Seizure burden in subarachnoid hemorrhage associated with functional and cognitive outcome

Association of Time to Continuous EEG Initiation With Outcomes in Critically Ill Patients

PURPOSE

Continuous electroencephalography (cEEG) is used in the critical care setting for seizure detection and treatment, sedation management, and ischemia detection. Further evidence is needed to support whether early cEEG use can improve outcomes. We examined whether time from admission to cEEG initiation affects outcomes.

METHODS

This is a single-center cohort study of critically ill adults (age > 18 years) who underwent cEEG monitoring within 7 days of admission from January to December 2019. Patients with anoxic brain injury were excluded. Time (hours) from admission to cEEG was recorded. Outcomes were in-hospital mortality and poor discharge modified Rankin Score (4-6). Results are reported as median [quartile range] and odds ratio (OR) [confidence intervals, CI].

RESULTS

In total, 464 patients met eligibility. Median time to cEEG was 23 hours [13, 52]. On multivariable analysis, increasing time to cEEG was associated with discharge mortality (OR, 1.006 [CI, 1.0002-1.013], 0.1%/hour [CI, 0.02-0.2]) and poor outcome (OR, 1.013 [CI, 1.005-1.020], 0.2%/hour [CI, 0.07-0.3]). Median time to cEEG initiation in patients with clinical concern for seizures/status at presentation (n = 121) was 12 hours [6, 17] and in patients without clinical concern for seizures at presentation (n = 343) was 31 hours [18, 66]. In patients without clinical concern for seizures/status epilepticus at presentation, time to cEEG continued to be associated with mortality (OR, 1.007 [CI, 1.001-1.014)] and poor outcome (OR, 1.012 [CI, 1.003-1.021]).

CONCLUSIONS

Increasing time to cEEG initiation was associated with higher mortality and worse outcomes. We hypothesize earlier cEEG results in timely interventions including treatment escalation and de-escalation that may improve outcomes.

Feasibility Assessment of Rapid Response EEG in the Identification of Nonconvulsive Seizures During Military Medical Air Transport

INTRODUCTION

Traumatic brain injury often requires neurologic care and specialized equipment, not often found downrange. Nonconvulsive seizures (NCSs) and nonconvulsive status epilepticus (NCSE) occur in up to 30% of patients with moderate or severe traumatic brain injury and is associated with a 39% morbidity and an 18% mortality. It remains difficult to identify at bedside because of the heterogeneous clinical manifestations. The primary diagnostic tool is an electroencephalogram (EEG) which is large, requires an external power source, and requires a specialized technician and neurologist to collect and interpret the data. Rapid response EEG (rr-EEG) is an FDA-approved device that is pocket sized and battery powered and uses a disposable 10-electrode headset. Prior studies have demonstrated the noninferiority of rr-EEG in the identification of NCSE and NCS as compared to conventional EEG in hospitals. An unanswered question is whether rr-EEG could be used in the identification of NCSE and NCS by medics.

MATERIALS AND METHODS

In conjunction with the Critical Care Air Transport (CCAT) team, a simulation was created and implemented on a CCAT training mission. The simulation team included a neurology resident, who oversaw the simulation, a pulmonary critical care fellow, an intensive care unit nurse, and a respiratory therapy. A survey was provided before and after the simulation. The team was expected to review the rr-EEG to make clinical decisions during ground transport, takeoff, and landing. The neurology resident monitored and recorded the team's ability to distinguish between NCS and a normal EEG. In between, the neurology resident monitored the quality of the EEG for potential interference and loss of quality.

RESULTS

The CCAT team was able to efficiently set up the rr-EEG on a patient manikin, correctly identify visual EEG wave forms of a patient in NCS, and utilize the proprietary audio program of a simulated patient in NCS. The team reported that the device was easily set up in the environment, and the data were interpretable despite vibration, aircraft auditory and electrical noise, and the ergonomics of the aircraft medical section.

CONCLUSIONS

This pilot study has validated a potentially revolutionary technology in medical transport. The rr-EEG technology is measurably user-friendly and will improve patient outcomes. This device and simulation can reduce time to an EEG by hours to days allowing for immediate treatment and intervention, which can significantly reduce morbidity and mortality.

Evaluating the Impact of Point-of-Care Electroencephalography on Length of Stay in the Intensive Care Unit: Subanalysis of the SAFER-EEG Trial

BACKGROUND

Electroencephalography (EEG) is needed to diagnose nonconvulsive seizures. Prolonged nonconvulsive seizures are associated with neuronal injuries and deleterious clinical outcomes. However, it is uncertain whether the rapid identification of these seizures using point-of-care EEG (POC-EEG) can have a positive impact on clinical outcomes.

METHODS

In a retrospective subanalysis of the recently completed multicenter Seizure Assessment and Forecasting with Efficient Rapid-EEG (SAFER-EEG) trial, we compared intensive care unit (ICU) length of stay (LOS), unfavorable functional outcome (modified Rankin Scale score ≥ 4), and time to EEG between adult patients receiving a US Food and Drug Administration-cleared POC-EEG (Ceribell, Inc.) and those receiving conventional EEG (conv-EEG). Patient records from January 2018 to June 2022 at three different academic centers were reviewed, focusing on EEG timing and clinical outcomes. Propensity score matching was applied using key clinical covariates to control for confounders. Medians and interquartile ranges (IQRs) were calculated for descriptive statistics. Nonparametric tests (Mann-Whitney U-test) were used for the continuous variables, and the χ2 test was used for the proportions.

RESULTS

A total of 283 ICU patients (62 conv-EEG, 221 POC-EEG) were included. The two populations were matched using demographic and clinical characteristics. We found that the ICU LOS was significantly shorter in the POC-EEG cohort compared to the conv-EEG cohort (3.9 [IQR 1.9-8.8] vs. 8.0 [IQR 3.0-16.0] days, p = 0.003). Moreover, modified Rankin Scale functional outcomes were also different between the two EEG cohorts (p = 0.047).

CONCLUSIONS

This study reveals a significant association between early POC-EEG detection of nonconvulsive seizures and decreased ICU LOS. The POC-EEG differed from conv-EEG, demonstrating better functional outcomes compared with the latter in a matched analysis. These findings corroborate previous research advocating the benefit of early diagnosis of nonconvulsive seizure. The causal relationship between the type of EEG and metrics of interest, such as ICU LOS and functional/clinical outcomes, needs to be confirmed in future prospective randomized studies.

Accuracy of a Rapid-Response EEG's Automated Seizure-Burden Estimator: AccuRASE Study

BACKGROUND AND OBJECTIVES

The use of rapid response EEG (rr-EEG) has recently expanded in limited-resource settings and as a supplement to conventional EEG to rapidly detect and treat nonconvulsive status epilepticus. The study objective was to test the accuracy of an rr-EEG's automated seizure burden estimator (ASBE).

METHODS

This is a retrospective observational study using multiple blinded reviewers. All consecutive clinical rr-EEG procedures performed between November 2019 and February 2021 at Yale New Haven Hospital, one affiliated community hospital, and one affiliated inner-city regional hospital were included. Three reviewers blindly reviewed each EEG. The reference standard was 2/3 agreement. The co-primary outcome measures were the negative predictive value (NPV) of the ASBE for the detection of electrographic status epilepticus (ESE) or possible ESE (ESE/pESE) (to be used as a screening method to exclude ESE without the need for urgent expert review) and the positive predictive value (PPV, to be used for immediate treatment without requiring urgent expert review). These were assessed using a variety of seizure burden cutoffs determined by the algorithm (>1%, >10%, >20%, >50%, and >90%).

RESULTS

In the first 2 hours, a >10% burden cutoff detected 86% (95% CI 42%-100%) of studies with ESE alone and 88% (68%-97%) with ESE/pESE; this >10% cutoff had a NPV of 99% (97%-100%) for ESE and 98% (95%-100%) for ESE/pESE. The specificity at this threshold was 79% (73%-84%) for ESE and 84% (79%-89%) for ESE/pESE, but the PPV was low at 11% (4%-23%) for ESE and 39% (26%-53%) for ESE/pESE. A >90% burden cutoff was 97% (94%-99%) specific for detecting ESE (PPV 33% [7%-70%]) and 99% (97%-100%) specific for detecting ESE/pESE [PPV 78% (40%-97%)], although the sensitivity dropped significantly to 29% (13%-51%) for ESE/pESE and 43% (10%-82%) for ESE at the >90% threshold.

DISCUSSION

The ASBE has high specificity at >90% seizure burden threshold for detecting ESE and ESE/pESE, with good PPV for ESE/pESE, though with only low-to-moderate sensitivity; at this threshold, it can be used to help triage patients for immediate treatment/transfer, urgent expert review, and additional CEEG. A >10% threshold has a high sensitivity, detecting approximately 85% of patients with ESE; at this lower cutoff, it can be used as a screening tool to exclude ESE with >95% NPV.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that ASBE software can reliably exclude ESE (98% negative predictive value using a <10% burden cutoff) without expert review in most patients requiring rapid response EEG.

Using artificial intelligence to optimize anti-seizure treatment and EEG-guided decisions in severe brain injury

Electroencephalography (EEG) is invaluable in the management of acute neurological emergencies. Characteristic EEG changes have been identified in diverse neurologic conditions including stroke, trauma, and anoxia, and the increased utilization of continuous EEG (cEEG) has identified potentially harmful activity even in patients without overt clinical signs or neurologic diagnoses. Manual annotation by expert neurophysiologists is a major resource limitation in investigating the prognostic and therapeutic implications of these EEG patterns and in expanding EEG use to a broader set of patients who are likely to benefit. Artificial intelligence (AI) has already demonstrated clinical success in guiding cEEG allocation for patients at risk for seizures, and its potential uses in neurocritical care are expanding alongside improvements in AI itself. We review both current clinical uses of AI for EEG-guided management as well as ongoing research directions in automated seizure and ischemia detection, neurologic prognostication, and guidance of medical and surgical treatment.

Neurologic prognostication in coma and disorders of consciousness

Coma and disorders of consciousness (DoC) are clinical syndromes primarily resulting from severe acute brain injury, with uncertain recovery trajectories that often necessitate prolonged supportive care. This imposes significant socioeconomic burdens on patients, caregivers, and society. Predicting recovery in comatose patients is a critical aspect of neurocritical care, and while current prognostication heavily relies on clinical assessments, such as pupillary responses and motor movements, which are far from precise, contemporary prognostication has integrated more advanced technologies like neuroimaging and electroencephalogram (EEG). Nonetheless, neurologic prognostication remains fraught with uncertainty and significant inaccuracies and is impacted by several forms of prognostication biases, including self-fulfilling prophecy bias, affective forecasting, and clinician treatment biases, among others. However, neurologic prognostication in patients with disorders of consciousness impacts life-altering decisions including continuation of treatment interventions vs withdrawal of life-sustaining therapies (WLST), which have a direct influence on survival and recovery after severe acute brain injury. In recent years, advancements in neuro-monitoring technologies, artificial intelligence (AI), and machine learning (ML) have transformed the field of prognostication. These technologies have the potential to process vast amounts of clinical data and identify reliable prognostic markers, enhancing prediction accuracy in conditions such as cardiac arrest, intracerebral hemorrhage, and traumatic brain injury (TBI). For example, AI/ML modeling has led to the identification of new states of consciousness such as covert consciousness and cognitive motor dissociation, which may have important prognostic significance after severe brain injury. This chapter reviews the evolving landscape of neurologic prognostication in coma and DoC, highlights current pitfalls and biases, and summarizes the integration of clinical examination, neuroimaging, biomarkers, and neurophysiologic tools for prognostication in specific disease states. We will further discuss the future of neurologic prognostication, focusing on the integration of AI and ML techniques to deliver more individualized and accurate prognostication, ultimately improving patient outcomes and decision-making process in neurocritical care.

ICU-Electroencephalogram Unit Improves Outcome in Status Epilepticus Patients: A Retrospective Before-After Study

OBJECTIVES

Continuous electroencephalogram (cEEG) monitoring is recommended for status epilepticus (SE) management in ICU but is still underused due to resource limitations and inconclusive evidence regarding its impact on outcome. Furthermore, the term "continuous monitoring" often implies continuous recording with variable intermittent review. The establishment of a dedicated ICU-electroencephalogram unit may fill this gap, allowing cEEG with nearly real-time review and multidisciplinary management collaboration. This study aimed to evaluate the effect of ICU-electroencephalogram unit establishing on SE outcome and management.

DESIGN

Single-center retrospective before-after study.

SETTING

Neuro-ICU of a Swiss academic tertiary medical care center.

PATIENTS

Adult patients treated for nonhypoxic SE between November 1, 2015, and December 31, 2023.

INTERVENTIONS

None.

MEASUREMENT AND MAIN RESULTS

Data from all SE patients were assessed, comparing those treated before and after ICU-electroencephalogram unit introduction. Primary outcomes were return to premorbid neurologic function, ICU mortality, SE duration, and ICU SE management. Secondary outcomes were SE type and etiology. Two hundred seven SE patients were included, 149 (72%) before and 58 (38%) after ICU-electroencephalogram unit establishment. ICU-electroencephalogram unit introduction was associated with increased detection of nonconvulsive SE ( p = 0.003) and SE due to acute symptomatic etiology ( p = 0.019). Regression analysis considering age, comorbidities, SE etiology, and SE semeiology revealed a higher chance of returning to premorbid neurologic function ( p = 0.002), reduced SE duration ( p = 0.024), and a shift in SE management with increased use of antiseizure medications ( p = 0.007) after ICU-electroencephalogram unit introduction.

CONCLUSIONS

Integrating neurology expertise in the ICU setting through the establishment of an ICU-electroencephalogram unit with nearly real-time cEEG review, shortened SE duration, and increased likelihood of returning to premorbid neurologic function, with an increased number of antiseizure medications used. Further studies are warranted to validate these findings and assess long-term prognosis.

[Utility of EEG in neurological emergencies and critical care]

EEG is useful for evaluation of pathophysiology and prognostication of neurocritically ill patients, as it provides non-invasive, real-time monitoring of cerebral function. There have been recently a lot of advances in research on critical care EEG according to the American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology. Based on the latest knowledge, this review discusses clinical utilization of EEG in neurocritically ill patients, including critical care continuous EEG monitoring, and key points of interpretation of critical care EEG, classifying main purposes into three points: detection of electrographic and electroclinical seizures, consideration of special encephalopathies, and evaluation and prognostication of cerebral function. Neurologists should have fundamental ability to read and interpret critical care EEG and support treating physicians in terms of therapeutic strategy.

Survivorship After Neurocritical Care: A Scoping Review of Outcomes Beyond Physical Status

Following intensive care unit hospitalization, survivors of acute neurological injury often experience debilitating short-term and long-term impairments. Although the physical/motor impairments experienced by survivors of acute neurological injury have been described extensively, fewer studies have examined cognitive, mental health, health-related quality of life (HRQoL), and employment outcomes. This scoping review describes the publication landscape beyond physical and/or motor sequelae in neurocritical care survivors. Databases were searched for terms related to critical illness, intensive care, and outcomes from January 1970 to March 2022. English-language studies of critically ill adults with a primary neurological diagnosis were included if they reported on at least one outcome of interest: cognition, mental health, HRQoL or employment. Data extraction was performed in duplicate for prespecified variables related to study outcomes. Of 16,036 abstracts screened, 74 citations were identified for inclusion. The studies encompassed seven worldwide regions and eight neurocritical diagnosis categories. Publications reporting outcomes of interest increased from 3 before the year 2000 to 71 after. Follow-up time points included ≤ 1 (n = 15 [20%] citations), 3 (n = 28 [38%]), 6 (n = 28 [38%]), and 12 (n = 21 [28%]) months and 1 to 5 (n = 19 [26%]) and > 5 years (n = 8 [11%]), with 28 (38%) citations evaluating outcomes at multiple time points. Sixty-six assessment tools were used to evaluate the four outcomes of interest: 22 evaluating HRQoL (56 [76%] citations), 21 evaluating cognition (20 [27%] citations), 21 evaluating mental health (18 [24%] citations), and 2 evaluating employment (9 [12%] citations). This scoping review aimed to better understand the literature landscape regarding nonphysical outcomes in survivors of neurocritical care. Although a rising number of publications highlight growing awareness, future efforts are needed to improve study consistency and comparability and characterize outcomes in a disease-specific manner, including outlining of a minimum core outcomes set and associated assessment tools.

Antiseizure Medication Use and Outcomes After Suspected or Confirmed Acute Symptomatic Seizures

Importance

Antiseizure medications (ASMs) are frequently prescribed for acute symptomatic seizures and epileptiform abnormalities (EAs; eg, periodic or rhythmic patterns). There are limited data on factors associated with ASM use and their association with outcomes.

Objectives

To determine factors associated with ASM use in patients with confirmed or suspected acute symptomatic seizures undergoing continuous electroencephalography, and to explore the association of ASMs with outcomes.

Design, Setting, and Participants

This multicenter cohort study was performed between July 1 and September 30, 2021, at 5 US centers of the Post Acute Symptomatic Seizure Investigation and Outcomes Network. After screening 1717 patients, the study included 1172 hospitalized adults without epilepsy who underwent continuous electroencephalography after witnessed or suspected acute symptomatic seizures. Data analysis was performed from November 14, 2023, to February 2, 2024.

Exposure

ASM treatment (inpatient ASM continuation ≥48 hours).

Main Outcomes and Measures

Factors associated with (1) ASM treatment, (2) discharge ASM prescription, and (3) discharge and 3-month Glasgow Outcome Scale score of 4 or 5 were ascertained.

Results

A total of 1172 patients (median [IQR] age, 64 [52-75] years; 528 [45%] female) were included. Among them, 285 (24%) had clinical acute symptomatic seizures, 107 (9%) had electrographic seizures, and 364 (31%) had EAs; 532 (45%) received ASM treatment. Among 922 patients alive at discharge, 288 (31%) were prescribed ASMs. The respective frequencies of inpatient ASM treatment and discharge prescription were 82% (233 of 285) and 69% (169 of 246) for patients with clinical acute symptomatic seizures, 96% (103 of 107) and 95% (61 of 64) for electrographic seizures, and 64% (233 of 364) and 48% (128 of 267) for EAs. On multivariable analysis, acute and progressive brain injuries were independently associated with increased odds of inpatient ASM treatment (odds ratio [OR], 3.86 [95% CI, 2.06-7.32] and 8.37 [95% CI, 3.48-20.80], respectively) and discharge prescription (OR, 2.26 [95% CI, 1.04-4.98] and 10.10 [95% CI, 3.94-27.00], respectively). Admission to the neurology or neurosurgery service (OR, 2.56 [95% CI, 1.08-6.18]) or to the neurological intensive care unit (OR, 7.98 [95% CI, 3.49-19.00]) was associated with increased odds of treatment. Acute symptomatic seizures and EAs were significantly associated with increased odds of ASM treatment (OR, 14.30 [95% CI, 8.52-24.90] and 2.30 [95% CI, 1.47-3.61], respectively) and discharge prescription (OR, 12.60 [95% CI, 7.37-22.00] and 1.72 [95% CI, 1.00-2.97], respectively). ASM treatment was not associated with outcomes at discharge (OR, 0.96 [95% CI, 0.61-1.52]) or at 3 months after initial presentation (OR, 1.26 [95% CI, 0.78-2.04]). Among 623 patients alive and with complete data at 3 months after discharge, 30 (5%) had postdischarge seizures, 187 (30%) were receiving ASMs, and 202 (32%) had all-cause readmissions.

Conclusions and Relevance

This study suggests that etiology and electrographic findings are associated with ASM treatment for acute symptomatic seizures and EAs; ASM treatment was not associated with functional outcomes. Comparative effectiveness studies are indicated to identify which patients may benefit from ASMs and to determine the optimal treatment duration.

Utility of Quantitative EEG in Neurological Emergencies and ICU Clinical Practice

The electroencephalogram (EEG) is a cornerstone tool for the diagnosis, management, and prognosis of selected patient populations. EEGs offer significant advantages such as high temporal resolution, real-time cortical function assessment, and bedside usability. The quantitative EEG (qEEG) added the possibility of long recordings being processed in a compressive manner, making EEG revision more efficient for experienced users, and more friendly for new ones. Recent advancements in commercially available software, such as Persyst, have significantly expanded and facilitated the use of qEEGs, marking the beginning of a new era in its application. As a result, there has been a notable increase in the practical, real-world utilization of qEEGs in recent years. This paper aims to provide an overview of the current applications of qEEGs in daily neurological emergencies and ICU practice, and some elementary principles of qEEGs using Persyst software in clinical settings. This article illustrates basic qEEG patterns encountered in critical care and adopts the new terminology proposed for spectrogram reporting.

How many patients do you need? Investigating trial designs for anti-seizure treatment in acute brain injury patients

BACKGROUND/OBJECTIVES

Epileptiform activity (EA), including seizures and periodic patterns, worsens outcomes in patients with acute brain injuries (e.g., aneurysmal subarachnoid hemorrhage [aSAH]). Randomized control trials (RCTs) assessing anti-seizure interventions are needed. Due to scant drug efficacy data and ethical reservations with placebo utilization, and complex physiology of acute brain injury, RCTs are lacking or hindered by design constraints. We used a pharmacological model-guided simulator to design and determine the feasibility of RCTs evaluating EA treatment.

METHODS

In a single-center cohort of adults (age >18) with aSAH and EA, we employed a mechanistic pharmacokinetic-pharmacodynamic framework to model treatment response using observational data. We subsequently simulated RCTs for levetiracetam and propofol, each with three treatment arms mirroring clinical practice and an additional placebo arm. Using our framework, we simulated EA trajectories across treatment arms. We predicted discharge modified Rankin Scale as a function of baseline covariates, EA burden, and drug doses using a double machine learning model learned from observational data. Differences in outcomes across arms were used to estimate the required sample size.

RESULTS

Sample sizes ranged from 500 for levetiracetam 7 mg/kg versus placebo, to >4000 for levetiracetam 15 versus 7 mg/kg to achieve 80% power (5% type I error). For propofol 1 mg/kg/h versus placebo, 1200 participants were needed. Simulations comparing propofol at varying doses did not reach 80% power even at samples >1200.

CONCLUSIONS

Our simulations using drug efficacy show sample sizes are infeasible, even for potentially unethical placebo-control trials. We highlight the strength of simulations with observational data to inform the null hypotheses and propose use of this simulation-based RCT paradigm to assess the feasibility of future trials of anti-seizure treatment in acute brain injury.

Improving Clinician Performance in Classifying EEG Patterns on the Ictal-Interictal Injury Continuum Using Interpretable Machine Learning

BACKGROUND

In intensive care units (ICUs), critically ill patients are monitored with electroencephalography (EEG) to prevent serious brain injury. EEG monitoring is constrained by clinician availability, and EEG interpretation can be subjective and prone to interobserver variability. Automated deep-learning systems for EEG could reduce human bias and accelerate the diagnostic process. However, existing uninterpretable (black-box) deep-learning models are untrustworthy, difficult to troubleshoot, and lack accountability in real-world applications, leading to a lack of both trust and adoption by clinicians.

METHODS

We developed an interpretable deep-learning system that accurately classifies six patterns of potentially harmful EEG activity - seizure, lateralized periodic discharges (LPDs), generalized periodic discharges (GPDs), lateralized rhythmic delta activity (LRDA), generalized rhythmic delta activity (GRDA), and other patterns - while providing faithful case-based explanations of its predictions. The model was trained on 50,697 total 50-second continuous EEG samples collected from 2711 patients in the ICU between July 2006 and March 2020 at Massachusetts General Hospital. EEG samples were labeled as one of the six EEG patterns by 124 domain experts and trained annotators. To evaluate the model, we asked eight medical professionals with relevant backgrounds to classify 100 EEG samples into the six pattern categories - once with and once without artificial intelligence (AI) assistance - and we assessed the assistive power of this interpretable system by comparing the diagnostic accuracy of the two methods. The model's discriminatory performance was evaluated with area under the receiver-operating characteristic curve (AUROC) and area under the precision-recall curve. The model's interpretability was measured with task-specific neighborhood agreement statistics that interrogated the similarities of samples and features. In a separate analysis, the latent space of the neural network was visualized by using dimension reduction techniques to examine whether the ictal-interictal injury continuum hypothesis, which asserts that seizures and seizure-like patterns of brain activity lie along a spectrum, is supported by data.

RESULTS

The performance of all users significantly improved when provided with AI assistance. Mean user diagnostic accuracy improved from 47 to 71% (P<0.04). The model achieved AUROCs of 0.87, 0.93, 0.96, 0.92, 0.93, and 0.80 for the classes seizure, LPD, GPD, LRDA, GRDA, and other patterns, respectively. This performance was significantly higher than that of a corresponding uninterpretable black-box model (with P<0.0001). Videos traversing the ictal-interictal injury manifold from dimension reduction (a two-dimensional representation of the original high-dimensional feature space) give insight into the layout of EEG patterns within the network's latent space and illuminate relationships between EEG patterns that were previously hypothesized but had not yet been shown explicitly. These results indicate that the ictal-interictal injury continuum hypothesis is supported by data.

CONCLUSIONS

Users showed significant pattern classification accuracy improvement with the assistance of this interpretable deep-learning model. The interpretable design facilitates effective human-AI collaboration; this system may improve diagnosis and patient care in clinical settings. The model may also provide a better understanding of how EEG patterns relate to each other along the ictal-interictal injury continuum. (Funded by the National Science Foundation, National Institutes of Health, and others.).

Post-Intensive Care Syndrome in Neurocritical Care Patients

Post-intensive care syndrome (PICS) refers to unintended consequences of critical care that manifest as new or worsening impairments in physical functioning, cognitive ability, or mental health. As intensive care unit (ICU) survival continues to improve, PICS is becoming increasingly recognized as a public health problem. Studies that focus on PICS have typically excluded patients with acute brain injuries and chronic neurodegenerative problems. However, patients who require neurocritical care undoubtedly suffer from impairments that overlap substantially with those encompassed by PICS. A major challenge is to distinguish between impairments related to brain injury and those that occur as a consequence of critical care. The general principles for the prevention and management of PICS and multidomain impairments in patients with moderate and severe neurological injuries are similar including the ICU liberation bundle, multidisciplinary team-based care throughout the continuum of care, and increasing awareness regarding the challenges of critical care survivorship among patients, families, and multidisciplinary team members. An extension of this concept, PICS-Family (PICS-F) refers to the mental health consequences of the intensive care experience for families and loved ones of ICU survivors. A dyadic approach to ICU survivorship with an emphasis on recognizing families and caregivers that may be at risk of developing PICS-F after neurocritical care illness can help improve outcomes for ICU survivors. In this review, we will summarize our current understanding of PICS and PICS-F, emerging literature on PICS in severe acute brain injury, strategies for preventing and treating PICS, and share our recommendations for future directions.

Predictive Model for Estimating the Risk of Epilepsy After Aneurysmal Subarachnoid Hemorrhage: The RISE Score

BACKGROUND AND OBJECTIVES

The occurrence of seizures after aneurysmal subarachnoid hemorrhage (aSAH) is associated with a poorer functional and cognitive prognosis and less favorable quality of life. It would be of value to promptly identify patients at risk of epilepsy to optimize follow-up protocols and design preventive strategies. Our aim was to develop a predictive score to help stratify epilepsy risk in patients with aSAH.

METHODS

This is a retrospective, longitudinal study of all adults with aSAH admitted to our center (2012-2021). We collected demographic data, clinical and radiologic variables, data on early-onset seizures (EOSs), and data on development of epilepsy. Exclusion criteria were previous structural brain lesion, epilepsy, and ≤7 days' follow-up. Multiple Cox regression was used to evaluate factors independently associated with unprovoked remote seizures (i.e., epilepsy). The best fitting regression model was used to develop a predictive score. Performance was evaluated in an external validation cohort of 308 patients using receiver-operating characteristic curve analysis.

RESULTS

From an initial database of 743 patients, 419 met the inclusion criteria and were included in the analysis. The mean age was 60 ± 14 years, 269 patients (64%) were women, and 50 (11.9%) developed epilepsy within a median follow-up of 4.2 years. Premorbid modified Rankin Score (mRS) (hazard ratio [HR] 4.74 [1.8-12.4], p = 0.001), VASOGRADE score (HR 2.45 [1.4-4.2], p = 0.001), surgical treatment (HR 2.77 [1.6-4.9], p = 0.001), and presence of EOSs (HR 1.84 [1.0-3.4], p = 0.05) were independently associated with epilepsy. The proposed scale, designated RISE, scores 1 point for premorbid mRS ≥ 2 (R), VASOGRADE-Yellow (I, Ischemia), surgical intervention (S), and history of EOSs (E) and 2 points for VASOGRADE-Red. RISE stratifies patients into 3 groups: low (0-1), moderate (2-3), and high (4-5) risk (2.9%, 20.8%, and 75.7% developed epilepsy, respectively). On validation in a cohort from a different tertiary care center (N = 308), the new scale yielded a similar risk distribution and good predictive power for epilepsy within 5 years after aSAH (area under the curve [AUC] 0.82; 95% CI 0.74-0.90).

DISCUSSION

The RISE scale is a robust predictor of post-SAH epilepsy with immediate clinical applicability. In addition to facilitating personalized diagnosis and treatment, RISE may be of value for exploring future antiepileptogenesis strategies.

The Cost of After-Hour Electroencephalography

Background and Objectives

High costs associated with after-hour electroencephalography (EEG) constitute a barrier for financially constrained hospitals to provide this neurodiagnostic procedure outside regular working hours. Our study aims to deepen our understanding of the cost elements involved in delivering EEG services during after-hours.

Methods

We accessed publicly available data sets and created a cost model depending on 3 most commonly seen staffing scenarios: (1) technologist on-site, (2) technologist on-call from home, and (3) a hybrid of the two.

Results

Cost of EEG depends on the volume of testing and the staffing plan. Within the various cost elements, labor cost of EEG technologists is the predominant expenditure, which varies across geographic regions and urban areas.

Discussion

We provide a model to explain why access to EEGs during after-hours has a substantial expense. This model provides a cost calculator tool (made available as part of this publication in eAppendix 1, links.lww.com/CPJ/A513) to estimate the cost of EEG platform based on site-specific staffing scenarios and annual volume.

Estimate of Patients With Missed Seizures Because of Delay in Conventional EEG

PURPOSE

There is frequent delay between ordering and placement of conventional EEG. Here we estimate how many patients had seizures during this delay.

METHODS

Two hundred fifty consecutive adult patients who underwent conventional EEG monitoring at the University of Wisconsin Hospital were retrospectively chart reviewed for demographics, time of EEG order, clinical and other EEG-related information. Patients were stratified by use of anti-seizure medications before EEG and into low-risk, medium-risk, and high-risk groups based on 2HELPS2B score (0, 1, or >1). Monte Carlo simulations (500 trials) were performed to estimate seizures during delay.

RESULTS

The median delay from EEG order to performing EEG was 2.00 hours (range of 0.5-8.00 hours) in the total cohort. For EEGs ordered after-hours, it was 2.00 hours (range 0.5-8.00 hours), and during business hours, it was 2.00 hours (range 0.5-6.00 hours). The place of EEG, intensive care unit, emergency department, and general floor, did not show significant difference (P = 0.84). Anti-seizure medication did not affect time to first seizure in the low-risk (P = 0.37), medium-risk (P = 0.44), or high-risk (P = 0.12) groups. The estimated % of patients who had a seizure in the delay period for low-risk group (2HELPS2B = 0) was 0.8%, for the medium-risk group (2HELPS2B = 1) was 10.3%, and for the high-risk group (2HELPS2B > 1) was 17.6%, and overall risk was 7.2%.

CONCLUSIONS

The University of Wisconsin Hospital with 24-hour in-house EEG technologists has a median delay of 2 hours from order to start of EEG, shorter than published reports from other centers. Nonetheless, seizures were likely missed in about 7.2% of patients.

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.

Emerging Treatments for Subarachnoid Hemorrhage

The current landscape of therapeutic strategies for subarachnoid hemorrhage (SAH), a significant adverse neurological event commonly resulting from the rupture of intracranial aneurysms, is rapidly evolving. Through an in-depth exploration of the natural history of SAH, historical treatment approaches, and emerging management modalities, the present work aims to provide a broad overview of the shifting paradigms in SAH care. By synthesizing the historical management protocols with contemporary therapeutic advancements, patient-specific treatment plans can be individualized and optimized to deliver outstanding care for the best possible SAH-related outcomes.

"T" Times: Revisiting the Timing of Neuronal Injury in Status Epilepticus

Effects of Epileptiform Activity on Discharge Outcome in Critically Ill Patients in the USA: A Retrospective Cross-Sectional Study Parikh H, Hoffman K, Sun H, Zafar SF, Ge W, Jing J, Liu L, Sun J, Struck A, Volfovsky A, Rudin C, Westover MB. Lancet Digit Health. 2023;5:e495-e502. doi:10.1016/S2589-7500(23)00088-2 Background: Epileptiform activity is associated with worse patient outcomes, including increased risk of disability and death. However, the effect of epileptiform activity on neurological outcome is confounded by the feedback between treatment with antiseizure medications and epileptiform activity burden. We aimed to quantify the heterogeneous effects of epileptiform activity with an interpretability-centred approach. Methods: We did a retrospective, cross-sectional study of patients in the intensive care unit who were admitted to Massachusetts General Hospital (Boston, MA, USA). Participants were aged 18 years or older and had electrographic epileptiform activity identified by a clinical neurophysiologist or epileptologist. The outcome was the dichotomised modified Rankin Scale (mRS) at discharge and the exposure was epileptiform activity burden defined as mean or maximum proportion of time spent with epileptiform activity in 6 h windows in the first 24 h of electroencephalography. We estimated the change in discharge mRS if everyone in the dataset had experienced a specific epileptiform activity burden and were untreated. We combined pharmacological modelling with an interpretable matching method to account for confounding and epileptiform activity-antiseizure medication feedback. The quality of the matched groups was validated by the neurologists. Findings: Between Dec 1, 2011, and Oct 14, 2017, 1514 patients were admitted to Massachusetts General Hospital intensive care unit, 995 (66%) of whom were included in the analysis. Compared with patients with a maximum epileptiform activity of 0 to less than 25%, patients with a maximum epileptiform activity burden of 75% or more when untreated had a mean 22.27% (SD 0.92) increased chance of a poor outcome (severe disability or death). Moderate but long-lasting epileptiform activity (mean epileptiform activity burden 2% to <10%) increased the risk of a poor outcome by mean 13.52% (SD 1.93). The effect sizes were heterogeneous depending on preadmission profile—eg, patients with hypoxic-ischaemic encephalopathy or acquired brain injury were more adversely affected compared with patients without these conditions. Interpretation: Our results suggest that interventions should put a higher priority on patients with an average epileptiform activity burden 10% or greater, and treatment should be more conservative when maximum epileptiform activity burden is low. Treatment should also be tailored to individual preadmission profiles because the potential for epileptiform activity to cause harm depends on age, medical history, and reason for admission.

Effects of New-Generation Antiepileptic Drug Prophylaxis on Delayed Neurovascular Events After Aneurysmal Subarachnoid Hemorrhage

Neuroelectric disruptions such as seizures and cortical spreading depolarization may contribute to the development of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (SAH). However, effects of antiepileptic drug prophylaxis on outcomes remain controversial in SAH. The authors investigated if prophylactic administration of new-generation antiepileptic drugs levetiracetam and perampanel was beneficial against delayed neurovascular events after SAH. This was a retrospective single-center cohort study of 121 consecutive SAH patients including 56 patients of admission World Federation of Neurological Surgeons grades IV - V who underwent aneurysmal obliteration within 72 h post-SAH from 2013 to 2021. Prophylactic antiepileptic drugs differed depending on the study terms: none (2013 - 2015), levetiracetam for patients at high risks of seizures (2016 - 2019), and perampanel for all patients (2020 - 2021). The 3rd term had the lowest occurrence of delayed cerebral microinfarction on diffusion-weighted magnetic resonance imaging, which was related to less development of DCI. Other outcome measures were similar among the 3 terms including incidences of angiographic vasospasm, computed tomography-detectable delayed cerebral infarction, seizures, and 3-month good outcomes (modified Rankin Scale 0 - 2). The present study suggests that prophylactic administration of levetiracetam and perampanel was not associated with worse outcomes and that perampanel may have the potential to reduce DCI by preventing microcirculatory disturbances after SAH. Further studies are warranted to investigate anti-DCI effects of a selective α-amino-3-hydroxy-5-methyl-4-isoxazole propionate receptor antagonist perampanel in SAH patients in a large-scale prospective study.

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.

Outcomes in Patients With Poststroke Seizures: A Systematic Review and Meta-Analysis

Importance

Published data about the impact of poststroke seizures (PSSs) on the outcomes of patients with stroke are inconsistent and have not been systematically evaluated, to the authors' knowledge.

Objective

To investigate outcomes in people with PSS compared with people without PSS.

Data Sources

MEDLINE, Embase, PsycInfo, Cochrane, LILACS, LIPECS, and Web of Science, with years searched from 1951 to January 30, 2023.

Study Selection

Observational studies that reported PSS outcomes.

Data Extraction and Synthesis

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was used for abstracting data, and the Joanna Briggs Institute tool was used for risk-of-bias assessment. Data were reported as odds ratio (OR) and standardized mean difference (SMD) with a 95% CI using a random-effects meta-analysis. Publication bias was assessed using funnel plots and the Egger test. Outlier and meta-regression analyses were performed to explore the source of heterogeneity. Data were analyzed from November 2022 to January 2023.

Main Outcomes and Measures

Measured outcomes were mortality, poor functional outcome (modified Rankin scale [mRS] score 3-6), disability (mean mRS score), recurrent stroke, and dementia at patient follow-up.

Results

The search yielded 71 eligible articles, including 20 110 patients with PSS and 1 166 085 patients without PSS. Of the participants with PSS, 1967 (9.8%) had early seizures, and 10 605 (52.7%) had late seizures. The risk of bias was high in 5 studies (7.0%), moderate in 35 (49.3%), and low in 31 (43.7%). PSSs were associated with mortality risk (OR, 2.1; 95% CI, 1.8-2.4), poor functional outcome (OR, 2.2; 95% CI, 1.8-2.8), greater disability (SMD, 0.6; 95% CI, 0.4-0.7), and increased dementia risk (OR, 3.1; 95% CI, 1.3-7.7) compared with patients without PSS. In subgroup analyses, early seizures but not late seizures were associated with mortality (OR, 2.4; 95% CI, 1.9-2.9 vs OR, 1.2; 95% CI, 0.8-2.0) and both ischemic and hemorrhagic stroke subtypes were associated with mortality (OR, 2.2; 95% CI, 1.8-2.7 vs OR, 1.4; 95% CI, 1.0-1.8). In addition, early and late seizures (OR, 2.4; 95% CI, 1.6-3.4 vs OR, 2.7; 95% CI, 1.8-4.1) and stroke subtypes were associated with poor outcomes (OR, 2.6; 95% CI, 1.9-3.7 vs OR, 1.9; 95% CI, 1.0-3.6).

Conclusions and Relevance

Results of this systematic review and meta-analysis suggest that PSSs were associated with significantly increased mortality and severe disability in patients with history of stroke. Unraveling these associations is a high clinical and research priority. Trials of interventions to prevent seizures may be warranted.

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.

How Many Patients Do You Need? Investigating Trial Designs for Anti-Seizure Treatment in Acute Brain Injury Patients

Objectives

Epileptiform activity (EA) worsens outcomes in patients with acute brain injuries (e.g., aneurysmal subarachnoid hemorrhage [aSAH]). Randomized trials (RCTs) assessing anti-seizure interventions are needed. Due to scant drug efficacy data and ethical reservations with placebo utilization, RCTs are lacking or hindered by design constraints. We used a pharmacological model-guided simulator to design and determine feasibility of RCTs evaluating EA treatment.

Methods

In a single-center cohort of adults (age >18) with aSAH and EA, we employed a mechanistic pharmacokinetic-pharmacodynamic framework to model treatment response using observational data. We subsequently simulated RCTs for levetiracetam and propofol, each with three treatment arms mirroring clinical practice and an additional placebo arm. Using our framework we simulated EA trajectories across treatment arms. We predicted discharge modified Rankin Scale as a function of baseline covariates, EA burden, and drug doses using a double machine learning model learned from observational data. Differences in outcomes across arms were used to estimate the required sample size.

Results

Sample sizes ranged from 500 for levetiracetam 7 mg/kg vs placebo, to >4000 for levetiracetam 15 vs. 7 mg/kg to achieve 80% power (5% type I error). For propofol 1mg/kg/hr vs. placebo 1200 participants were needed. Simulations comparing propofol at varying doses did not reach 80% power even at samples >1200.

Interpretation

Our simulations using drug efficacy show sample sizes are infeasible, even for potentially unethical placebo-control trials. We highlight the strength of simulations with observational data to inform the null hypotheses and assess feasibility of future trials of EA treatment.

Clinical and Electroencephalographic Predictors of Seizures and Status Epilepticus in 12,450 Critically Ill Adults: A Retrospective Cohort Study

OBJECTIVES

Status epilepticus (SE) is associated with significantly higher morbidity and mortality than isolated seizures. Our objective was to identify clinical diagnoses and rhythmic and periodic electroencephalogram patterns (RPPs) associated with SE and seizures.

DESIGN

Retrospective cohort study.

SETTING

Tertiary-care hospitals.

SUBJECTS

Twelve thousand four hundred fifty adult hospitalized patients undergoing continuous electroencephalogram (cEEG) monitoring in selected participating sites in the Critical Care EEG Monitoring Research Consortium database (February 2013 to June 2021).

INTERVENTIONS

Not applicable.

MEASUREMENTS AND MAIN RESULTS

We defined an ordinal outcome in the first 72 hours of cEEG: no seizures, isolated seizures without SE, or SE (with or without isolated seizures). Composite groups included isolated seizures or SE (AnySz) and no seizure or isolated seizures. In this cohort (mean age: 60 ± 17 yr), 1,226 patients (9.8%) had AnySz and 439 patients (3.5%) had SE. In a multivariate model, factors independently associated with SE were cardiac arrest (9.2% with SE; adjusted odds ratio, 8.8 [6.3-12.1]), clinical seizures before cEEG (5.7%; 3.3 [2.5-4.3]), brain neoplasms (3.2%; 1.6 [1.0-2.6]), lateralized periodic discharges (LPDs) (15.4%; 7.3 [5.7-9.4]), brief potentially ictal rhythmic discharges (BIRDs) (22.5%; 3.8 [2.6-5.5]), and generalized periodic discharges (GPDs) (7.2%; 2.4 [1.7-3.3]). All above variables and lateralized rhythmic delta activity (LRDA) were also associated with AnySz. Factors disproportionately increasing odds of SE over isolated seizures were cardiac arrest (7.3 [4.4-12.1]), clinical seizures (1.7 [1.3-2.4]), GPDs (2.3 [1.4-3.5]), and LPDs (1.4 [1.0-1.9]). LRDA had lower odds of SE compared with isolated seizures (0.5 [0.3-0.9]). RPP modifiers did not improve SE prediction beyond RPPs presence/absence ( p = 0.8).

CONCLUSIONS

Using the largest existing cEEG database, we identified specific predictors of SE (cardiac arrest, clinical seizures prior to cEEG, brain neoplasms, LPDs, GPDs, and BIRDs) and seizures (all previous and LRDA). These findings could be used to tailor cEEG monitoring for critically ill patients.

Effects of epileptiform activity on discharge outcome in critically ill patients in the USA: a retrospective cross-sectional study

BACKGROUND

Epileptiform activity is associated with worse patient outcomes, including increased risk of disability and death. However, the effect of epileptiform activity on neurological outcome is confounded by the feedback between treatment with antiseizure medications and epileptiform activity burden. We aimed to quantify the heterogeneous effects of epileptiform activity with an interpretability-centred approach.

METHODS

We did a retrospective, cross-sectional study of patients in the intensive care unit who were admitted to Massachusetts General Hospital (Boston, MA, USA). Participants were aged 18 years or older and had electrographic epileptiform activity identified by a clinical neurophysiologist or epileptologist. The outcome was the dichotomised modified Rankin Scale (mRS) at discharge and the exposure was epileptiform activity burden defined as mean or maximum proportion of time spent with epileptiform activity in 6 h windows in the first 24 h of electroencephalography. We estimated the change in discharge mRS if everyone in the dataset had experienced a specific epileptiform activity burden and were untreated. We combined pharmacological modelling with an interpretable matching method to account for confounding and epileptiform activity-antiseizure medication feedback. The quality of the matched groups was validated by the neurologists.

FINDINGS

Between Dec 1, 2011, and Oct 14, 2017, 1514 patients were admitted to Massachusetts General Hospital intensive care unit, 995 (66%) of whom were included in the analysis. Compared with patients with a maximum epileptiform activity of 0 to less than 25%, patients with a maximum epileptiform activity burden of 75% or more when untreated had a mean 22·27% (SD 0·92) increased chance of a poor outcome (severe disability or death). Moderate but long-lasting epileptiform activity (mean epileptiform activity burden 2% to <10%) increased the risk of a poor outcome by mean 13·52% (SD 1·93). The effect sizes were heterogeneous depending on preadmission profile-eg, patients with hypoxic-ischaemic encephalopathy or acquired brain injury were more adversely affected compared with patients without these conditions.

INTERPRETATION

Our results suggest that interventions should put a higher priority on patients with an average epileptiform activity burden 10% or greater, and treatment should be more conservative when maximum epileptiform activity burden is low. Treatment should also be tailored to individual preadmission profiles because the potential for epileptiform activity to cause harm depends on age, medical history, and reason for admission.

FUNDING

National Institutes of Health and National Science Foundation.

Early timing of anesthesia in status epilepticus is associated with complete recovery: A 7-year retrospective two-center study

OBJECTIVE

This study was undertaken to investigate the efficacy, tolerability, and outcome of different timing of anesthesia in adult patients with status epilepticus (SE).

METHODS

Patients with anesthesia for SE from 2015 to 2021 at two Swiss academic medical centers were categorized as anesthetized as recommended third-line treatment, earlier (as first- or second-line treatment), and delayed (later as third-line treatment). Associations between timing of anesthesia and in-hospital outcomes were estimated by logistic regression.

RESULTS

Of 762 patients, 246 received anesthesia; 21% were anesthetized as recommended, 55% earlier, and 24% delayed. Propofol was preferably used for earlier (86% vs. 55.5% for recommended/delayed anesthesia) and midazolam for later anesthesia (17.2% vs. 15.9% for earlier anesthesia). Earlier anesthesia was statistically significantly associated with fewer infections (17% vs. 32.7%), shorter median SE duration (.5 vs. 1.5 days), and more returns to premorbid neurologic function (52.9% vs. 35.5%). Multivariable analyses revealed decreasing odds for return to premorbid function with every additional nonanesthetic antiseizure medication given prior to anesthesia (odds ratio [OR] = .71, 95% confidence interval [CI] = .53-.94) independent of confounders. Subgroup analyses revealed decreased odds for return to premorbid function with increasing delay of anesthesia independent of the Status Epilepticus Severity Score (STESS; STESS = 1-2: OR = .45, 95% CI = .27-.74; STESS > 2: OR = .53, 95% CI = .34-.85), especially in patients without potentially fatal etiology (OR = .5, 95% CI = .35-.73) and in patients experiencing motor symptoms (OR = .67, 95% CI = .48-.93).

SIGNIFICANCE

In this SE cohort, anesthetics were administered as recommended third-line therapy in only every fifth patient and earlier in every second. Increasing delay of anesthesia was associated with decreased odds for return to premorbid function, especially in patients with motor symptoms and no potentially fatal etiology.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

BACKGROUND AND OBJECTIVES

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

METHODS

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

RESULTS

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

DISCUSSION

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

CLASSIFICATION OF EVIDENCE

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

Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs

BACKGROUND AND OBJECTIVES

The validity of brain monitoring using electroencephalography (EEG), particularly to guide care in patients with acute or critical illness, requires that experts can reliably identify seizures and other potentially harmful rhythmic and periodic brain activity, collectively referred to as "ictal-interictal-injury continuum" (IIIC). Previous interrater reliability (IRR) studies are limited by small samples and selection bias. This study was conducted to assess the reliability of experts in identifying IIIC.

METHODS

This prospective analysis included 30 experts with subspecialty clinical neurophysiology training from 18 institutions. Experts independently scored varying numbers of ten-second EEG segments as "seizure (SZ)," "lateralized periodic discharges (LPDs)," "generalized periodic discharges (GPDs)," "lateralized rhythmic delta activity (LRDA)," "generalized rhythmic delta activity (GRDA)," or "other." EEGs were performed for clinical indications at Massachusetts General Hospital between 2006 and 2020. Primary outcome measures were pairwise IRR (average percent agreement [PA] between pairs of experts) and majority IRR (average PA with group consensus) for each class and beyond chance agreement (κ). Secondary outcomes were calibration of expert scoring to group consensus, and latent trait analysis to investigate contributions of bias and noise to scoring variability.

RESULTS

Among 2,711 EEGs, 49% were from women, and the median (IQR) age was 55 (41) years. In total, experts scored 50,697 EEG segments; the median [range] number scored by each expert was 6,287.5 [1,002, 45,267]. Overall pairwise IRR was moderate (PA 52%, κ 42%), and majority IRR was substantial (PA 65%, κ 61%). Noise-bias analysis demonstrated that a single underlying receiver operating curve can account for most variation in experts' false-positive vs true-positive characteristics (median [range] of variance explained ([Formula: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Formula: see text]: 75 [59, 89]%). Thus, variation between experts is mostly attributable not to differences in expertise but rather to variation in decision thresholds.

DISCUSSION

Our results provide precise estimates of expert reliability from a large and diverse sample and a parsimonious theory to explain the origin of disagreements between experts. The results also establish a standard for how well an automated IIIC classifier must perform to match experts.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that an independent expert review reliably identifies ictal-interictal injury continuum patterns on EEG compared with expert consensus.

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

Background and purpose

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

Methods

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

Results

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

Conclusions

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

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

Objectives

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

Design and review methods

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

Results

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

Conclusion

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

Neuromonitoring in Children with Cerebrovascular Disorders

BACKGROUND

Cerebrovascular disorders are an important cause of morbidity and mortality in children. The acute care of a child with an ischemic or hemorrhagic stroke or cerebral sinus venous thrombosis focuses on stabilizing the patient, determining the cause of the insult, and preventing secondary injury. Here, we review the use of both invasive and noninvasive neuromonitoring modalities in the care of pediatric patients with arterial ischemic stroke, nontraumatic intracranial hemorrhage, and cerebral sinus venous thrombosis.

METHODS

Narrative review of the literature on neuromonitoring in children with cerebrovascular disorders.

RESULTS

Neuroimaging, near-infrared spectroscopy, transcranial Doppler ultrasonography, continuous and quantitative electroencephalography, invasive intracranial pressure monitoring, and multimodal neuromonitoring may augment the acute care of children with cerebrovascular disorders. Neuromonitoring can play an essential role in the early identification of evolving injury in the aftermath of arterial ischemic stroke, intracranial hemorrhage, or sinus venous thrombosis, including recurrent infarction or infarct expansion, new or recurrent hemorrhage, vasospasm and delayed cerebral ischemia, status epilepticus, and intracranial hypertension, among others, and this, is turn, can facilitate real-time adjustments to treatment plans.

CONCLUSIONS

Our understanding of pediatric cerebrovascular disorders has increased dramatically over the past several years, in part due to advances in the neuromonitoring modalities that allow us to better understand these conditions. We are now poised, as a field, to take advantage of advances in neuromonitoring capabilities to determine how best to manage and treat acute cerebrovascular disorders in children.

Non-Convulsive Status Epilepticus in Aneurysmal Subarachnoid Hemorrhage: A Prognostic Parameter

A non-convulsive status epilepticus (ncSE) is a potentially fatal complication for patients in neurointensive care. In patients with aneurysmal subarachnoid hemorrhage (SAH), ncSE remains scarcely investigated. In this study, we aim to investigate the frequency and influence of non-convulsive status epilepticus on outcome in patients with SAH. We retrospectively analyzed data of consecutive patients with aneurysmal subarachnoid hemorrhage and evaluated clinical, radiological, demographical and electroencephalogram (EEG) data. Outcome was assessed according to the modified Rankin Scale (mRS) at 6 months and stratified into favorable (mRS 0-2) vs. unfavorable (mRS 3-6). We identified 171 patients with SAH, who received EEG between 01/2012 and 12/2020. ncSE was diagnosed in 19 patients (3.7%), only one of whom achieved favorable outcome. The multivariate regression analysis revealed four independent predictors of unfavorable outcome: presence of ncSE (p = 0.003; OR 24.1; 95 CI% 2.9-195.3), poor-grade SAH (p < 0.001; OR 14.0; 95 CI% 8.5-23.1), age (p < 0.001; OR 2.8; 95 CI% 1.6-4.6) and the presence of DIND (p < 0.003; OR 1.9; 95 CI% 1.2-3.1) as independent predictors for unfavorable outcome. According to our study, development of ncSE in patients suffering SAH might correlate with poor prognosis. Even when medical treatment is successful and no EEG abnormalities are detected, the long-term outcome remains poor.

Electrographic Seizures in the Critically Ill

Identifying and treating critically ill patients with seizures can be challenging. In this article, the authors review the available data on patient populations at risk, seizure prognostication with tools such as 2HELPS2B, electrographic seizures and the various ictal-interictal continuum patterns with their latest definitions and associated risks, ancillary testing such as imaging studies, serum biomarkers, and invasive multimodal monitoring. They also illustrate 5 different patient scenarios, their treatment and outcomes, and propose recommendations for targeted treatment of electrographic seizures in critically ill patients.

Utilization of EEG for Monitoring in Subarachnoid hemorrhage Recovery

Seizures and delayed cerebral ischemia following subarachnoid hemorrhage are associated with significant morbidity and mortality. In this article, we briefly review subarachnoid hemorrhage, its complications, and the current literature on information gained from EEG monitoring in subarachnoid hemorrhage. We review when EEG should be used implemented in the multi-modal monitoring of patients with subarachnoid hemorrhage. Finally, we discuss the recent advances and future directions in the field.

Closing the Gap in Pediatric Hemorrhagic Stroke: A Systematic Review

Pediatric hemorrhagic stroke (HS) accounts for a large proportion of childhood strokes, 1 of the top 10 causes of pediatric deaths. Morbidity and mortality lead to significant socio-economic and psychosocial burdens. To understand published data on recognizing and managing children with HS, we conducted a systematic review of the literature presented here. We searched PubMed, Embase, CINAHL and the Cochrane Library databases limited to English language and included 174 studies, most conducted in the USA (52%). Terminology used interchangeably for HS included intraparenchymal/intracranial hemorrhage, spontaneous ICH, and cerebrovascular accident (CVA). Key assessments informing prognosis and management included clinical scoring (Glasgow coma scale), and neuroimaging. HS etiologies reported were systemic coagulopathy (genetic, acquired pathologic, or iatrogenic), or focal cerebrovascular lesions (brain arteriovenous malformations, cavernous malformations, aneurysms, or tumor vascularity). Several scales were used to measure outcome: Glasgow outcome score (GOS), Kings outcome score for head injury (KOSCHI), modified Rankin scale (mRS) and pediatric stroke outcome measure (PSOM). Most studies described treatments of at-risk lesions. Few studies described neurocritical care management including raised ICP, seizures, vasospasm, or blood pressure. Predictors of poor outcome included ethnicity, comorbidity, location of bleed, and hematoma &gt;2% of total brain volume. Motor and cognitive outcomes followed independent patterns. Few studies reported on cognitive outcomes, rehabilitation, and transition of care models. Interdisciplinary approach to managing HS is urgently needed, informed by larger cohort studies targeting key clinical question (eg development of a field-guide for the clinician managing patients with HS that is reproducible internationally).

Spontaneous subarachnoid haemorrhage

Subarachnoid haemorrhage (SAH) is the third most common subtype of stroke. Incidence has decreased over past decades, possibly in part related to lifestyle changes such as smoking cessation and management of hypertension. Approximately a quarter of patients with SAH die before hospital admission; overall outcomes are improved in those admitted to hospital, but with elevated risk of long-term neuropsychiatric sequelae such as depression. The disease continues to have a major public health impact as the mean age of onset is in the mid-fifties, leading to many years of reduced quality of life. The clinical presentation varies, but severe, sudden onset of headache is the most common symptom, variably associated with meningismus, transient or prolonged unconsciousness, and focal neurological deficits including cranial nerve palsies and paresis. Diagnosis is made by CT scan of the head possibly followed by lumbar puncture. Aneurysms are commonly the underlying vascular cause of spontaneous SAH and are diagnosed by angiography. Emergent therapeutic interventions are focused on decreasing the risk of rebleeding (ie, preventing hypertension and correcting coagulopathies) and, most crucially, early aneurysm treatment using coil embolisation or clipping. Management of the disease is best delivered in specialised intensive care units and high-volume centres by a multidisciplinary team. Increasingly, early brain injury presenting as global cerebral oedema is recognised as a potential treatment target but, currently, disease management is largely focused on addressing secondary complications such as hydrocephalus, delayed cerebral ischaemia related to microvascular dysfunction and large vessel vasospasm, and medical complications such as stunned myocardium and hospital acquired infections.

Epileptiform Abnormalities in Acute Ischemic Stroke: Impact on Clinical Management and Outcomes

PURPOSE

Studies examining seizures (Szs) and epileptiform abnormalities (EAs) using continuous EEG in acute ischemic stroke (AIS) are limited. Therefore, we aimed to describe the prevalence of Sz and EA in AIS, its impact on anti-Sz drug management, and association with discharge outcomes.

METHODS

The study included 132 patients with AIS who underwent continuous EEG monitoring >6 hours. Continuous EEG was reviewed for background, Sz and EA (lateralized periodic discharges [LPD], generalized periodic discharges, lateralized rhythmic delta activity, and sporadic epileptiform discharges). Relevant clinical, demographic, and imaging factors were abstracted to identify risk factors for Sz and EA. Outcomes included all-cause mortality, functional outcome at discharge (good outcome as modified Rankin scale of 0-2 and poor outcome as modified Rankin scale of 3-6) and changes to anti-Sz drugs (escalation or de-escalation).

RESULTS

The frequency of Sz was 7.6%, and EA was 37.9%. Patients with Sz or EA were more likely to have cortical involvement (84.6% vs. 67.5% P = 0.028). Among the EAs, the presence of LPD was associated with an increased risk of Sz (25.9% in LPD vs. 2.9% without LPD, P = 0.001). Overall, 21.2% patients had anti-Sz drug changes because of continuous EEG findings, 16.7% escalation and 4.5% de-escalation. The presence of EA or Sz was not associated with in-hospital mortality or discharge functional outcomes.

CONCLUSIONS

Despite the high incidence of EA, the rate of Sz in AIS is relatively lower and is associated with the presence of LPDs. These continuous EEG findings resulted in anti-Sz drug changes in one-fifth of the cohort. Epileptiform abnormality and Sz did not affect mortality or discharge functional outcomes.

Anti-seizure medication treatment and outcomes in acute ischemic stroke patients undergoing continuous EEG monitoring

OBJECTIVES

To determine the association of anti-seizure medication (ASM) treatment with outcomes in acute ischemic stroke (AIS) patients undergoing continuous electroencephalography (cEEG).

METHODS

Retrospective analysis of AIS patients admitted between 2012 and 2019. The following are the inclusion criteria: age ≥ 18 years and ≥ 16 h of cEEG within the first 7 days of admission. ASM treatment exposure was defined as > 48 h of treatment after the first 24 h of cEEG. The primary outcome measure was 90-day mortality, and the secondary outcome was 90-day functional recovery (Modified Ranking Scale 0-3). Propensity scores were used to adjust for baseline covariates and presence of epileptiform abnormalities (seizures, periodic and rhythmic patterns).

RESULTS

One hundred thirteen patients met the inclusion criteria; 39 (34.5%) were exposed to ASM. ASM treatment was not associated with 90-day mortality (propensity adjusted HR 1.0 [0.31-3.27], p = 0.999) or functional outcomes (adjusted HR 0.99 [0.32-3.02], p = 0.989), compared to no treatment.

CONCLUSIONS

In our study, ASM treatment in AIS patients with cEEG abnormalities was not significantly associated with a change in 90-day mortality and functional recovery. Larger comparative effectiveness studies are indicated to identify which acute ischemic stroke patients with cEEG abnormalities benefit most from ASM treatment.

High epileptiform discharge burden predicts delayed cerebral ischemia after subarachnoid hemorrhage

OBJECTIVE

To investigate whether epileptiform discharge burden can identify those at risk for delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH).

METHODS

Retrospective analysis of 113 moderate to severe grade SAH patients who had continuous EEG (cEEG) recordings during their hospitalization. We calculated the burden of epileptiform discharges (ED), measured as number of ED per hour.

RESULTS

We find that many SAH patients have an increase in ED burden during the first 3-10 days following rupture, the major risk period for DCI. However, those who develop DCI have a significantly higher hourly burden from days 3.5-6 after SAH vs. those who do not. ED burden is higher in DCI patients when assessed in relation to the onset of DCI (area under the receiver operator curve 0.72). Finally, specific trends of ED burden over time, assessed by group-based trajectory analysis, also help stratify DCI risk.

CONCLUSIONS

These results suggest that ED burden is a useful parameter for identifying those at higher risk of developing DCI after SAH. The higher burden rate associated with DCI supports the theory of metabolic supply-demand mismatch which contributes to this complication.

SIGNIFICANCE

ED burden is a novel biomarker for predicting those at high risk of DCI.

International consensus recommendations for management of New Onset Refractory Status Epilepticus (NORSE) incl. Febrile Infection-Related Epilepsy Syndrome (FIRES): Statements and Supporting Evidence

OBJECTIVE

To develop consensus-based recommendations for the management of adult and paediatric patients with NORSE/FIRES based on best evidence and experience.

METHODS

The Delphi methodology was followed. A facilitator group of 9 experts was established, who defined the scope, users and suggestions for recommendations. Following a review of the current literature, recommendation statements concerning diagnosis, treatment and research directions were generated which were then voted on a scale of 1 (strongly disagree) to 9 (strongly agree) by a panel of 48 experts in the field. Consensus that a statement was appropriate was reached if the median score was greater or equal to 7, and inappropriate if the median score was less than or equal to 3. The analysis of evidence was mapped to the results of each statement included in the Delphi survey.

RESULTS

Overall, 85 recommendation statements achieved consensus. The recommendations are divided into five sections: 1) disease characteristics, 2) diagnostic testing and sampling, 3) acute treatment, 4) treatment in the post-acute phase, and 5) research, registries and future directions in NORSE/FIRES. The detailed results and discussion of all 85 statements are outlined herein. A corresponding summary of findings and practical flowsheets are presented in a companion article.

SIGNIFICANCE

This detailed analysis offers insight into the supporting evidence and the current gaps in the literature that are associated with expert consensus statements related to NORSE/FIRES. The recommendations generated by this consensus can be used as a guide for the diagnosis, evaluation, and management of patients with NORSE/FIRES, and for planning of future research.

A Validation Study for SHE Score for Acute Subdural Hematoma in the Elderly

OBJECTIVE

The aim of this study was the verification of the Subdural Hematoma in the Elderly (SHE) score proposed by Alford et al. as a mortality predictor in patients older than 65 years with nontraumatic/minor trauma acute subdural hematoma (aSDH). Additionally, we evaluated further predictors associated with poor outcome.

METHODS

Patients were scored according to age (1 point is given if patients were older than 80 years), GCS by admission (1 point for GCS 5-12, 2 points for GCS 3-4), and SDH volume (1 point for volume 50 mL). The sum of points determines the SHE score. Multivariate logistic regression analysis was performed to identify additional independent risk factors associated with 30-day mortality.

RESULTS

We evaluated 131 patients with aSDH who were treated at our institution between 2008 and 2020. We observed the same 30-day mortality rates published by Alford et al.: SHE 0: 4.3% vs. 3.2%, p = 1.0; SHE 1: 12.2% vs. 13.1%, p = 1.0; SHE 2: 36.6% vs. 32.7%, p = 0.8; SHE 3: 97.1% vs. 95.7%, p = 1.0 and SHE 4: 100% vs. 100%, p = 1.0. Additionally, 18 patients who developed status epilepticus (SE) had a mortality of 100 percent regardless of the SHE score. The distribution of SE among the groups was: 1 for SHE 1, 6 for SHE 2, 9 for SHE 3, and 2 for SHE 4. The logistic regression showed the surgical evacuation to be the only significant risk factor for developing the seizure. All patients who developed SE underwent surgery (p = 0.0065). Furthermore, SHE 3 and 4 showed no difference regarding the outcome between surgical and conservative treatment.

CONCLUSIONS

SHE score is a reliable mortality predictor for minor trauma acute subdural hematoma in elderly patients. In addition, we identified status epilepticus as a strong life-expectancy-limiting factor in patients undergoing surgical evacuation.

Quantitative EEG-Based Seizure Estimation in Super-Refractory Status Epilepticus

BACKGROUND

The objective of this study was to evaluate the accuracy of seizure burden in patients with super-refractory status epilepticus (SRSE) by using quantitative electroencephalography (qEEG).

METHODS

EEG recordings from 69 patients with SRSE (2009-2019) were reviewed and annotated for seizures by three groups of reviewers: two board-certified neurophysiologists using only raw EEG (gold standard), two neurocritical care providers with substantial experience in qEEG analysis (qEEG experts), and two inexperienced qEEG readers (qEEG novices) using only a qEEG trend panel.

RESULTS

Raw EEG experts identified 35 (51%) patients with seizures, accounting for 2950 seizures (3,126 min). qEEG experts had a sensitivity of 93%, a specificity of 61%, a false positive rate of 6.5 per day, and good agreement (κ = 0.64) between both qEEG experts. qEEG novices had a sensitivity of 98.5%, a specificity of 13%, a false positive rate of 15 per day, and fair agreement (κ = 0.4) between both qEEG novices. Seizure burden was not different between the qEEG experts and the gold standard (3,257 vs. 3,126 min), whereas qEEG novices reported higher burden (6066 vs. 3126 min).

CONCLUSIONS

Both qEEG experts and novices had a high sensitivity but a low specificity for seizure detection in patients with SRSE. qEEG could be a useful tool for qEEG experts to estimate seizure burden in patients with SRSE.

Antiseizure Medication Treatment and Outcomes in Patients with Subarachnoid Hemorrhage Undergoing Continuous EEG Monitoring

BACKGROUND

Patients with aneurysmal subarachnoid hemorrhage (aSAH) with electroencephalographic epileptiform activity (seizures, periodic and rhythmic patterns, and sporadic discharges) are frequently treated with antiseizure medications (ASMs). However, the safety and effectiveness of ASM treatment for epileptiform activity has not been established. We used observational data to investigate the effectiveness of ASM treatment in patients with aSAH undergoing continuous electroencephalography (cEEG) to develop a causal hypothesis for testing in prospective trials.

METHODS

This was a retrospective single-center cohort study of patients with aSAH admitted between 2011 and 2016. Patients underwent ≥ 24 h of cEEG within 4 days of admission. All patients received primary ASM prophylaxis until aneurysm treatment (typically within 24 h of admission). Treatment exposure was defined as reinitiation of ASMs after aneurysm treatment and cEEG initiation. We excluded patients with non-cEEG indications for ASMs (e.g., epilepsy, acute symptomatic seizures). Outcomes measures were 90-day mortality and good functional outcome (modified Rankin Scale scores 0-3). Propensity scores were used to adjust for baseline covariates and disease severity.

RESULTS

Ninety-four patients were eligible (40 continued ASM treatment; 54 received prophylaxis only). ASM continuation was not significantly associated with higher 90-day mortality (propensity-adjusted hazard ratio [HR] = 2.01 [95% confidence interval (CI) 0.57-7.02]). ASM continuation was associated with lower likelihood for 90-day good functional outcome (propensity-adjusted HR = 0.39 [95% CI 0.18-0.81]). In a secondary analysis, low-intensity treatment (low-dose single ASM) was not significantly associated with mortality (propensity-adjusted HR = 0.60 [95% CI 0.10-3.59]), although it was associated with a lower likelihood of good outcome (propensity-adjusted HR = 0.37 [95% CI 0.15-0.91]), compared with prophylaxis. High-intensity treatment (high-dose single ASM, multiple ASMs, or anesthetics) was associated with higher mortality (propensity-adjusted HR = 6.80 [95% CI 1.67-27.65]) and lower likelihood for good outcomes (propensity-adjusted HR = 0.30 [95% CI 0.10-0.94]) compared with prophylaxis only.

CONCLUSIONS

Our findings suggest the testable hypothesis that continuing ASMs in patients with aSAH with cEEG abnormalities does not improve functional outcomes. This hypothesis should be tested in prospective randomized studies.

Seizure prophylaxis following aneurysmal subarachnoid haemorrhage (SPSAH): study protocol for a multicentre randomised placebo-controlled trial of short-term sodium valproate prophylaxis in patients with acute subarachnoid haemorrhage

INTRODUCTION

Seizures are a common complication that leads to neurological deficits and affects outcomes after aneurysmal subarachnoid haemorrhage (aSAH). However, whether to use prophylactic anticonvulsants in patients with aSAH remains controversial. Our study aims to determine whether short-term (7 days) sodium valproate could prevent seizure occurrence and improve neurological function in patients with SAH caused by anterior circulation aneurysm rupture and treated with clipping.

METHODS AND ANALYSIS

In this multicentre randomised evaluator-blind placebo-controlled trial, 182 eligible patients with good-grade aSAH planned for surgical clipping will be enrolled from four neurosurgical centres in China. In addition to standard care, patients will be randomly assigned to receive sodium valproate 20 mg/kg daily or matching placebo. After aneurysmal clipping, patients will be followed up at discharge, 90 days and 180 days. The primary outcomes are the incidence of early and late seizures. The secondary outcomes include aSAH-related complications, sodium valproate-related adverse effects, modified Rankin Scale (mRS) (on discharge, at 90 days, 180 days), rate of good outcome (defined as mRS 0-2), all-cause death (at 90 days, 180 days) and Montreal Cognitive Assessment score (at 180 days). All analyses are by intention-to-treat.

ETHICS AND DISSEMINATION

This study will be conducted according to the principles of Declaration of Helsinki and good clinical practice guidelines. This trial involves human participants and has been approved by the ethics committee of West China Hospital. Informed consent will be achieved from each included patient and/or their legally authorised representative. Preliminary and final results from this study will be disseminated through manuscript publishing and international congresses presentations. Any protocol amendments will be approved by the ethics committee of West China Hospital and subsequently updated on ChiCTR.

TRIAL REGISTRATION NUMBER

ChiCTR.org identifier: ChiCTR2100050161.