Assessment of the Validity of the 2HELPS2B Score for Inpatient Seizure Risk Prediction

Seizure Assessment and Forecasting With Efficient Rapid-EEG: A Retrospective Multicenter Comparative Effectiveness Study

BACKGROUND AND OBJECTIVES

Approximately 30% of critically ill patients have seizures, and more than half of these seizures do not have an overt clinical correlate. EEG is needed to avoid missing seizures and prevent overtreatment with antiseizure medications. Conventional-EEG (cEEG) resources are logistically constrained and unable to meet their growing demand for seizure detection even in highly developed centers. Brief EEG screening with the validated 2HELPS2B algorithm was proposed as a method to triage cEEG resources, but it is hampered by cEEG requirements, primarily EEG technologists. Seizure risk-stratification using reduced time-to-application rapid response-EEG (rrEEG) systems (∼5 minutes) could be a solution. We assessed the noninferiority of the 2HELPS2B score on a 1-hour rrEEG compared to cEEG.

METHODS

A multicenter retrospective EEG diagnostic accuracy study was conducted from October 1, 2021, to July 31, 2022. Chart and EEG review performed with consecutive sampling at 4 tertiary care centers, included records of patients ≥18 years old, from January 1, 2018, to June 20, 2022. Monte Carlo simulation power analysis yielded n = 500 rrEEG; for secondary outcomes n = 500 cEEG and propensity-score covariate matching was planned. Primary outcome, noninferiority of rrEEG for seizure risk prediction, was assessed per area under the receiver operator characteristic curve (AUC). Noninferiority margin (0.05) was based on the 2HELPS2B validation study.

RESULTS

A total of 240 rrEEG with follow-on cEEG were obtained. Median age was 64 (interquartile range 22); 42% were female. 2HELPS2B on a 1-hour rrEEG met noninferiority to cEEG (AUC 0.85, 95% CI 0.78-0.90, p = 0.001). Secondary endpoints of comparison with a matched contemporaneous cEEG showed no significant difference in AUC (0.89, 95% CI 0.83-0.94, p = 0.31); in false negative rate for the 2HELPS2B = 0 group (p = 1.0) rrEEG (0.021, 95% CI 0-0.062), cEEG (0.016, 95% CI 0-0.048); nor in survival analyses.

DISCUSSION

2HELPS2B on 1-hour rrEEG is noninferior to cEEG for seizure prediction. Patients with low-risk (2HELPS2B = 0) may be able to forgo prolonged cEEG, allowing for increased monitoring of at-risk patients.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that rrEEG is noninferior to cEEG in calculating the 2HELPS2B score to predict seizure risk.

Survey of Continuous EEG Monitoring Practices in the United States

OBJECTIVE

Continuous EEG (cEEG) practice has markedly changed over the last decade given its utility in improving critical care outcomes. However, there are limited data describing the current cEEG infrastructure in US hospitals.

METHODS

A web-based cEEG practice survey was sent to neurophysiologists at 123 ACGME-accredited epilepsy or clinical neurophysiology programs.

RESULTS

Neurophysiologists from 100 (81.3%) institutions completed the survey. Most institutions had 3 to 10 EEG faculty (80.0%), 1 to 5 fellows (74.8%), ≥6 technologists (84.9%), and provided coverage to neurology ICUs with >10 patients (71.0%) at a time. Round-the-clock EEG technologist coverage was available at most (90.0%) institutions with technologists mostly being in-house (68.0%). Most institutions without after-hours coverage (8 of 10) attributed this to insufficient technologists. The typical monitoring duration was 24 to 48 hours (23.0 and 40.0%), most commonly for subclinical seizures (68.4%) and spell characterization (11.2%). Larger neurology ICUs had more EEG technologists ( p = 0.02), fellows ( p = 0.001), and quantitative EEG use ( p = 0.001).

CONCLUSIONS

This survey explores current cEEG practice patterns in the United States. Larger centers had more technologists and fellows. Overall technologist numbers are stable over time, but with a move toward more in-hospital compared with home-based coverage. Reduced availability of EEG technologists was a major factor limiting cEEG availability at some centers.

Guidelines for Seizure Prophylaxis in Adults Hospitalized with Moderate-Severe Traumatic Brain Injury: A Clinical Practice Guideline for Health Care Professionals from the Neurocritical Care Society

BACKGROUND

There is practice heterogeneity in the use, type, and duration of prophylactic antiseizure medications (ASMs) in patients with moderate-severe traumatic brain injury (TBI).

METHODS

We conducted a systematic review and meta-analysis of articles assessing ASM prophylaxis in adults with moderate-severe TBI (acute radiographic findings and requiring hospitalization). The population, intervention, comparator, and outcome (PICO) questions were as follows: (1) Should ASM versus no ASM be used in patients with moderate-severe TBI and no history of clinical or electrographic seizures? (2) If an ASM is used, should levetiracetam (LEV) or phenytoin/fosphenytoin (PHT/fPHT) be preferentially used? (3) If an ASM is used, should a long versus short (> 7 vs. ≤ 7 days) duration of prophylaxis be used? The main outcomes were early seizure, late seizure, adverse events, mortality, and functional outcomes. We used Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology to generate recommendations.

RESULTS

The initial literature search yielded 1998 articles, of which 33 formed the basis of the recommendations: PICO 1: We did not detect any significant positive or negative effect of ASM compared to no ASM on the outcomes of early seizure, late seizure, adverse events, or mortality. PICO 2: We did not detect any significant positive or negative effect of PHT/fPHT compared to LEV for early seizures or mortality, though point estimates suggest fewer late seizures and fewer adverse events with LEV. PICO 3: There were no significant differences in early or late seizures with longer versus shorter ASM use, though cognitive outcomes and adverse events appear worse with protracted use.

CONCLUSIONS

Based on GRADE criteria, we suggest that ASM or no ASM may be used in patients hospitalized with moderate-severe TBI (weak recommendation, low quality of evidence). If used, we suggest LEV over PHT/fPHT (weak recommendation, very low quality of evidence) for a short duration (≤ 7 days, weak recommendation, low quality of evidence).

Flexible cost-penalized Bayesian model selection: Developing inclusion paths with an application to diagnosis of heart disease

We propose a Bayesian model selection approach that allows medical practitioners to select among predictor variables while taking their respective costs into account. Medical procedures almost always incur costs in time and/or money. These costs might exceed their usefulness for modeling the outcome of interest. We develop Bayesian model selection that uses flexible model priors to penalize costly predictors a priori and select a subset of predictors useful relative to their costs. Our approach (i) gives the practitioner control over the magnitude of cost penalization, (ii) enables the prior to scale well with sample size, and (iii) enables the creation of our proposed inclusion path visualization, which can be used to make decisions about individual candidate predictors using both probabilistic and visual tools. We demonstrate the effectiveness of our inclusion path approach and the importance of being able to adjust the magnitude of the prior's cost penalization through a dataset pertaining to heart disease diagnosis in patients at the Cleveland Clinic Foundation, where several candidate predictors with various costs were recorded for patients, and through simulated data.

The Evolving Role of Electroencephalography in Postarrest Care

Electroencephalography is an accessible, portable, noninvasive and safe means of evaluating a patient's brain activity. It can aid in diagnosis and management decisions for post-cardiac arrest patients with seizures, myoclonus and other non-epileptic movements. It also plays an important role in a multimodal approach to neuroprognostication predicting both poor and favorable outcomes. Individuals ordering, performing and interpreting these tests, regardless of the indication, should understand the supporting evidence, logistical considerations, limitations and impact the results may have on postarrest patients and their families as outlined herein.

Immediate and long-term management practices of acute symptomatic seizures and epileptiform abnormalities: A cross-sectional international survey

OBJECTIVES

Acute symptomatic seizures (ASyS) and epileptiform abnormalities (EAs) on electroencephalography (EEG) are commonly encountered following acute brain injury. Their immediate and long-term management remains poorly investigated. We conducted an international survey to understand their current management.

METHODS

The cross-sectional web-based survey of 21 fixed-response questions was based on a common clinical encounter: convulsive or suspected ASyS following an acute brain injury. Respondents selected the option that best matched their real-world practice. Respondents completing the survey were compared with those who accessed but did not complete it.

RESULTS

A total of 783 individuals (44 countries) accessed the survey; 502 completed it. Almost everyone used anti-seizure medications (ASMs) for secondary prophylaxis after convulsive or electrographic ASyS (95.4% and 97.2%, respectively). ASM dose escalation after convulsive ASyS depends on continuous EEG (cEEG) findings: most often increased after electrographic seizures (78% of respondents), followed by lateralized periodic discharges (LPDs; 41%) and sporadic epileptiform discharges (sEDs; 17.5%). If cEEG is unrevealing, one in five respondents discontinue ASMs after a week. In the absence of convulsive and electrographic ASyS, a large proportion of respondents start ASMs due to LPD (66.7%) and sED (44%) on cEEG. At hospital discharge, most respondents (85%) continue ASM without dose change. The recommended duration of outpatient ASM use is as follows: 1-3 months (36%), 3-6 months (30%), 6-12 months (13%), >12 months (11%). Nearly one-third of respondents utilized ancillary testing before outpatient ASM taper, most commonly (79%) a <2 h EEG. Approximately half of respondents had driving restrictions recommended for 6 months after discharge.

SIGNIFICANCE

ASM use for secondary prophylaxis after convulsive and electrographic ASyS is a universal practice and is continued upon discharge. Outpatient care, particularly the ASM duration, varies significantly. Wide practice heterogeneity in managing acute EAs reflects uncertainty about their significance and management. These results highlight the need for a structured outpatient follow-up and optimized care pathway for patients with ASyS.

Recent advances in clinical electroencephalography

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

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.

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.

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

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

Development of a Predictive Model for Persistent Instability Following Conservative Management of Type II Odontoid Fractures

BACKGROUND

Odontoid fractures are common cervical spine fractures; however, significant controversy exists regarding their treatment. Risk factors for failure of conservative therapy have been identified, although no predictive risk score has been developed to aid in decision-making.

METHODS

A retrospective review was conducted of all patients evaluated at a level 1 trauma center. Patients identified with type II odontoid fractures as classified by the D'Alonzo Classification system who were treated with external orthosis were included in analysis. Patients were considered to have failed conservative therapy if they were offered surgical intervention. A machine learning method (Risk-SLIM) was then utilized to create a risk stratification score based on risk factors to identify patients at high risk for requiring surgical intervention due to persistent instability.

RESULTS

A total of 138 patients were identified as presenting with type II odontoid fractures that were treated conservatively; 38 patients were offered surgery for persistent instability. The Odontoid Fracture Predictive Model (OFPM) was created using a machine learning algorithm with a 5-fold cross validation area under the curve of 0.7389 (95% CI: 0.671 to 0.808). Predictive factors were found to include fracture displacement, displacement greater than 5 mm, comminution at the fracture base, and history of smoking. The probability of persistent instability was <5% with a score of 0 and 88% with a score of 5.

CONCLUSIONS

The OFPM model is a unique, quick, and accurate tool to assist in clinical decision-making in patients with type II odontoid fractures. External validation is necessary to evaluate the validity of these findings.

Status epilepticus in the ICU

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

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

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

OBJECTIVE

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

METHODS

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

RESULTS

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

SIGNIFICANCE

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

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Neurologic Complications of Critical Medical Illness

OBJECTIVE

This article reviews the neurologic complications encountered in patients admitted to non-neurologic intensive care units, outlines various scenarios in which a neurologic consultation can add to the diagnosis or management of a critically ill patient, and provides advice on the best diagnostic approach in the evaluation of these patients.

LATEST DEVELOPMENTS

Increasing recognition of neurologic complications and their adverse impact on long-term outcomes has led to increased neurology involvement in non-neurologic intensive care units. The COVID-19 pandemic has highlighted the importance of having a structured clinical approach to neurologic complications of critical illness as well as the critical care management of patients with chronic neurologic disabilities.

ESSENTIAL POINTS

Critical illness is often accompanied by neurologic complications. Neurologists need to be aware of the unique needs of critically ill patients, especially the nuances of the neurologic examination, challenges in diagnostic testing, and neuropharmacologic aspects of commonly used medications.

Spectrum of Ictal-Interictal Continuum: The Significance of 2HELPS2B Score and Background Suppression

PURPOSE

The aims of this study were to identify (1) the spectrum of ictal-interictal continuum (IIC) using the two dimensions of 2HELPS2B score and background suppression and (2) the response to subsequent anti-seizure drugs depends on the spectrum of IIC.

METHODS

The study prospectively enrolled 62 patients with IIC on EEG. The diagnosis of nonconvulsive status epilepticus was attempted with Salzburg criteria as well as clinical and neuroimaging data. IICs were dichotomized into patients with nonconvulsive status epilepticus and coma-IIC. The 2HELPS2B score was evaluated as the original proposal. The suppression ratio was analyzed with Persyst software.

RESULTS

Forty-seven cases (75.8%) were nonconvulsive status epilepticus-IIC and 15 cases (24.2%) were coma-IIC. Multivariate analysis revealed that the 2HELPS2B score was the only significant variable dichotomizing the spectrum of IIC (odds ratio, 3.0; 95% confidence interval, 1.06-8.6; P = 0.03 for nonconvulsive status epilepticus-IIC). In addition, the suppression ratio was significantly negatively correlated with 2HELPS2B scores (Spearman coefficient = -0.37, P = 0.004 for left hemisphere and Spearman coefficient = -0.3, P = 0.02 for right hemisphere). Furthermore, patients with higher 2HELPS2B score (74% [14/19] in ≥2 points vs. 44% [14/32] in <2 points, P = 0.03 by χ 2 test) and lower suppression ratio (62% [23/37] in ≤2.18 vs. 35% [6/17] in >2.18, P = 0.06 by χ 2 test) seemed to be more responsive to subsequent anti-seizure drug.

CONCLUSIONS

The 2HELPS2B score and background suppression can be used to distinguish the spectrum of IIC and thereby predict the response to subsequent anti-seizure drug.

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

EEG: Current relevance and promising quantitative analyses

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

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.

Machine learning for the early prediction of infants with electrographic seizures in neonatal hypoxic-ischemic encephalopathy

OBJECTIVE

To assess if early clinical and electroencephalography (EEG) features predict later seizure development in infants with hypoxic-ischemic encephalopathy (HIE).

METHODS

Clinical and EEG parameters <12 h of birth from infants with HIE across eight European Neonatal Units were used to develop seizure-prediction models. Clinical parameters included intrapartum complications, fetal distress, gestational age, delivery mode, gender, birth weight, Apgar scores, assisted ventilation, cord pH, and blood gases. The earliest EEG hour provided a qualitative analysis (discontinuity, amplitude, asymmetry/asynchrony, sleep-wake cycle [SWC]) and a quantitative analysis (power, discontinuity, spectral distribution, inter-hemispheric connectivity) from full montage and two-channel amplitude-integrated EEG (aEEG). Subgroup analysis, only including infants without anti-seizure medication (ASM) prior to EEG was also performed. Machine-learning (ML) models (random forest and gradient boosting algorithms) were developed to predict infants who would later develop seizures and assessed using Matthews correlation coefficient (MCC) and area under the receiver-operating characteristic curve (AUC).

RESULTS

The study included 162 infants with HIE (53 had seizures). Low Apgar, need for ventilation, high lactate, low base excess, absent SWC, low EEG power, and increased EEG discontinuity were associated with seizures. The following predictive models were developed: clinical (MCC 0.368, AUC 0.681), qualitative EEG (MCC 0.467, AUC 0.729), quantitative EEG (MCC 0.473, AUC 0.730), clinical and qualitative EEG (MCC 0.470, AUC 0.721), and clinical and quantitative EEG (MCC 0.513, AUC 0.746). The clinical and qualitative-EEG model significantly outperformed the clinical model alone (MCC 0.470 vs 0.368, p-value .037). The clinical and quantitative-EEG model significantly outperformed the clinical model (MCC 0.513 vs 0.368, p-value .012). The clinical and quantitative-EEG model for infants without ASM (n = 131) had MCC 0.588, AUC 0.832. Performance for quantitative aEEG (n = 159) was MCC 0.381, AUC 0.696 and clinical and quantitative aEEG was MCC 0.384, AUC 0.720.

SIGNIFICANCE

Early EEG background analysis combined with readily available clinical data helped predict infants who were at highest risk of seizures, hours before they occur. Automated quantitative-EEG analysis was as good as expert analysis for predicting seizures, supporting the use of automated assessment tools for early evaluation of HIE.

Indications for continuous electroencephalographic (cEEG) monitoring: What do they tell us?

OBJECTIVE

While studies have explored clinical and EEG predictors of seizures on continuous EEG (cEEG), the role of cEEG indications as predictors of seizures has not been studied. Our study aims to fill this knowledge gap.

METHODS

We used the prospective cEEG database at Cleveland Clinic for the 2016 calendar year. Patients ≥ 18 years who underwent cEEG for the indication of altered mental status (AMS) and seizure-like events (SLE: motor or patient-reported events) were included. Baseline characteristics and EEG findings were compared between the two groups. Multivariable regression was used to compare the two groups and identify seizure detection risk factors.

RESULTS

Of 2227 patients (mean age 59.4 years) who met the inclusion criteria, 882 (50% females) underwent cEEG for AMS and 1345(51% females) for SLE. SLE patients were younger(OR: 0.988, CI: 0.98-0.99, p < 0.001), had longer monitoring(OR:1.04, CI:1.00-1.07, p = 0.033), were more likely to have epilepsy-related-breakthrough seizures(OR:25.9, CI:0.5.89-115, p < 0.001), psychogenic non-epileptic spells (OR:6.85, CI:1.60-29.3, p = 0.008), were more awake (p < 0.001) and more likely to be on anti-seizure medications(OR:1.60, CI:1.29-1.98, p < 0.001). On multivariable analysis, SLE was an independent predictor of seizure detection (OR: 2.60, CI: 1.77-3.88, p < 0.001).

SIGNIFICANCE

Our findings highlight the differences in patients undergoing cEEG for AMS vs. SLE. SLE as a cEEG indication represents an independent predictor of seizures on cEEG and, therefore, deserves special attention. Future multicenter studies are needed to validate our findings.

From Alpha to Zeta: A Systematic Review of Zeta Waves

PURPOSE

Electroencephalogram is used for prognostication and diagnosis in critically ill patients and is vital in developing clinical management algorithms. Unique waveforms on EEG may distinguish neurological disorders and define a potential for seizures. To better characterize zeta waves, we sought to define their electroclinical spectrum.

METHODS

We performed a systematic review using MEDLINE, Embase, Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Review [through Ovid], Scopus, Science Citation Index Expanded and Emerging Sources Citation Index [through the Web of Science], and Epistemonikos. Grey literature resources were searched.

RESULTS

Five hundred thirty-seven articles were identified. After excluding duplicates and reviewing titles, abstracts, and bodies and bibliographies of articles, four studies reported 64 cases describing data from patients with zeta waves, with a prevalence of 3 to 4%. Various and often incomplete clinical, neuroimaging, and EEG data were available. 57 patients (89.1%) had a focal cerebral lesion concordant with the location of zeta waves on EEG. 26 patients (40.6%) had clinical seizures, all but one being focal onset. Thirteen patients (20%) had epileptiform activity on EEG. Typically, zeta waves were located in the frontal head regions, often with generalized, frontal, predominant, rhythmic delta activity and associated with focal EEG suppression.

CONCLUSIONS

Zeta waves frequently represent an underlying focal structural lesion. Their presence suggests a heightened risk for seizures. The small number of retrospective cases series in the literature reporting zeta waves might be an underrepresentation. We suggest a need for prospective studies of cEEG in critically ill patients to determine their clinical significance.

Rapid response EEG with needle electrodes in an intensive care unit with limited resources

Objective

Continuous EEG (cEEG) is the gold standard for detecting seizures and rhythmic and periodic patterns (RPPs) in critically ill patients but is often not available in health systems with limited resources. The current study aims to determine the feasibility and utility of low-cost, practical, limited montage, sub-dermal needle electrode EEG in a setting where otherwise no EEG would be available.

Methods

The study included all adult patients admitted to the intensive care unit of a single center over a 24-month period. Members of the existing ICU care team, mostly nurses, were trained to place 8 sub-dermal needle EEG electrodes to achieve rapid, limited montage-EEG recording. Clinical outcomes were recorded, including any reported major complications; and the EEG findings documented, including background characterization, RPPs, and seizures.

Results

One hundred twenty-three patients, mean age 68 years, underwent an average of 15.6 min of EEG recording. There were no complications of electrode placement. Overall, 13.0% had seizures (8.1% qualifying as status epilepticus [SE]), 18.7 % had generalized periodic discharges (GPDs), 4.9% had lateralized periodic discharges (LPDs), and 11.4 % sporadic epileptiform discharges (sEDs). Greater mortality was observed in patients with worse background EEGs, seizures, LPDs, or sEDs.

Conclusions

Rapid, limited montage EEG could be achieved safely and inexpensively in a broad population of critically ill patients following minimal training of existing care teams.

Significance

For resource poor centers or centers outside of major metropolitan areas who otherwise have no access to EEG, this may prove a useful method for screening for non-convulsive seizures and status epilepticus.

EEG as an indispensable tool during and after the COVID-19 pandemic: A review of tribulations and successes

During the coronavirus disease 2019 (COVID-19) pandemic, elective and non-emergent tests and procedures were delayed or suspended in lieu of diverting resources to more emergent treatment of critically ill patients and to avoid the spread and contraction of COVID-19. Further, the workforce was stretched thin, and healthcare facilities saw high turnover rates for full-time and contract employees, which strained the system and reduced the ability to provide clinical services. One of the casualties of these changes was electroencephalography (EEG) procedures, which have been performed less frequently throughout the world since the pandemic. Whether considered routine or emergent, the deferral of EEG studies can cause downstream effects, including a delay in diagnosis and initiation of treatment for epilepsy and non-epileptic seizures resulting in a higher risk of morbidity and mortality. Despite these limitations, the importance and utility of EEG and EEG technologists have been reinforced with the development of COVID-related neurological complications, including encephalopathy and seizures, which require EEG for diagnosis and treatment. Since the pandemic, reliance on remote telemonitoring has further highlighted the value and ease of using EEG. There has also been a heightened interest in rapid EEG devices that non-technologist professionals can attach quickly, allowing minimum patient contact to avoid exposure to COVID-19 and taking advantage of remote EEG monitoring. This review discusses the acute and potential long-term effects of the COVID-19 pandemic on the use and performance of EEG.

Creation and validation of a predictive model for lumbar synovial cyst recurrence following decompression without fusion

OBJECTIVE

Lumbar synovial cysts (LSCs) represent a relatively rare clinical pathology that may result in radiculopathy or neurogenic claudication. Because of the potential for recurrence of these cysts, some authors advocate for segmental fusion, as opposed to decompression alone, as a way to eliminate the risk for recurrence. The objective of this study was to create a predictive score for synovial cyst recurrence following decompression without fusion.

METHODS

A retrospective chart review was completed of all patients evaluated at a single center over 20 years who were found to have symptomatic LSCs requiring intervention. Only patients undergoing decompression without fusion were included in the analysis. Following this review, baseline characteristics were obtained as well as radiological information. A machine learning method (risk-calibrated supersparse linear integer model) was then used to create a risk stratification score to identify patients at high risk for symptomatic cyst recurrence requiring repeat surgical intervention. Following the creation of this model, a fivefold cross-validation was completed.

RESULTS

In total, 89 patients were identified who had complete radiological information. Of these 89 patients, 11 developed cyst recurrence requiring reoperation. The Lumbar Synovial Cyst Score was then created with an area under the curve of 0.83 and calibration error of 11.0%. Factors predictive of recurrence were found to include facet inclination angle > 45°, canal stenosis > 50%, T2 joint space hyperintensity, and presence of grade I spondylolisthesis. The probability of cyst recurrence ranged from < 5% for a score of 2 or less to > 88% for a score of 7.

CONCLUSIONS

The Lumbar Synovial Cyst Score model is a quick and accurate tool to assist in clinical decision-making in the treatment of LSCs.

How to evaluate and assess the epileptogenic/seizure potential of periodic discharges along the ictal-interictal continuum?

The ictal–interictal continuum (IIC) is a concept used for those particular EEG patterns that do not meet the strict criteria for status epilepticus but may be associated with neuronal injury. The aim of this article is to review equivocal periodic patterns and to discuss their clinical significance along the IIC. The risk of seizures increases when the frequency of periodic discharges exceeds 2 Hz and when the pattern has features of superimposed rhythmic, sharp, or fast activity (plus modifier). Lateralized periodic discharges (LPDs) are one of the best examples of the IIC. Criteria have been proposed for identifying patterns along the IIC that we called “peri-ictal” LPDs. There is ongoing debate about when to treat patients with these EEG patterns along this spectrum. The term IIC is only an EEG description, and does not in itself reflect a clinical diagnosis, hence management is based on EEG alone. The decision to intensify treatment is based on the combination of EEG, the underlying etiology, the level of consciousness, comorbidities, imaging, and other surrogates of “damage.”

Adult Critical Care Electroencephalography Monitoring for Seizures: A Narrative Review

Electroencephalography (EEG) is an important and relatively inexpensive tool that allows intensivists to monitor cerebral activity of critically ill patients in real time. Seizure detection in patients with and without acute brain injury is the primary reason to obtain an EEG in the Intensive Care Unit (ICU). In response to the increased demand of EEG, advances in quantitative EEG (qEEG) created an approach to review large amounts of data instantly. Finally, rapid response EEG is now available to reduce the time to detect electrographic seizures in limited-resource settings. This review article provides a concise overview of the technical aspects of EEG monitoring for seizures, clinical indications for EEG, the various available modalities of EEG, common and challenging EEG patterns, and barriers to EEG monitoring in the ICU.

Development and Validation of a Predictive Model for Failure of Medical Management in Spinal Epidural Abscesses

BACKGROUND

The optimal management of spinal epidural abscesses (SEA) secondary to primary spinal infections has demonstrated large variability in the literature. Although some literature suggests a high rate of neurological deterioration, others suggest failure of medical management is uncommon.

OBJECTIVE

To develop a predictive model to evaluate the likelihood of failure of medical therapy in the setting of SEA.

METHODS

A retrospective review was conducted of all patients presenting with SEA from primary spinal infections. Patients presenting with MRI evidence of SEA without neurological deficits were included. Failure of medical management was defined as requiring surgical intervention over 72 hours after the initiation of antibiotics. A machine learning method (Risk-Calibrated Supersparse Linear Integer Model) was used to create a risk stratification score to identify patients at high risk for requiring surgical intervention.

RESULTS

In total, 159 patients were identified as presenting with MRI findings of SEA without evidence of neurological deficit. Of these patients, 50 required delayed surgery compared with 109 whose infection were successfully treated with surgical intervention. The Spinal Epidural Abscess Predictive Score was created using a machine learning model with an area under the curve of 0.8043 with calibration error of 14.7%. Factors included active malignancy, spondylodiscitis, organism identification, blood cultures, and sex. The probability of failure of medical management ranged from <5% for a score of 2 or less and >95% for a score of 7 or more.

CONCLUSION

The Spinal Epidural Abscess Predictive Score model is a quick and accurate tool to assist in clinical decision-making in SEA.

Status epilepticus: review on diagnosis, monitoring and treatment

Status epilepticus (SE) is a frequent neurological emergency associated with high morbidity and mortality. According to the new ILAE 2015 definition, SE results either from the failure of the mechanisms responsible for seizure termination or initiation, leading to abnormally prolonged seizures. The definition has different time points for convulsive, focal and absence SE. Time is brain. There are changes in synaptic receptors leading to a more proconvulsant state and increased risk of brain lesion and sequelae with long duration. Management of SE must include three pillars: stop seizures, stabilize patients to avoid secondary lesions and treat underlying causes. Convulsive SE is defined after 5 minutes and is a major emergency. Benzodiazepines are the initial treatment, and should be given fast and an adequate dose. Phenytoin/fosphenytoin, levetiracetam and valproic acid are evidence choices for second line treatment. If SE persists, anesthetic drugs are probably the best option for third line treatment, despite lack of evidence. Midazolam is usually the best initial choice and barbiturates should be considered for refractory cases. Nonconvulsive status epilepticus has a similar initial approach, with benzodiazepines and second line intravenous (IV) agents, but after that, aggressiveness should be balanced considering risk of lesion due to seizures and medical complications caused by aggressive treatment. Usually, the best approach is the use of sequential IV antiepileptic drugs (oral/tube are options if IV options are not available). EEG monitoring is crucial for diagnosis of nonconvulsive SE, after initial control of convulsive SE and treatment control. Institutional protocols are advised to improve care.

Association Between Lateralized Periodic Discharge Amplitude and Seizure on Continuous EEG Monitoring in Patients With Structural Brain Abnormality in Critical Illness

Objective

To investigate the association between lateralized periodic discharge (LPD) amplitude and seizure risk on an individual level in patients with structural brain abnormality.

Methods

Retrospective case-control study of patients with structural brain abnormality undergoing continuous EEG monitoring was performed. We included 10 patients with LPDs and seizures as cases and 10 controls, patients with LPDs without seizure. Analysis was performed with a mixed-effects model with primary outcome measure of number of seizures per 8-h EEG epoch with fixed effects being variables of interest and random effect being subject ID.

Results

Epochs with seizures showed a higher absolute amplitude (corrected p = 0.04) and a higher relative amplitude (corrected p = 0.04) of LPDs. Additionally, the number of seizures was higher in epochs that had LPDs with plus features (uncorrected p = 0.002) and LPDs with higher relative amplitude (uncorrected p = 0.005).

Conclusion

Higher LPD amplitude is associated with increased risk of seizures on an individual patient level. A decreasing amplitude is suggestive of decreasing seizure risk, and may in fact be suggestive of decreasing ictal character of LPDs.

The Relationship Between Seizures and Spreading Depolarizations in Patients with Severe Traumatic Brain Injury

BACKGROUND

Both seizures and spreading depolarizations (SDs) are commonly detected using electrocorticography (ECoG) after severe traumatic brain injury (TBI). A close relationship between seizures and SDs has been described, but the implications of detecting either or both remain unclear. We sought to characterize the relationship between these two phenomena and their clinical significance.

METHODS

We performed a post hoc analysis of a prospective observational clinical study of patients with severe TBI requiring neurosurgery at five academic neurotrauma centers. A subdural electrode array was placed intraoperatively and ECoG was recorded during intensive care. SDs, seizures, and high-frequency background characteristics were quantified offline using published standards and terminology. The primary outcome was the Glasgow Outcome Scale-Extended score at 6 months post injury.

RESULTS

There were 138 patients with valid ECoG recordings; the mean age was 47 ± 19 years, and 104 (75%) were men. Overall, 2,219 ECoG-detected seizures occurred in 38 of 138 (28%) patients in a bimodal pattern, with peak incidences at 1.7-1.8 days and 3.8-4.0 days post injury. Seizures detected on scalp electroencephalography (EEG) were diagnosed by standard clinical care in only 18 of 138 (13%). Of 15 patients with ECoG-detected seizures and contemporaneous scalp EEG, seven (47%) had no definite scalp EEG correlate. ECoG-detected seizures were significantly associated with the severity and number of SDs, which occurred in 83 of 138 (60%) of patients. Temporal interactions were observed in 17 of 24 (70.8%) patients with both ECoG-detected seizures and SDs. After controlling for known prognostic covariates and the presence of SDs, seizures detected on either ECoG or scalp EEG did not have an independent association with 6-month functional outcome but portended worse outcome among those with clustered or isoelectric SDs.

CONCLUSIONS

In patients with severe TBI requiring neurosurgery, seizures were half as common as SDs. Seizures would have gone undetected without ECoG monitoring in 20% of patients. Although seizures alone did not influence 6-month functional outcomes in this cohort, they were independently associated with electrographic worsening and a lack of motor improvement following surgery. Temporal interactions between ECoG-detected seizures and SDs were common and held prognostic implications. Together, seizures and SDs may occur along a dynamic continuum of factors critical to the development of secondary brain injury. ECoG provides information integral to the clinical management of patients with TBI.

Management of Status Epilepticus and Indications for Inpatient Electroencephalography Monitoring

Status epilepticus (SE) is a neurologic emergency requiring immediate time-sensitive treatment to minimize neuronal injury and systemic complications. Minimizing time to administration of first- and second-line therapy is necessary to optimize the chances of successful seizure termination in generalized convulsive SE (GCSE). The approach to refractory and superrefractory GCSE is less well defined. Multiple agents with differing complementary actions that facilitate seizure termination are recommended. Nonconvulsive SE (NCSE) has a wide range of presentations and approaches to treatment. Continuous electroencephalography is critical to the management of both GCSE and NCSE, while its use for patients without seizure continues to expand.

Quantitative burst suppression on serial intermittent EEG in refractory status epilepticus

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Quantitative burst suppression ratios (QBSR) represent depth of EEG suppression.

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Deeper QBSR on serial intermittent EEG did not affect survival in RSE.

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Non-suppressive continuous EEG effects on RSE mortality merits further research.

Objectives

In refractory status epilepticus (RSE), the optimal degree of suppression (EEG burst suppression or merely suppressing seizures) remains unknown. Many centers lacking continuous EEG must default to serial intermittent recordings where uncertainty from lack of data may prompt more aggressive suppression. In this study, we sought to determine whether the quantitative burst suppression ratio (QBSR) from serial intermittent EEG recording is associated with RSE patient outcome.

Methods

We screened the EEG database to identify non-anoxic adult RSE patients for EEG and chart review. QBSR was calculated per 10-second EEG epoch as the percentage of time during which EEG amplitude was <3 µV. Patients who survived 1–3 months after discharge from ICU and hospital comprised the favorable group. Further to initial unadjusted univariate analysis of all pooled QBSR, we conducted multivariate analyses to account for individual patient confounders (“per-capita analysis”), uneven number of EEG recordings (“per-session analysis”), and uneven number of epochs (“per-epoch analysis”). We analyzed gender, anesthetic number, and adjusted status epilepticus severity score (aSTESS) as confounders.

Results

In 135,765 QBSR values over 160 EEG recordings (median 2.17 h every ≥24 h) from 17 patients on Propofol, Midazolam, and/or Ketamine, QBSR was deeper in the favorable group (p < 0.001) on initial unadjusted analysis. However, on adjusted multivariate analysis, there was consistently no association between QBSR and outcome. Higher aSTESS consistently associated with unfavorable outcome on per-capita (p = 0.033), per-session (p = 0.048) and per-epoch (p < 0.001) analyses. Greater maximal number of non-barbiturate anesthetic associated with favorable outcome on per-epoch analysis (p < 0.001).

Conclusions

There was no association between depth of EEG suppression using non-barbiturate anesthetic and RSE patient outcome based on QBSR from serial intermittent EEG. A per-epoch association between non-barbiturate anesthetic and favorable outcome suggests an effect from non-suppressive time-varying EEG content.

Significance

Targeting and following deeper burst suppression through non-barbiturate anesthetics on serial intermittent EEG monitoring of RSE is of limited utility.

Seizure Management in the Intensive Care Unit

Purpose of this review

This review presents current therapy for seizures in the intensive care unit. The reader is provided with recent evidence regarding the use of EEG in determining treatment for acute seizures. Proposed treatment approaches for seizures and status epilepticus are provided. Controversies and complexity of selecting treatments are discussed.

Recent findings

Critical Care EEG Monitoring Research Consortium analyzed the association of periodic and rhythmic electroencephalographic patterns with seizures and found that lateralized and generalized periodic discharges and lateralized rhythmic delta were associated with increased seizure risk. Applications using modified EEG techniques have demonstrated more rapid feedback to the ICU than was previously possible.

Summary

Accurate diagnosis and efficient treatment of seizures in the ICU is challenging due to patient factors, complexities of antiepileptic drug therapy, and the required expertise for EEG interpretation. Selection of optimally effective therapy for seizures or status epilepticus depends on multiple factors, making collaboration between neurophysiologists and the ICU team of paramount importance.

Seizures, Status Epilepticus, and Continuous EEG in the Intensive Care Unit

PURPOSE OF REVIEW

This article discusses the evolving definitions of seizures and status epilepticus in the critical care environment and the role of critical care EEG in both diagnosing seizure activity and serving as a predictive biomarker of clinical trajectory.

RECENT FINDINGS

Initial screening EEG has been validated as a tool to predict which patients are at risk of future seizures. However, accepted definitions of seizures and nonconvulsive status epilepticus encourage a treatment trial when the diagnosis on EEG is indeterminate because of periodic or rhythmic patterns or uncertain clinical correlation. Similarly, recent data have demonstrated the diagnostic utility of intracranial EEG in increasing the yield of seizure detection. EEG has additionally been validated as a diagnostic biomarker of covert consciousness, a predictive biomarker of cerebral ischemia and impending neurologic deterioration, and a prognostic biomarker of coma recovery and status epilepticus resolution. A recent randomized trial concluded that patients allocated to continuous EEG had no difference in mortality than those undergoing intermittent EEG but could not demonstrate whether this lack of difference was because of studying heterogeneous conditions, examining a monitoring tool rather than a therapeutic approach, or examining an outcome measure (mortality) perhaps more strongly associated with early withdrawal of life-sustaining therapy than to a sustained response to pharmacotherapy.

SUMMARY

Seizures and status epilepticus are events of synchronous hypermetabolic activity that are either discrete and intermittent or, alternatively, continuous. Seizures and status epilepticus represent the far end of a continuum of ictal-interictal patterns that include lateralized rhythmic delta activity and periodic discharges, which not only predict future seizures but may be further classified as status epilepticus on the basis of intracranial EEG monitoring or a diagnostic trial of antiseizure medication therapy. In particularly challenging cases, neuroimaging or multimodality neuromonitoring may be a useful adjunct documenting metabolic crisis. Specialized uses of EEG as a prognostic biomarker have emerged in traumatic brain injury for predicting language function and covert consciousness, cardiac arrest for predicting coma recovery, and subarachnoid hemorrhage for predicting neurologic deterioration due to delayed cerebral ischemia.

Anticonvulsant Primary and Secondary Prophylaxis for Acute Ischemic Stroke Patients: A Decision Analysis

Background and Purpose

We examined the impact of 3 anticonvulsant prophylaxis strategies on quality-adjusted life-years (QALYs) among patients with an incident acute ischemic stroke.

Methods

We created a decision tree to evaluate 3 strategies: (1) long-term primary prophylaxis; (2) short-term secondary prophylaxis after an early seizure with lifetime prophylaxis if persistent or late seizures (LSs) developed; and (3) long-term secondary prophylaxis if either early, late, or persistent seizures developed. The outcome was quality-adjusted life expectancy (QALY). We created 4 base cases to simulate common clinical scenarios: (1) female patient aged 40 years with a 2% or 11% lifetime risk of an LS and a 33% lifetime risk of an adverse drug reaction (ADR); (2) male patient aged 65 years with a 6% or 29% LS risk and 60% ADR risk; (3) male patient aged 50 years with an 18% or 65% LS risk and 33% ADR risk; and (4) female patient aged 80 years with a 29% or 83% LS risk and 80% ADR risk. In sensitivity analyses, we altered the parameters and assumptions.

Results

Across all 4 base cases, primary prophylaxis yielded the fewest QALYs when compared with secondary prophylaxis. For example, under scenario 1, strategies 2 and 3 resulted in 7.17 QALYs each, but strategy 1 yielded only 6.91 QALYs. Under scenario 4, strategies 2 and 3 yielded 2.85 QALYs compared with 1.40 QALYs for strategy 1. Under scenarios in which patients had higher ADR risks, strategy 2 led to the most QALYs.

Conclusions

Short-term therapy with continued anticonvulsant prophylaxis only after postischemic stroke seizures arise dominates lifetime primary prophylaxis in all scenarios examined. Our findings reinforce the necessity of close follow-up and discontinuation of anticonvulsant seizure prophylaxis started during acute ischemic stroke hospitalization.

Evaluation and Management of Seizures and Status Epilepticus

Seizures are frequently triggered by an inciting event and result from uninhibited excitation and/or decreased inhibition of a pool of neurons. If physiologic seizure abortive mechanisms fail, the ensuing unrestrained synchronization of neurons-status epilepticus-can be life-threatening and is associated with the potential for marked morbidity in survivors and high medical care costs. Prognosis is intimately related to etiology and its response to therapeutic measures. Timely implementation of pharmacologic therapy while concurrently performing a stepwise workup for etiology are paramount. Neurodiagnostic testing should guide titration of pharmacologic therapies, and help determine if there is a role for immune modulation.

Pharmacotherapy for Nonconvulsive Seizures and Nonconvulsive Status Epilepticus

Most seizures in critically ill patients are nonconvulsive. A significant number of neurological and medical conditions can be complicated by nonconvulsive seizures (NCSs) and nonconvulsive status epilepticus (NCSE), with brain infections, hemorrhages, global hypoxia, sepsis, and recent neurosurgery being the most prominent etiologies. Prolonged NCSs and NCSE can lead to adverse neurological outcomes. Early recognition requires a high degree of suspicion and rapid and appropriate duration of continuous electroencephalogram (cEEG) monitoring. Although high quality research evaluating treatment with antiseizure medications and long-term outcome is still lacking, it is probable that expeditious pharmacological management of NCSs and NCSE may prevent refractoriness and further neurological injury. There is limited evidence on pharmacotherapy for NCSs and NCSE, although a few clinical trials encompassing both convulsive and NCSE have demonstrated similar efficacy of different intravenous (IV) antiseizure medications (ASMs), including levetiracetam, valproate, lacosamide and fosphenytoin. The choice of specific ASMs lies on tolerability and safety since critically ill patients frequently have impaired renal and/or hepatic function as well as hematological/hemodynamic lability. Treatment frequently requires more than one ASM and occasionally escalation to IV anesthetic drugs. When multiple ASMs are required, combining different mechanisms of action should be considered. There are several enteral ASMs that could be used when IV ASM options have been exhausted. Refractory NCSE is not uncommon, and its treatment requires a very judicious selection of ASMs aiming at reducing seizure burden along with management of the underlying condition.

What's new on EEG monitoring in the ICU

Continuous video-EEG (cEEG, lasting hours to several days) is increasingly used in ICU patients, as it is more sensitive than routine video-EEG (rEEG, lasting 20-30 min) to detect seizures or status epilepticus, and allows more frequent changes in therapeutic regimens. However, cEEG is more resource-consuming, and its relationship to outcome compared to repeated rEEG has only been formally assessed very recently in a randomized controlled trial, which did not show any significant difference in terms of long-term mortality or functional outcome. Awaiting more refined trials, it seems therefore that using repeated rEEG in ICU patients may represent a reasonable alternative in resource-limited settings. Prolonged EEG has been used recently in patients with severe COVID-19 infection, the proportion of seizures seems albeit relatively low, and similar to ICU patients with medical conditions. As in any case a timely EEG recording is recommended in the ICU, r ecent technical developments may ease its use in clinical practice.

Can Big Data guide prognosis and clinical decisions in epilepsy?

Big Data is no longer a novel concept in health care. Its promise of positive impact is not only undiminished, but daily enhanced by seemingly endless possibilities. Epilepsy is a disorder with wide heterogeneity in both clinical and research domains, and thus lends itself to Big Data concepts and techniques. It is therefore inevitable that Big Data will enable multimodal research, integrating various aspects of "-omics" domains, such as phenome, genome, microbiome, metabolome, and proteome. This scope and granularity have the potential to change our understanding of prognosis and mortality in epilepsy. The scale of new discovery is unprecedented due to the possibilities promised by advances in machine learning, in particular deep learning. The subsequent possibilities of personalized patient care through clinical decision support systems that are evidence-based, adaptive, and iterative seem to be within reach. A major objective is not only to inform decision-making, but also to reduce uncertainty in outcomes. Although the adoption of electronic health record (EHR) systems is near universal in the United States, for example, advanced clinical decision support in or ancillary to EHRs remains sporadic. In this review, we discuss the role of Big Data in the development of clinical decision support systems for epilepsy care, prognostication, and discovery.

Does continuous electroencephalography influence therapeutic decisions in neurocritical care?

OBJECTIVES

In the neurocritical care unit (neuro-ICU), the impact of continuous EEG (cEEG) on therapeutic decisions and prognostication, including outcome prediction using the Status Epilepticus Severity Score (STESS), is poorly investigated. We studied to what extent cEEG contributes to treatment decisions, and how this relates to clinical outcome and the use of STESS in neurocritical care.

METHODS

We included patients admitted to the neuro-ICU or neurological step-down unit of a tertiary referral hospital between 05/2013 and 06/2015. Inclusion criteria were ≥20 h of cEEG monitoring and age ≥15 years. Exclusion criteria were primary epileptic and post-cardiac arrest encephalopathies.

RESULTS

Ninety-eight patients met inclusion criteria, 80 of which had status epilepticus, including 14 with super-refractory status. Median length of cEEG monitoring was 50 h (range 21-374 h). Mean STESS was lower in patients with favorable outcome 1 year after discharge (modified Rankin Scale [mRS] 0-2) compared to patients with unfavorable outcome (mRS 3-6), albeit not statistically significant (mean STESS 2.3 ± 2.1 vs 3.6 ± 1.7, p = 0.09). STESS had a sensitivity of 80%, a specificity of 42%, and a negative predictive value of 93% for outcome. cEEG results changed treatment decisions in 76 patients, including escalation of antiepileptic treatment in 65 and reduction in 11 patients.

CONCLUSION

Status Epilepticus Severity Score had a high negative predictive value but low sensitivity, suggesting that STESS should be used cautiously. Of note, cEEG results altered clinical decision-making in three of four patients, irrespective of the presence or absence of status epilepticus, confirming the clinical value of cEEG in neurocritical care.