an interdisciplinary team of pediatric DoC experts was organized by the Neurocritical Care Society's Curing Coma Campaign. The multidisciplinary panel of pediatric DoC experts proposed pediatric-tailored common data elements (CDEs) covering each of the CDE working groups including behavioral phenotyping, biospecimens, electrophysiology, family and goals of care, neuroimaging, outcome and endpoints, physiology and big Data, therapies, and pediatrics.

RESULTS

We report the working groups' pediatric-focused DoC CDE recommendations and disseminate CDEs to be used in studies of pediatric patients with DoC.

CONCLUSIONS

The CDEs recommended support the vision of progressing collaborative and successful internationally collaborative pediatric coma research.

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

Background and Objectives

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

Methods

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

Results

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

Discussion

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

Initiation of Antiseizure Medications by US Board-Certified Neurologists After a First Unprovoked Seizure Based on EEG Findings

Background and Objectives

To investigate neurologists' practice variability in antiseizure medication (ASM) initiation after a first unprovoked seizure based on reported EEG interpretations.

Methods

We developed a 15-question multiple-choice survey incorporating a standardized clinical case scenario of a patient with a first unprovoked seizure for whom different EEG reports were provided. The survey was distributed among board-certified neurologists practicing in the United States. Associations between categorical variables were evaluated using the Fisher Exact test. Multivariate analysis was performed using logistic regression.

Results

A total of 106 neurologists responded to the survey. Most responders (75%-95%) would start ASM for definite epileptiform features on EEG, with similar rates between subgroups differing in years of practice, presence of subspecialty EEG training, and self-reported confidence in EEG interpretation. There was greater variability in practice for nonspecific EEG abnormalities, with sharply contoured activity, sharp transients, and focal delta slowing associated with the highest variability and uncertainty. Neurologists with >5 years of practice experience (21% vs 44%, OR 0.35 [95% CI 0.13-0.89], p = 0.021), subspecialty EEG training (15% vs 50%, OR = 0.17 [95% CI 0.06-0.48], p < 0.001), and greater confidence in EEG interpretation (21% vs 52%, OR 0.24 [95% CI 0.09-0.62], p = 0.001) were less likely to start ASM for ≥2 nonspecific EEG abnormalities and reported greater uncertainty. In multivariate analysis, seniority (p = 0.039) and subspecialty EEG training (p = 0.032) were associated with decreased ASM initiation for nonspecific EEG features.

Discussion

There was substantial variability in ASM initiation practices between board-certified neurologists after a first unprovoked seizure with nonspecific EEG abnormalities. These findings clarify specific areas where EEG reporting may be optimized and reinforces the importance of implementing evidence-based practice guidelines.

Critical Care Management of Patients After Cardiac Arrest: A Scientific Statement from the American Heart Association and Neurocritical Care Society

The critical care management of patients after cardiac arrest is burdened by a lack of high-quality clinical studies and the resultant lack of high-certainty evidence. This results in limited practice guideline recommendations, which may lead to uncertainty and variability in management. Critical care management is crucial in patients after cardiac arrest and affects outcome. Although guidelines address some relevant topics (including temperature control and neurological prognostication of comatose survivors, 2 topics for which there are more robust clinical studies), many important subject areas have limited or nonexistent clinical studies, leading to the absence of guidelines or low-certainty evidence. The American Heart Association Emergency Cardiovascular Care Committee and the Neurocritical Care Society collaborated to address this gap by organizing an expert consensus panel and conference. Twenty-four experienced practitioners (including physicians, nurses, pharmacists, and a respiratory therapist) from multiple medical specialties, levels, institutions, and countries made up the panel. Topics were identified and prioritized by the panel and arranged by organ system to facilitate discussion, debate, and consensus building. Statements related to postarrest management were generated, and 80% agreement was required to approve a statement. Voting was anonymous and web based. Topics addressed include neurological, cardiac, pulmonary, hematological, infectious, gastrointestinal, endocrine, and general critical care management. Areas of uncertainty, areas for which no consensus was reached, and future research directions are also included. Until high-quality studies that inform practice guidelines in these areas are available, the expert panel consensus statements that are provided can advise clinicians on the critical care management of patients after cardiac arrest.

Outcome prediction in comatose cardiac arrest patients with initial shockable and non-shockable rhythms

BACKGROUND

Prognosis after out-of-hospital cardiac arrest (OHCA) is presumed poorer in patients with non-shockable than shockable rhythms, frequently leading to treatment withdrawal. Multimodal outcome prediction is recommended 72 h post-arrest in still comatose patients, not considering initial rhythms. We investigated accuracy of outcome predictors in all comatose OHCA survivors, with a particular focus on shockable vs. non-shockable rhythms.

METHODS

In this observational NORCAST sub-study, patients still comatose 72 h post-arrest were stratified by shockable vs. non-shockable rhythms for outcome prediction analyzes. Good outcome was defined as cerebral performance category 1-2 within 6 months. False positive rate (FPR) was used for poor and sensitivity for good outcome prediction accuracy.

RESULTS

Overall, 72/128 (56%) patients with shockable and 12/50 (24%) with non-shockable rhythms had good outcome (p < .001). For poor outcome prediction, absent pupillary light reflexes (PLR) and corneal reflexes (clinical predictors) 72 h after sedation withdrawal, PLR 96 h post-arrest, and somatosensory evoked potentials (SSEP), all had FPR <0.1% in both groups. Unreactive EEG and neuron-specific enolase (NSE) >60 μg/L 24-72 h post-arrest had better precision in shockable patients. For good outcome, the clinical predictors, SSEP and CT, had 86%-100% sensitivity in both groups. For NSE, sensitivity varied from 22% to 69% 24-72 h post-arrest. The outcome predictors indicated severe brain injury proportionally more often in patients with non-shockable than with shockable rhythms. For all patients, clinical predictors, CT, and SSEP, predicted poor and good outcome with high accuracy.

CONCLUSION

Outcome prediction accuracy was comparable for shockable and non-shockable rhythms. PLR and corneal reflexes had best precision 72 h after sedation withdrawal and 96 h post-arrest.

Perioperative Neuromonitoring in Children with Congenital Heart Disease

Although neonates and children with congenital heart disease are primarily hospitalized for cardiac and pulmonary diseases, they are also at an increased risk for neurologic injury due to both empiric differences that can exist in their nervous systems and acquired injury from cardiopulmonary pathology and interventions. Although early efforts in care focused on survival after reparative cardiac surgery, as surgical and anesthetic techniques have evolved and survival rates accordingly improved, the focus has now shifted to maximizing outcomes among survivors. Children and neonates with congenital heart disease experience seizures and poor neurodevelopmental outcomes at a higher rate than age-matched counterparts. The aim of neuromonitoring is to help clinicians identify patients at highest risk for these outcomes to implement strategies to mitigate these risks and to also help with neuroprognostication after an injury has occurred. The mainstays of neuromonitoring are (1) electroencephalographic monitoring to evaluate brain activity for abnormal patterns or changes and to identify seizures, (2) neuroimaging to reveal structural changes and evidence of physical injury in and around the brain, and (3) near-infrared spectroscopy to monitor brain tissue oxygenation and detect changes in perfusion. This review will detail the aforementioned techniques and their use in the care of pediatric patients with congenital heart disease.

Post Cardiac Arrest Care in the Cardiac Intensive Care Unit

PURPOSE OF REVIEW

Cardiac arrests constitute a leading cause of mortality in the adult population and cardiologists are often tasked with the management of patients following cardiac arrest either as a consultant or primary provider in the cardiac intensive care unit. Familiarity with evidence-based practice for post-cardiac arrest care is a requisite for optimizing outcomes in this highly morbid group. This review will highlight important concepts necessary to managing these patients.

RECENT FINDINGS

Emerging evidence has further elucidated optimal care of post-arrest patients including timing for routine coronary angiography, utility of therapeutic hypothermia, permissive hypercapnia, and empiric aspiration pneumonia treatment. The complicated state of multi-organ failure following cardiac arrest needs to be carefully optimized by the clinician to prevent further neurologic injury and promote systemic recovery. Future studies should be aimed at understanding if these findings extend to specific patient populations, especially those at the highest risk for poor outcomes.

Association of Sepsis With Neurologic Outcomes of Adult Patients Treated With Venoarterial Extracorporeal Membrane Oxygnenation

OBJECTIVES

Neurologic outcomes of patients under venoarterial extracorporeal membrane oxygenation (VA-ECMO) may be worsened by secondary insults of systemic origin. We aimed to assess whether sepsis, commonly observed during ECMO support, is associated with brain injury and outcomes.

DESIGN

Single-center cohort study of the "exposed-non-exposed" type on consecutive adult patients treated by VA-ECMO.

SETTING

Medical ICU of a university hospital, France, 2013-2020.

PATIENTS

Patients with sepsis at the time of VA-ECMO cannulation ("sepsis" group) were compared with patients without sepsis ("no sepsis" group). The primary outcome measure was poor functional outcome at 90 days, defined by a score greater than or equal to 4 on the modified Rankin scale (mRS), indicating severe disability or death.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A total of 196 patients were included ("sepsis," n = 128; "no sepsis," n = 68), of whom 87 (44.4%) had presented cardiac arrest before VA-ECMO cannulation. A poor functional outcome (mRS ≥ 4) was observed in 99 of 128 patients (77.3%) of the "sepsis" group and 46 of 68 patients (67.6%) of the "no sepsis" group (adjusted logistic regression odds ratio (OR) 1.21, 95% CI, 0.58-2.47; inverse probability of treatment weighting (IPTW) OR 1.24; 95% CI, 0.79-1.95). Subsequent analyses performed according to pre-ECMO cardiac arrest status suggested that sepsis was independently associated with poorer functional outcomes in the subgroup of patients who had experienced pre-ECMO cardiac arrest (adjusted logistic regression OR 3.44; 95% CI, 1.06-11.40; IPTW OR 3.52; 95% CI, 1.68-7.73), whereas no such association was observed in patients without pre-ECMO cardiac arrest (adjusted logistic regression OR 0.69; 95% CI, 0.27-1.69; IPTW OR 0.76; 95% CI, 0.42-1.35). Compared with the "no sepsis" group, "sepsis" patients presented a significant increase in S100 calcium-binding protein beta concentrations at day 1 (0.94 μg/L vs. 0.52 μg/L, p = 0.03), and more frequent EEG alterations (i.e., severe slowing, discontinuous background, and a lower prevalence of sleep patterns), suggesting brain injury.

CONCLUSION

We observed a detrimental role of sepsis on neurologic outcomes in the subgroup of patients who had experienced pre-ECMO cardiac arrest, but not in other patients.

Impact of an Interactive, Animation-Based Electroencephalography Curriculum on Learner Confidence and Knowledge

BACKGROUND

There is a national need for innovative electroencephalography (EEG) education with efficacy evaluated by rigorous statistical analysis. We created a dynamic, online resource that includes a series of animated videos at a single academic medical center.

METHODS

For the animations and interactive module, we used VideoScribe and Articulate, respectively. The module comprised three chapters: (1) Origin & Technical Aspects of EEG, (2) Normal Adult EEG in Wakefulness & Sleep, and (3) Abnormal EEG, with appendices on artifacts, variants, activation procedures, seizure/epilepsy classification, and neonatal/pediatric EEG. The curriculum and knowledge assessments were reviewed independently by two fellowship-trained physicians before distribution. Linear mixed-effects models with bootstrapping were used to compare paired pre- and post-tests as well as Likert scale questionnaires.

RESULTS

Forty-nine learners participated in the pretest survey; 38 matched participants completed post-tests (78%). Learners across fields perceived benefit (100% would recommend to colleagues), indicated improved self-efficacy (P < 0.0001), and performed better on post-test knowledge assessments (54.1 vs 88.2%, P < 0.0001). In the neurology providers subgroup (n = 20), pretest scores correlated with years in training (Spearman r = 0.52, P = 0.039), neurology rotations (r = 0.70, P = 0.003), epilepsy/EEG rotations (r = 0.6, P = 0.014), and EEG teaching hours (r = 0.62, P = 0.01); content knowledge and self-efficacy improvement for neurology providers remained significant in a multivariate model adjusting for these covariates.

CONCLUSIONS

This animation-based, interactive EEG module proved effective in elevating learner confidence and knowledge across several medical specialties and training levels. Further study across institutions and subspecialties is needed to substantiate broad applicability, but our data appear promising for early EEG learners.

2023 American Heart Association Focused Update on Adult Advanced Cardiovascular Life Support: An Update to the American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care

Cardiac arrest is common and deadly, affecting up to 700 000 people in the United States annually. Advanced cardiac life support measures are commonly used to improve outcomes. This "2023 American Heart Association Focused Update on Adult Advanced Cardiovascular Life Support" summarizes the most recent published evidence for and recommendations on the use of medications, temperature management, percutaneous coronary angiography, extracorporeal cardiopulmonary resuscitation, and seizure management in this population. We discuss the lack of data in recent cardiac arrest literature that limits our ability to evaluate diversity, equity, and inclusion in this population. Last, we consider how the cardiac arrest population may make up an important pool of organ donors for those awaiting organ transplantation.

Association Between Dose Escalation of Anesthetics and Outcomes in Patients With Refractory Status Epilepticus

BACKGROUND AND OBJECTIVES

To investigate the association between dose escalation of continuously administered IV anesthetics and its duration with short-term outcomes in adult patients treated for refractory status epilepticus (RSE).

METHODS

Clinical and electroencephalographic data of patients with RSE without hypoxic-ischemic encephalopathy who were treated with anesthetics at a Swiss academic medical center from 2011 to 2019 were assessed. The frequency of anesthetic dose escalation (i.e., dose increase) and its associations with in-hospital death or return to premorbid neurologic function were primary endpoints. Multivariable logistic regression analysis was performed to identify associations with endpoints.

RESULTS

Among 111 patients with RSE, doses of anesthetics were escalated in 57%. Despite patients with dose escalation having a higher morbidity (lower Glasgow Coma Scale [GCS] score at status epilepticus [SE] onset, more presumably fatal etiologies, longer duration of SE and intensive care, more infections, and arterial hypotension) as compared with patients without, the primary endpoints did not differ between these groups in univariable analyses. Multivariable analyses revealed decreased odds for death with dose escalation (odds ratio 0.09, 95% CI 0.01-0.86), independent of initial GCS score, presumably fatal etiology, SE severity score, SE duration, and nonconvulsive SE with coma, with similar functional outcome among survivors compared with patients without dose escalation.

DISCUSSION

Our study reveals that anesthetic dose escalation in adult patients with RSE is associated with decreased odds for death without increasing the proportion of surviving patients with worse neurofunctional state than before RSE.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that anesthetic dose escalation decreases the odds of death in patients with RSE.

Critical Care Management of Patients After Cardiac Arrest: A Scientific Statement From the American Heart Association and Neurocritical Care Society

The critical care management of patients after cardiac arrest is burdened by a lack of high-quality clinical studies and the resultant lack of high-certainty evidence. This results in limited practice guideline recommendations, which may lead to uncertainty and variability in management. Critical care management is crucial in patients after cardiac arrest and affects outcome. Although guidelines address some relevant topics (including temperature control and neurological prognostication of comatose survivors, 2 topics for which there are more robust clinical studies), many important subject areas have limited or nonexistent clinical studies, leading to the absence of guidelines or low-certainty evidence. The American Heart Association Emergency Cardiovascular Care Committee and the Neurocritical Care Society collaborated to address this gap by organizing an expert consensus panel and conference. Twenty-four experienced practitioners (including physicians, nurses, pharmacists, and a respiratory therapist) from multiple medical specialties, levels, institutions, and countries made up the panel. Topics were identified and prioritized by the panel and arranged by organ system to facilitate discussion, debate, and consensus building. Statements related to postarrest management were generated, and 80% agreement was required to approve a statement. Voting was anonymous and web based. Topics addressed include neurological, cardiac, pulmonary, hematological, infectious, gastrointestinal, endocrine, and general critical care management. Areas of uncertainty, areas for which no consensus was reached, and future research directions are also included. Until high-quality studies that inform practice guidelines in these areas are available, the expert panel consensus statements that are provided can advise clinicians on the critical care management of patients after cardiac arrest.

Comparison of induction agents for rapid sequence intubation in refractory status epilepticus: A single-center retrospective analysis

Endotracheal intubation, frequently required during management of refractory status epilepticus (RSE), can be facilitated by anesthetic medications; however, their effectiveness for RSE control is unknown. We performed a single-center retrospective review of patients admitted to a neurocritical care unit (NCCU) who underwent in-hospital intubation during RSE management. Patients intubated with propofol, ketamine, or benzodiazepines, termed anti-seizure induction (ASI), were compared to patients who received etomidate induction (EI). The primary endpoint was clinical or electrographic seizures within 12 h post-intubation. We estimated the association of ASI on post-intubation seizure using logistic regression. A sub-group of patients undergoing electroencephalography during intubation was identified to evaluate the immediate effect of ASI on RSE. We screened 697 patients admitted to the NCCU for RSE and identified 148 intubated in-hospital (n = 90 ASI, n = 58 EI). There was no difference in post-intubation seizure (26 % (n = 23) ASI, 29 % (n = 17) EI) in the cohort, however, there was increased RSE resolution with ASI in 24 patients with electrographic RSE during intubation (ASI: 61 % (n = 11/18) vs EI: 0 % (n = 0/6), p =.016). While anti-seizure induction did not appear to affect post-intubation seizure occurrence overall, a sub-group of patients undergoing electroencephalography during intubation had a higher incidence of seizure cessation, suggesting potential benefit in an enriched population.

Brain tumor-related epilepsy management: A Society for Neuro-oncology (SNO) consensus review on current management

Tumor-related epilepsy (TRE) is a frequent and major consequence of brain tumors. Management of TRE is required throughout the course of disease and a deep understanding of diagnosis and treatment is key to improving quality of life. Gross total resection is favored from both an oncologic and epilepsy perspective. Shared mechanisms of tumor growth and epilepsy exist, and emerging data will provide better targeted therapy options. Initial treatment with antiseizure medications (ASM) in conjunction with surgery and/or chemoradiotherapy is typical. The first choice of ASM is critical to optimize seizure control and tolerability considering the effects of the tumor itself. These agents carry a potential for drug-drug interactions and therefore knowledge of mechanisms of action and interactions is needed. A review of adverse effects is necessary to guide ASM adjustments and decision-making. This review highlights the essential aspects of diagnosis and treatment of TRE with ASMs, surgery, chemotherapy, and radiotherapy while indicating areas of uncertainty. Future studies should consider the use of a standardized method of seizure tracking and incorporating seizure outcomes as a primary endpoint of tumor treatment trials.

Sustained effort network for treatment of status epilepticus/European academy of neurology registry on adult refractory status epilepticus (SENSE-II/AROUSE)

BACKGROUND

Status Epilepticus (SE) is a common neurological emergency associated with a high rate of functional decline and mortality. Large randomized trials have addressed the early phases of treatment for convulsive SE. However, evidence regarding third-line anesthetic treatment and the treatment of nonconvulsive status epilepticus (NCSE) is scarce. One trial addressing management of refractory SE with deep general anesthesia was terminated early due to insufficient recruitment. Multicenter prospective registries, including the Sustained Effort Network for treatment of Status Epilepticus (SENSE), have shed some light on these questions, but many answers are still lacking, such as the influence exerted by distinct EEG patterns in NCSE on the outcome. We therefore initiated a new prospective multicenter observational registry to collect clinical and EEG data that combined may further help in clinical decision-making and defining SE.

METHODS

Sustained effort network for treatment of status epilepticus/European Academy of Neurology Registry on refractory Status Epilepticus (SENSE-II/AROUSE) is a prospective, multicenter registry for patients treated for SE. The primary objectives are to document patient and SE characteristics, treatment modalities, EEG, neuroimaging data, and outcome of consecutive adults admitted for SE treatment in each of the participating centers and to identify factors associated with outcome and refractoriness. To reach sufficient statistical power for multivariate analysis, a cohort size of 3000 patients is targeted.

DISCUSSION

The data collected for the registry will provide both valuable EEG data and information about specific treatment steps in different patient groups with SE. Eventually, the data will support clinical decision-making and may further guide the planning of clinical trials. Finally, it could help to redefine NCSE and its management.

TRIAL REGISTRATION

NCT number: NCT05839418.

Assessing risk factors associated with breakthrough early post-traumatic seizures in patients receiving phenytoin prophylaxis

Objective

Post-traumatic seizure (PTS) is a well-known complication of traumatic brain injury (TBI). The objective of this study was to identify risk factors associated with breakthrough early PTS in TBI patients receiving phenytoin prophylaxis.

Methods

This was a single-centered retrospective study including adult patients admitted to the intensive care unit (ICU), had a TBI, and started on phenytoin for seizure prophylaxis within 24 h of admission. The primary outcome was the incidence and factors associated with early PTS, defined as a confirmed seizure on a continuous electroencephalogram within 7 days of TBI. Secondary outcomes included the association between early post-traumatic seizures and ICU length of stay, hospital length of stay, and in-hospital mortality.

Results

A total of 105 patients were included in the final analysis. Patients with early PTS were older (65 vs. 48 years old, p = 0.01), had a higher Marshall score (5 vs. 2, p = 0.01), were more likely to have a Marshall score > 2 (73 vs. 37%, p = 0.01), and had more neurosurgeries for hematoma evacuation (57 vs. 19%, p = 0.01). In patients with early PTS, 57% had a level at the time of seizure, and of those, 87.5% had a therapeutic level (>10 mcg/mL). Patients with early PTS had a longer ICU length of stay (14.7 vs. 5.9 days, p = 0.04) and a greater proportion of hospital mortality (21 vs. 2%, p = 0.02).

Conclusion

Patients with higher age, Marshall score, and neurosurgical procedures for hematoma evacuation had higher incidences of breakthrough early PTS despite the use of phenytoin prophylaxis. The majority of patients with early PTS had therapeutic phenytoin levels at the time of seizure when a level was available; however, approximately half (43%) did not have a level.

Neuroimaging correlation with EEG in status epilepticus

PURPOSE

This study was to correlate EEG patterns with peri‑ictal perfusion CT abnormality (PCA) or peri‑ictal MR abnormality (PMA) in patients with status epilepticus (SE).

METHODS

This is a retrospective study done with SE patients from January 2016 to December 2021. We defined the PCA as single or multi-territorial cortical and/or thalamic hyper-perfusion. The PMA was defined as increased signal intensity in multiple brain regions including the cortex and subcortical regions. EEG patterns were categorized into electrographic seizure (ESz)/electroclinical seizure (ECSz), ictal-interictal continuum (IIC), and lateralized periodic discharges (LPDs) per the American Clinical Neurophysiology Society's guideline. We analyzed the association between the patterns of EEG and the presence of PCA or PMA.

RESULTS

Among 73 patients, 26 % (19/73) showed PCA and 25 % (18/73) demonstrated PMA. The patterns of EEG were as follows; ESz/ECSz in 25 % (18/73), IIC in 34 % (25/73), and LPD in 12 % (9/73). There was a significant correlation between the patterns of EEG and the presence of PMA, but not PCA. 48 % (12/25) had both PMA and PCA whereas 52 % (13/25) showed either PMA (6/25) or PCA (7/25).

CONCLUSION

Although PCA did not reveal an electro-radiographical correlation, PMA was strongly linked to ESz, ECSz, IIC, and LPD.

Distinct Spectral Profiles of Awake Resting EEG in Disorders of Consciousness: The Role of Frequency and Topography of Oscillations

The prolonged disorders of consciousness (PDOC) pose a challenge for an accurate clinical diagnosis, mainly due to patients' scarce or ambiguous behavioral responsiveness. Measurement of brain activity can support better diagnosis, independent of motor restrictions. Methods based on spectral analysis of resting-state EEG appear as a promising path, revealing specific changes within the internal brain dynamics in PDOC patients. In this study we used a robust method of resting-state EEG power spectrum parameter extraction to identify distinct spectral properties for different types of PDOC. Sixty patients and 37 healthy volunteers participated in this study. Patient group consisted of 22 unresponsive wakefulness patients, 25 minimally conscious patients and 13 patients emerging from the minimally conscious state. Ten minutes of resting EEG was acquired during wakefulness and transformed into individual power spectra. For each patient, using the spectral decomposition algorithm, we extracted maximum peak frequency within 1-14 Hz range in the centro-parietal region, and the antero-posterior (AP) gradient of the maximal frequency peak. All patients were behaviorally diagnosed using coma recovery scale-revised (CRS-R). The maximal peak frequency in the 1-14 Hz range successfully predicted both neurobehavioral capacity of patients as indicated by CRS-R total score and PDOC diagnosis. Additionally, in patients in whom only one peak within the 1-14 Hz range was observed, the AP gradient significantly contributed to the accuracy of prediction. We have identified three distinct spectral profiles of patients, likely representing separate neurophysiological modes of thalamocortical functioning. Etiology did not have significant influence on the obtained results.

Optimal Dosing of Levetiracetam for Seizure Prophylaxis in Critically Ill Patients: A Prospective Observational Study

OBJECTIVES

Critically ill patients eliminate levetiracetam (LEV) more rapidly than healthy controls, yet low doses are commonly used for seizure prophylaxis in the ICU setting. We compared the rates of achievement of target serum levels and new onset seizure (clinical and/or electrographic) among patients who received low (500 mg bid) versus high (750-1,000 mg bid) dose LEV.

DESIGN

Prospective, observational study.

SETTING

Tertiary care, academic center.

PATIENTS

We included patients who received prophylactic LEV following traumatic brain injury, intracerebral hemorrhage, spontaneous subarachnoid hemorrhage, or supratentorial neurosurgery between 2019 and 2021. Patients with a history of seizure, antiseizure medication use, or renal failure requiring dialysis were excluded.

INTERVENTIONS

None.

MEASUREMENTS

LEV levels were obtained at steady state. The impact of low-dose versus high-dose LEV on the primary outcome of target LEV levels (12-46 μg/mL), and the secondary outcome of clinical and/or electrographic seizure, were assessed using multivariable logistic regression analyses adjusting for age, LEV loading dose, BMI, primary diagnosis and creatinine clearance (CrCl).

MAIN RESULTS

Of the 205 subjects included in analyses, n = 106 (52%) received LEV 500 mg bid (median 13 mg/kg/d), and n = 99 (48%) received LEV 750-1,000 mg bid (median 25 mg/kg/d). Overall, 111 of 205 patients (54%) achieved target levels: 48 (45%) from the low-dose group versus 63 (64%) from the high-dose group (odds ratio [OR] 2.1; 95% CI, 1.1-3.7; p = 0.009). In multivariable analyses, high-dose LEV predicted target levels (adjusted OR [aOR] 2.23; 95% CI, 1.16-4.27; p = 0.016), and was associated with lower seizure odds (aOR 0.32; 95% CI, 0.13-0.82; p = 0.018) after adjusting for age, loading dose, BMI, diagnosis, and CrCl.

CONCLUSIONS

Underdosing of LEV was common, with only 54% of patients achieving target serum levels. Higher doses (750-1,000 mg bid) were more than twice as likely to lead to optimal drug levels and reduced the odds of seizure by 68% compared with low-dose regimens (500 mg bid).

Status epilepticus in the ICU

Status epilepticus (SE) is a common medical emergency associated with significant morbidity and mortality. Management that follows published guidelines is best suited to improve outcomes, with the most severe cases frequently being managed in the intensive care unit (ICU). Diagnosis of convulsive SE can be made without electroencephalography (EEG), but EEG is required to reliably diagnose nonconvulsive SE. Rapidly narrowing down underlying causes for SE is crucial, as this may guide additional management steps. Causes may range from underlying epilepsy to acute brain injuries such as trauma, cardiac arrest, stroke, and infections. Initial management consists of rapid administration of benzodiazepines and one of the following non-sedating intravenous antiseizure medications (ASM): (fos-)phenytoin, levetiracetam, or valproate; other ASM are increasingly used, such as lacosamide or brivaracetam. SE that continues despite these medications is called refractory, and most commonly treated with continuous infusions of midazolam or propofol. Alternatives include further non-sedating ASM and non-pharmacologic approaches. SE that reemerges after weaning or continues despite management with propofol or midazolam is labeled super-refractory SE. At this step, management may include non-sedating or sedating compounds including ketamine and barbiturates. Continuous video EEG is necessary for the management of refractory and super-refractory SE, as these are almost always nonconvulsive. If possible, management of the underlying cause of seizures is crucial particularly for patients with autoimmune encephalitis. Short-term mortality ranges from 10 to 15% after SE and is primarily related to increasing age, underlying etiology, and medical comorbidities. Refractoriness of treatment is clearly related to outcome with mortality rising from 10% in responsive cases, to 25% in refractory, and nearly 40% in super-refractory SE.

Prevalence of nonconvulsive seizures and nonconvulsive status epilepticus in dogs and cats with a history of cluster seizures: A retrospective study

BACKGROUND

Nonconvulsive seizures (NCS) and nonconvulsive status epilepticus (NCSE) are frequently observed in human patients. Diagnosis of NCS and NCSE only can be achieved by the use of electroencephalography (EEG). Electroencephalographic monitoring is rare in veterinary medicine and consequently there is limited data on frequency of NCS and NCSE.

OBJECTIVES

Determine the prevalence of NCS and NCSE in dogs and cats with a history of cluster seizures.

ANIMALS

Twenty-six dogs and 12 cats.

METHODS

Retrospective study. Medical records of dogs and cats with cluster seizures were reviewed. Electroencephalography was performed in order to identify electrographic seizure activity after the apparent cessation of convulsive seizure activity.

RESULTS

Nonconvulsive seizures were detected in 9 dogs and 2 cats out of the 38 patients (29%). Nonconvulsive status epilepticus was detected in 4 dogs and 2 cats (16%). Five patients had both NCS and NCSE. A decreased level of consciousness was evident in 6/11 patients with NCS, 3/6 also had NCSE. Mortality rate for patients with NCS (73%) and NCSE (67%) was much higher than that for patients with no seizure activity on EEG (27%).

CONCLUSION AND CLINICAL IMPORTANCE

Prevalence of NCS and NCSE is high in dogs and cats with a history of cluster seizures. Nonconvulsive seizures and NCSE are difficult to detect clinically and are associated with higher in hospital mortality rates. Results indicate that prompt EEG monitoring should be performed in dogs and cats with cluster seizures.

The predictive value of highly malignant EEG patterns after cardiac arrest: evaluation of the ERC-ESICM recommendations

PURPOSE

The 2021 guidelines endorsed by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) recommend using highly malignant electroencephalogram (EEG) patterns (HMEP; suppression or burst-suppression) at > 24 h after cardiac arrest (CA) in combination with at least one other concordant predictor to prognosticate poor neurological outcome. We evaluated the prognostic accuracy of HMEP in a large multicentre cohort and investigated the added value of absent EEG reactivity.

METHODS

This is a pre-planned prognostic substudy of the Targeted Temperature Management trial 2. The presence of HMEP and background reactivity to external stimuli on EEG recorded > 24 h after CA was prospectively reported. Poor outcome was measured at 6 months and defined as a modified Rankin Scale score of 4-6. Prognostication was multimodal, and withdrawal of life-sustaining therapy (WLST) was not allowed before 96 h after CA.

RESULTS

845 patients at 59 sites were included. Of these, 579 (69%) had poor outcome, including 304 (36%) with WLST due to poor neurological prognosis. EEG was recorded at a median of 71 h (interquartile range [IQR] 52-93) after CA. HMEP at > 24 h from CA had 50% [95% confidence interval [CI] 46-54] sensitivity and 93% [90-96] specificity to predict poor outcome. Specificity was similar (93%) in 541 patients without WLST. When HMEP were unreactive, specificity improved to 97% [94-99] (p = 0.008).

CONCLUSION

The specificity of the ERC-ESICM-recommended EEG patterns for predicting poor outcome after CA exceeds 90% but is lower than in previous studies, suggesting that large-scale implementation may reduce their accuracy. Combining HMEP with an unreactive EEG background significantly improved specificity. As in other prognostication studies, a self-fulfilling prophecy bias may have contributed to observed results.

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.

Curriculum Innovation: Design and Implementation of Synchronous and Asynchronous Curricula to Enhance Residents' EEG Knowledge and Experience

Introduction and Problem Statement

There is a need for structured EEG education opportunities to enhance neurology resident education. To address this need, the American Epilepsy Society (AES) supported the development and implementation of both synchronous and asynchronous EEG courses.

Objectives

To produce EEG curricula that enhance resident EEG learning, increase interest in EEG and improve participants' knowledge, and to ensure that courses were highly used and available to the broadest range of learners.

Methods and Curriculum Description

A multi-institutional group of EEG educators developed both courses. The synchronous curriculum consisted of a mixture of brief "mini-lectures" and interactive small group activities with self-assessment quizzes at the start and end of the course. The online asynchronous EEG curriculum consisted of self-directed slide sets, multiple-choice self-assessment quizzes and a structured EEG self-assessment tool. Courses were evaluated using postcourse surveys, analysis of pretest and posttest data, and analysis of user data from the asynchronous curriculum.

Results and Assessment Data

Between 2019 and 2021, 56 residents participated in the synchronous EEG courses. On the resident survey, mean Likert scores for course design, planning, and learning outcomes ranged from 4.6 to 5.0 for the in-person courses and from 3.9 to 4.5 for the virtual course. On the 24-item pretests and posttests, overall median scores increased from 60% (14.5/24) to 75% (18/24; p < 0.001). More than 2,300 learners completed the first submodule of the asynchronous curriculum, but only 164 completed all sections. Most of those who completed the asynchronous curriculum reported that it was effective and appropriate for resident-level learning.

Discussion and Lessons Learned

The AES EEG courses provide EEG learning opportunities for neurology residents beyond what is available at their home institutions. There is evidence for the effectiveness of the synchronous course, but the scope is limited to a small number of attendees. The asynchronous curriculum is more broadly available, but very few learners completed all elements. Future steps will include expansion of the in-person synchronous course and providing guidance to learners about the core and optional components of the asynchronous curriculum to increase the impact of both educational offerings.

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.