The use and yield of continuous EEG in critically ill patients: A comparative study of three centers

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.

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.

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

Background and Objectives

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

Methods

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

Results

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

Discussion

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

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.

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

Background and Objectives

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

Methods

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

Results

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

Discussion

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

Impact of acute symptomatic seizures and their management on patient-reported outcomes after stroke

OBJECTIVE

Acute symptomatic seizures (ASyS) after stroke are not uncommon. However, the impact of ASyS and its management with anti-seizure medications (ASMs) on patient-reported outcome measures (PROMs) remains poorly investigated. The objective of our study is to evaluate the association between PROMs and ASyS and ASMs following stroke.

METHODS

We performed a retrospective cohort study of all stroke patients who underwent inpatient continuous EEG (cEEG) monitoring performed due to suspected ASyS, including the ones with observed convulsive ASyS, from 04/01/2012 to 03/31/2018, who completed PROMs within 6 months of hospital discharge. Patient-reported outcome measures, including one Neuro-QoL and six PROMIS v1.0 domain scales, were completed by patients as the standard of care in ambulatory stroke clinics. Since ASMs are sometimes used without clearly diagnosed ASyS, we performed group comparisons based on ASM status at discharge, irrespective of their ASyS status. T-tests or Wilcoxon rank sum tests compared continuous variables across groups and chi-square tests or Fisher's exact tests were used for categorical variables.

RESULTS

A total of 508 patients were included in the study [mean age 62.0 ± 14.1 years, 51.6% female; 244 (48.0%) ischemic stroke, 165 (32.5%) intracerebral hemorrhage, and 99 (19.5%) subarachnoid hemorrhage]. A total of 190 (37.4%) patients were discharged on ASMs. At the time of the first PROM, conducted a median of 47 (IQR = 33-78) days after the suspected ASyS, and 162 (31.9%) were on ASMs. ASM use was significantly higher in patients diagnosed with ASyS. Physical Function and Satisfaction with Social Roles and Activities were the most affected health domains. Patient-reported outcome measures were not significantly different between groups based on ASyS (electrographic and/or convulsive), ASM use at hospital discharge, or ASM status on the day of PROM completion.

SIGNIFICANCE

There were no differences in multiple domain-specific PROMs in patients with recent stroke according to ASyS status or ASM use suggesting the possible lack of the former's sensitivity to detect their impact. Additional research is necessary to determine if there is a need for developing ASyS-specific PROMs.

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.

Do acute EEG findings add to clinical features in predicting outcomes after status epilepticus and acute symptomatic seizures?

Status epilepticus is a potentially life-threatening medical emergency associated with poor functional outcomes. Improving our ability to accurately predict functional outcomes is beneficial to optimizing treatment strategies. Currently, there are four published status epilepticus scores in adults: STESS (Status Epilepticus Severity Score), EMSE (Epidemiology-Based Mortality Score in Status Epilepticus), END-IT (Encephalitis-Nonconvulsive-Diazepam resistance-Imaging-Tracheal intubation), and recently published ACD (Age-level of Consciousness-Duration of status epilepticus) score. The only available scale in the pediatric population is PEDSS (Pediatric CPC scale-EEG (normal vs abnormal)-Drug refractoriness-critical Sickness-Semiology). While these scores are useful research tools, currently there is little evidence to suggest their utility during real-time clinical care. Except for EMSE, none of the scores incorporate EEG findings for prognostication. Adding EEG features improves prognostic accuracy, as has been shown with the EMSE scale with and without the EEG component. Acute symptomatic seizures (AsyS) and early epileptiform abnormalities, especially nonconvulsive seizures, and periodic discharges, markedly increase the risk for subsequent unprovoked seizures. However, many of these patients may not need lifelong anti-seizure medications (ASMs). Continuous EEG monitoring shows that the majority of ASyS are nonconvulsive and can identify epileptic patterns. Dedicated specialty clinics for these patients, known as Post Acute Symptomatic Seizure (PASS) clinics, already exist in the United States. Post Acute Symptomatic Seizure clinics are ideal for both long-term clinical care and answering important research questions related to epileptogenesis, duration of ASM treatment required, and evolution of EEG findings. This topic was presented at the 8th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures held in September 2022. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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.

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.

Continuous Electroencephalogram Evaluation of Paroxysmal Events in Critically Ill Patients: Diagnostic Yield and Impact on Clinical Decision Making

BACKGROUND

Continuous electroencephalogram (cEEG) monitoring has been widely used in the intensive care unit (ICU) for the evaluation of patients in the ICU with altered consciousness to detect nonconvulsive seizures. We investigated the yield of cEEG when used to evaluate paroxysmal events in patients in the ICU and assessed the predictors of a diagnostic findings. The clinical impact of cEEG was also evaluated in this study.

METHODS

We identified patients in the ICU who underwent cEEG monitoring (> 6 h) to evaluate paroxysmal events between January 1, 2018, and December 31, 2019. We extracted patient demographics, medical history, neurological examination, brain imaging results, and the description of the paroxysmal events that necessitated the monitoring. We dichotomized the cEEG studies into those that captured habitual nonepileptic events or revealed epileptiform discharges (ictal or interictal), i.e., those considered to be of positive diagnostic yield (Y +), and those studies that did not show those findings (negative diagnostic yield, Y -). We also assessed the clinical impact of cEEG by documenting changes in administered antiseizure medication (ASM) before and after the cEEG.

RESULTS

We identified 159 recordings that were obtained for the indication of paroxysmal events, of which abnormal movements constituted the majority (n = 123). For the remaining events (n = 36), descriptions included gaze deviations, speech changes, and sensory changes. Twenty-nine percent (46 of 159) of the recordings were Y + , including the presence of ictal or interictal epileptiform discharges (n = 33), and captured habitual nonepileptic events (n = 13). A history of epilepsy was the only predictor of the study outcome. Detection of abnormal findings occurred within 6 h of the recording in most patients (30 of 46, 65%). Overall, cEEG studies led to 49 (31%) changes in ASM administration. The changes included dosage increases or initiation of ASM in patients with epileptiform discharges (n = 28) and reduction or elimination of ASM in patients with either habitual nonepileptic events (n = 5) or Y - cEEG studies (n = 16).

CONCLUSIONS

Continuous electroencephalogram monitoring is valuable in evaluating paroxysmal events, with a diagnostic yield of 29% in critically ill patients. A history of epilepsy predicts diagnostic studies. Both Y + and Y - cEEG studies may directly impact clinical decisions by leading to ASMs changes.

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.

Using electronic health data to explore effectiveness of ICU EEG and anti-seizure treatment

Objectives

The purpose of this study was to examine critical care continuous electroencephalography (cEEG) utilization and downstream anti‐seizure treatment patterns, their association with outcomes, and generate hypotheses for larger comparative effectiveness studies of cEEG‐guided interventions.

Methods

Single‐center retrospective study of critically ill patients (n = 14,523, age ≥18 years). Exposure defined as ≥24 h of cEEG and subsequent anti‐seizure medication (ASM) escalation, with or without concomitant anesthetic. Exposure window was the first 7 days of admission. Primary outcome was in‐hospital mortality. Multivariable analysis was performed using penalized logistic regression.

Results

One thousand and seventy‐three patients underwent ≥24 h of cEEG within 7 days of admission. After adjusting for disease severity, ≥24 h of cEEG followed by ASM escalation in patients not on anesthetics (n = 239) was associated with lower in‐hospital mortality (OR 0.76 [0.53–1.07]), though the finding did not reach significance. ASM escalation with concomitant anesthetic use (n = 484) showed higher odds for mortality (OR 1.41 [1.03–1.94]). In the seizures/status epilepticus subgroup, post cEEG ASM escalation without anesthetics showed lower odds for mortality (OR 0.43 [0.23–0.74]). Within the same subgroup, ASM escalation with concomitant anesthetic use showed higher odds for mortality (OR 1.34 [0.92–1.91]) though not significant.

Interpretation

Based on our findings we propose the following hypotheses for larger comparative effectiveness studies investigating the direct causal effect of cEEG‐guided treatment on outcomes: (1) cEEG‐guided ASM escalation may improve outcomes in critically ill patients with seizures; (2) cEEG‐guided treatment with combination of ASMs and anesthetics may not improve outcomes in all critically ill patients.

Evaluation and Management of First-Time Seizure in Adults

First seizures are often perceived as devastating events by patients and their families due to the fear of having a life-long disease. One in 10 people experiences one or more seizures during their lifetime, while 1 in 26 people develops epilepsy. Acute symptomatic seizures are often related to a provoking factor or an acute brain insult and typically do not recur. Careful history and clinical examination should guide clinicians' management plans. Electroencephalography and brain imaging, preferably with epilepsy-specific magnetic resonance imaging, may help characterize both etiology and risk of seizure recurrence. Antiepileptic drugs should be initiated in patients with newly diagnosed epilepsy. In patients without an epilepsy diagnosis, the decision to prescribe drugs depends on individual risk factors for seizure recurrence and possible complications from seizures, which should be discussed with the patient. Counseling about driving and lifestyle modifications should be provided early, often at the first seizure encounter.

Continuous vs Routine Electroencephalogram in Critically Ill Adults With Altered Consciousness and No Recent Seizure: A Multicenter Randomized Clinical Trial

Question

In patients with acute consciousness impairment and no recent seizures, does continuous electroencephalogram (cEEG) correlate with reduced mortality compared with repeated routine EEG (rEEG)?

Findings

In this pragmatic, multicenter randomized clinical trial analyzing 364 adults, cEEG translated into a higher rate of seizures/status epilepticus detection and antiseizure treatment modifications but did not improve mortality compared with rEEG.

Meaning

Pending larger studies, rEEG may represent a valid alternative to cEEG in centers with limited resources.

Importance

In critically ill patients with altered consciousness, continuous electroencephalogram (cEEG) improves seizure detection, but is resource-consuming compared with routine EEG (rEEG). It is also uncertain whether cEEG has an effect on outcome.

Objective

To assess whether cEEG is associated with reduced mortality compared with rEEG.

Design, Setting, and Participants

The pragmatic multicenter Continuous EEG Randomized Trial in Adults (CERTA) was conducted between 2017 and 2018, with follow-up of 6 months. Outcomes were assessed by interviewers blinded to interventions.The study took place at 4 tertiary hospitals in Switzerland (intensive and intermediate care units). Depending on investigators’ availability, we pragmatically recruited critically ill adults having Glasgow Coma Scale scores of 11 or less or Full Outline of Responsiveness score of 12 or less, without recent seizures or status epilepticus. They had cerebral (eg, brain trauma, cardiac arrest, hemorrhage, or stroke) or noncerebral conditions (eg, toxic-metabolic or unknown etiology), and EEG was requested as part of standard care. An independent physician provided emergency informed consent.

Interventions

Participants were randomized 1:1 to cEEG for 30 to 48 hours vs 2 rEEGs (20 minutes each), interpreted according to standardized American Clinical Neurophysiology Society guidelines.

Main Outcomes and Measures

Mortality at 6 months represented the primary outcome. Secondary outcomes included interictal and ictal features detection and change in therapy.

Results

We analyzed 364 patients (33% women; mean [SD] age, 63 [15] years). At 6 months, mortality was 89 of 182 in those with cEEG and 88 of 182 in those with rEEG (adjusted relative risk [RR], 1.02; 95% CI, 0.83-1.26; P = .85). Exploratory comparisons within subgroups stratifying patients according to age, premorbid disability, comorbidities on admission, deeper consciousness reduction, and underlying diagnoses revealed no significant effect modification. Continuous EEG was associated with increased detection of interictal features and seizures (adjusted RR, 1.26; 95% CI, 1.08-1.15; P = .004 and 3.37; 95% CI, 1.63-7.00; P = .001, respectively) and more frequent adaptations in antiseizure therapy (RR, 1.84; 95% CI, 1.12-3.00; P = .01).

Conclusions and Relevance

This pragmatic trial shows that in critically ill adults with impaired consciousness and no recent seizure, cEEG leads to increased seizure detection and modification of antiseizure treatment but is not related to improved outcome compared with repeated rEEG. Pending larger studies, rEEG may represent a valid alternative to cEEG in centers with limited resources.

Trial Registration

ClinicalTrials.gov Identifier: NCT03129438

Epidemiology of status epilepticus in a non-urban area in Switzerland

OBJECTIVE

The aim of this study is to provide a precise population-based data on incidence, types, and causes of SE according to the 2015 ILAE definition and classification using a prospectively cohort in an adult population of a non-urban area.

MATERIALS & METHODS

Prospective observational SE cohort in a single large community hospital. The center is the only one in the region (French-speaking Valais canton), with all available resources to treat SE (including neurologist available 24/7, EEG monitoring and ICU). Every adult patient with SE is included (except post-anoxic SE). All variables are collected prospectively using the 2015 ILAE status epilepticus classification.

RESULTS

We identified 103 patients with SE in the study period between 1st of May 2015 and 30th of June 2019 for a population of 260,855 people. The incidence is 8.6 per 100,000 adults per year with an overall case-fatality rate of 7.8%. SE was generalized convulsive in 52% of cases and nonconvulsive SE in coma in 34%.

CONCLUSIONS

Using a prospective reliable data collection with strict inclusion criteria, we found an incidence of 8.6 per 100,000 persons per year, in line with previous report using similar methods. The most severe forms-generalized convulsive and nonconvulsive SE in coma-represent the majority of cases. These data might be important for resources allocation in non-urban area with non-university healthcare system.

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.

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.

Association of Epileptiform Abnormality on Electroencephalography with Development of Epilepsy After Acute Brain Injury

BACKGROUND/OBJECTIVES

Epileptiform abnormalities (EA) on continuous electroencephalography (cEEG) are associated with increased risk of acute seizures; however, data on their association with development of long-term epilepsy are limited. We aimed to investigate the association of EA in patients with acute brain injury (ABI): ischemic or hemorrhagic stroke, traumatic brain injury, encephalitis, or posterior reversible encephalopathy syndrome, and subsequent development of epilepsy.

METHODS

This was a retrospective, single-center study of patients with ABI who had at least 6 hours of cEEG during the index admission between 1/1/2017 and 12/31/2018 and at least 12 months of follow-up. We compared patients with EAs; defined as lateralized periodic discharges (LPDs), lateralized rhythmic delta activity (LRDA), generalized periodic discharges (GPDs), and sporadic interictal epileptiform discharges (sIEDs) to patients without EAs on cEEG. The primary outcome was the new development of epilepsy, defined as the occurrence of spontaneous clinical seizures following hospital discharge. Secondary outcomes included time to development of epilepsy and use of anti-seizure medications (ASMs) at the time of last follow-up visit.

RESULTS

One hundred and one patients with ABI met study inclusion criteria. Thirty-one patients (30.7%) had EAs on cEEG. The median (IQR) time to cEEG was 2 (1-5) days. During a median (IQR) follow-up period of 19.1 (16.2-24.3) months, 25.7% of patients developed epilepsy; the percentage of patients who developed epilepsy was higher in those with EAs compared to those without EAs (41.9% vs. 18.6%, p = 0.025). Patients with EAs were more likely to be continued on ASMs during follow-up compared to patients without EAs (67.7% vs. 38.6%, p = 0.009). Using multivariable Cox regression analysis, after adjusting for age, mental status, electrographic seizures on cEEG, sex, ABI etiology, and ASM treatment on discharge, patients with EAs had a significantly increased risk of developing epilepsy compared to patients without EA (hazard ratio 3.39; 95% CI 1.39-8.26; p = 0.007).

CONCLUSIONS

EAs on cEEG in patients with ABI are associated with a greater than three-fold increased risk of new-onset epilepsy. cEEG findings in ABI may therefore be a useful risk stratification tool for assessing long-term risk of seizures and serve as a biomarker for new-onset epilepsy.

Clinical Electroencephalography Findings and Considerations in Hospitalized Patients With Coronavirus SARS-CoV-2

Background and Purpose

Reports have suggested that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes neurologic manifestations including encephalopathy and seizures. However, there has been relatively limited electrophysiology data to contextualize these specific concerns and to understand their associated clinical factors. Our objective was to identify EEG abnormalities present in patients with SARS-CoV-2, and to determine whether they reflect new or preexisting brain pathology.

Methods

We studied a consecutive series of hospitalized patients with SARS-CoV-2 who received an EEG, obtained using tailored safety protocols. Data from EEG reports and clinical records were analyzed to identify EEG abnormalities and possible clinical associations, including neurologic symptoms, new or preexisting brain pathology, and sedation practices.

Results

We identified 37 patients with SARS-CoV-2 who underwent EEG, of whom 14 had epileptiform findings (38%). Patients with epileptiform findings were more likely to have preexisting brain pathology (6/14, 43%) than patients without epileptiform findings (2/23, 9%; p = 0.042). There were no clear differences in rates of acute brain pathology. One case of nonconvulsive status epilepticus was captured, but was not clearly a direct consequence of SARS-CoV-2. Abnormalities of background rhythms were common, as may be seen in systemic illness, and in part associated with recent sedation (p = 0.022).

Conclusions

Epileptiform abnormalities were common in patients with SARS-CoV-2 referred for EEG, but particularly in the context of preexisting brain pathology and sedation. These findings suggest that neurologic manifestations during SARS-CoV-2 infection may not solely relate to the infection itself, but rather may also reflect patients' broader, preexisting neurologic vulnerabilities.

Clinical Electroencephalography Findings and Considerations in Hospitalized Patients with Coronavirus SARS-CoV-2

Background and Purpose Reports have suggested that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes neurologic manifestations including encephalopathy and seizures. However, there has been relatively limited electrophysiology data to contextualize these specific concerns and to understand their associated clinical factors. Our objective was to identify EEG abnormalities present in patients with SARS-CoV-2, and to determine whether they reflect new or preexisting brain pathology. Methods We studied a consecutive series of hospitalized patients with SARS-CoV-2 who received an EEG, obtained using tailored safety protocols. Data from EEG reports and clinical records were analyzed to identify EEG abnormalities and possible clinical associations, including neurologic symptoms, new or preexisting brain pathology, and sedation practices. Results We identified 37 patients with SARS-CoV-2 who underwent EEG, of whom 14 had epileptiform findings (38%). Patients with epileptiform findings were more likely to have preexisting brain pathology (6/14, 43%) than patients without epileptiform findings (2/23, 9%; p=0.042). There were no clear differences in rates of acute brain pathology. One case of nonconvulsive status epilepticus was captured, but was not clearly a direct consequence of SARS-CoV-2. Abnormalities of background rhythms were common, and patients recently sedated were more likely to lack a posterior dominant rhythm (p=0.022). Conclusions Epileptiform abnormalities were common in patients with SARS-CoV-2 referred for EEG, but particularly in the context of preexisting brain pathology and sedation. These findings suggest that neurologic manifestations during SARS-CoV-2 infection may not solely relate to the infection itself, but rather may also reflect patients' broader, preexisting neurologic vulnerabilities.

Validation of an algorithm of time-dependent electro-clinical risk stratification for electrographic seizures (TERSE) in critically ill patients

OBJECTIVE

The clinical implementation of continuous electroencephalography (CEEG) monitoring in critically ill patients is hampered by the substantial burden of work that it entails for clinical neurophysiologists. Solutions that might reduce this burden, including by shortening the duration of EEG to be recorded, would help its widespread adoption. Our aim was to validate a recently described algorithm of time-dependent electro-clinical risk stratification for electrographic seizure (ESz) (TERSE) based on simple clinical and EEG features.

METHODS

We retrospectively reviewed the medical records and EEG recordings of consecutive patients undergoing CEEG between October 1, 2015 and September, 30 2016 and assessed the sensitivity of TERSE for seizure detection, as well as the reduction in EEG time needed to be reviewed.

RESULTS

In a cohort of 407 patients and compared to full CEEG review, the model allowed the detection of 95% of patients with ESz and 97% of those with electrographic status epilepticus. The amount of CEEG to be recorded to detect ESz was reduced by two-thirds, compared to the duration of CEEG taht was actually recorded.

CONCLUSIONS

TERSE allowed accurate time-dependent ESz risk stratification with a high sensitivity for ESz detection, which could substantially reduce the amount of CEEG to be recorded and reviewed, if applied prospectively in clinical practice.

SIGNIFICANCE

Time-dependent electro-clinical risk stratification, such as TERSE, could allow more efficient practice of CEEG and its more widespread adoption. Future studies should aim to improve risk stratification in the subgroup of patients with acute brain injury and absence of clinical seizures.

Burden of Epileptiform Activity Predicts Discharge Neurologic Outcomes in Severe Acute Ischemic Stroke

BACKGROUND/OBJECTIVES

Clinical seizures following acute ischemic stroke (AIS) appear to contribute to worse neurologic outcomes. However, the effect of electrographic epileptiform abnormalities (EAs) more broadly is less clear. Here, we evaluate the impact of EAs, including electrographic seizures and periodic and rhythmic patterns, on outcomes in patients with AIS.

METHODS

This is a retrospective study of all patients with AIS aged ≥ 18 years who underwent at least 18 h of continuous electroencephalogram (EEG) monitoring at a single center between 2012 and 2017. EAs were classified according to American Clinical Neurophysiology Society (ACNS) nomenclature and included seizures and periodic and rhythmic patterns. EA burden for each 24-h epoch was defined using the following cutoffs: EA presence, maximum daily burden < 10% versus > 10%, maximum daily burden < 50% versus > 50%, and maximum daily burden using categories from ACNS nomenclature ("rare" < 1%; "occasional" 1-9%; "frequent" 10-49%; "abundant" 50-89%; "continuous" > 90%). Maximum EA frequency for each epoch was dichotomized into ≥ 1.5 Hz versus < 1.5 Hz. Poor neurologic outcome was defined as a modified Rankin Scale score of 4-6 (vs. 0-3 as good outcome) at hospital discharge.

RESULTS

One hundred and forty-three patients met study inclusion criteria. Sixty-seven patients (46.9%) had EAs. One hundred and twenty-four patients (86.7%) had poor outcome. On univariate analysis, the presence of EAs (OR 3.87 [1.27-11.71], p = 0.024) and maximum daily burden > 10% (OR 12.34 [2.34-210], p = 0.001) and > 50% (OR 8.26 [1.34-122], p = 0.035) were associated with worse outcomes. On multivariate analysis, after adjusting for clinical covariates (age, gender, NIHSS, APACHE II, stroke location, stroke treatment, hemorrhagic transformation, Charlson comorbidity index, history of epilepsy), EA presence (OR 5.78 [1.36-24.56], p = 0.017), maximum daily burden > 10% (OR 23.69 [2.43-230.7], p = 0.006), and maximum daily burden > 50% (OR 9.34 [1.01-86.72], p = 0.049) were associated with worse outcomes. After adjusting for covariates, we also found a dose-dependent association between increasing EA burden and increasing probability of poor outcomes (OR 1.89 [1.18-3.03] p = 0.009). We did not find an independent association between EA frequency and outcomes (OR: 4.43 [.98-20.03] p = 0.053). However, the combined effect of increasing EA burden and frequency ≥ 1.5 Hz (EA burden * frequency) was significantly associated with worse outcomes (OR 1.64 [1.03-2.63] p = 0.039).

CONCLUSIONS

Electrographic seizures and periodic and rhythmic patterns in patients with AIS are associated with worse outcomes in a dose-dependent manner. Future studies are needed to assess whether treatment of this EEG activity can improve outcomes.

Post-acute symptomatic seizure (PASS) clinic: A continuity of care model for patients impacted by continuous EEG monitoring

Objective

We present a model for the outpatient care of patients undergoing continuous electroencephalography (cEEG) monitoring during a hospitalization, named the post‐acute symptomatic seizure (PASS) clinic. We investigated whether establishing this clinic led to improved access to epileptologist care.

Methods

As part of the PASS clinic initiative, electronic health record (EHR) provides an automated alert to the inpatient care team discharging adults on first time antiepileptic drug (AED) after undergoing cEEG monitoring. The alert explains the rationale and facilitates scheduling for a PASS clinic appointment, three‐month after discharge, along with a same‐day extended (75 minutes) EEG. We compared the initial epilepsy clinic visits by patients undergoing cEEG in 2017, before (“Pre‐PASS” period and cohort) and after (“PASS” period and cohort) the alert went live in the EHR.

Results

Of the 170 patients included, 68 (40%) suffered a seizure during the mean follow‐up of 20.9 ± 10 months. AEDs were stopped or reduced in 66 out of 148 (44.6%) patients discharged on AEDs. Pre‐PASS cohort included 45 patients compared to 145 patients in the PASS cohort, accounting for 5.8% and 9.9% of patients, respectively, who underwent cEEG during the corresponding periods (odds ratio [OR] = 1.8, 95% CI = 1.26‐2.54, P = .001). The two cohorts did not differ in terms of electrographic or clinical seizures. The PASS cohort was significantly more likely to be followed up within 1‐6 months of discharge (OR = 4.6, 95% CI = 2.1‐10.1, P < .001) and have a pre‐clinic EEG (51.2% vs 11.1%; OR = 8.39, 95% CI = 3.1‐22.67, P < .001).

Significance

PASS clinic, a unique outpatient transition of care model for managing patients at risk of acute symptomatic seizure led to an almost twofold increase in access to an epileptologist. Future research should address the wide knowledge gap about the best post‐hospital discharge management practices for these patients.

Determinants and outcome of repeat continuous electroencephalogram monitoring-A case-control study

OBJECTIVE

A retrospective, single-center study to analyze the determinants of a repeat continuous EEG (cEEG) monitoring during hospitalization and its outcomes using a matched case-control study design.

METHODS

Adults with a repeat cEEG session (cases) were matched by age (±3 years), gender, and mental status to patients with a single cEEG (controls) during hospitalization. Several clinical and EEG characteristics were analyzed to identify predictors of repeat cEEG. Repeat cEEG outcomes were analyzed based on its yield of electrographic seizure. We investigated the predictors of finding increased epileptic potential (degree of association with electrographic seizures) on the repeat cEEG, a marker for possible anti-epileptic drugs (AEDs) management change.

RESULTS

A total of 213 (8.6% of all unique cEEG patients) cases were included. A multivariable conditional logistic regression model comparing cases and controls showed that the presence of acute brain insult [odds ratio (OR) = 3.36, 95% CI = 1.26-8.94, P = .015], longer hospital admission (OR = 1.11, 95% CI = 1.07-1.15, P < .001) and being on AEDs at the end of index cEEG (OR = 4.0, 95% CI = 1.8-8.87, P < .001) was determinants of a repeat cEEG. Among cases, 17 (8%) had electrographic seizures on repeat cEEG. Increased epileptic potential on repeat cEEG was noted in 34 (16%) cases. The latter is associated with change in etiology after the index cEEG (P = .03) and duration of repeat cEEG (P = .003) based on multivariable logistic regression model. AEDs were changed in 46 (21.6%) patients based on repeat cEEG findings.

SIGNIFICANCE

Repeat cEEG is not an uncommon practice. It leads to the diagnosis of electrographic seizures in a significant percentage of patients. With the potential of impacting AED management in 16%-21% patients, it should be considered in high-risk patients suffering acute brain insults undergoing prolonged hospitalization.

Electroencephalographic biomarkers of epilepsy development in patients with acute brain injury: a matched, parallel cohort study

Objective

This study was designed to investigate if highly epileptic electroencephalogram (EEG) findings in patients with acute brain injury increase the long‐term risk of epilepsy development.

Methods

Adults patients, lacking epilepsy history, with electrographic seizures or lateralized periodic discharges (LPDs) (cases) were identified and matched based on age, mental status, and etiology with the ones lacking any epileptiform activity (controls) on continuous EEG (cEEG) during hospitalization. The primary outcome of clinical seizures after hospital discharge and their antiepileptic drug (AED) status was determined using a telephonic interview. Logistic regression models using generalized estimating equations to account for the matched nature of the data were performed.

Results

A total of 70 cases [16 (22.9%) “LPDs only,” 34 (48.6%) “electrographic seizure only,” and 20 (28.6%) “both”] and controls were enrolled. A total of 22 (31.4%) cases developed epilepsy after a mean follow‐up duration of 20.6 ± 5.0 months compared to three (4.3%) controls. After adjusting for cEEG indication and follow‐up duration, the odds of cases developing epilepsy were almost 15 times higher compared to the controls (OR = 14.8, 95% CI = 2.4–92.3, P = 0.004). This elevated risk was despite a 10 times higher likelihood of cases to be taking AEDs at the last follow‐up (OR = 10.34, 95% CI = 3.7–29, P < 0.001).

Interpretation

Highly epileptic EEG findings in patients with acute brain injury may serve as prognostic biomarkers of epilepsy development. Although prospective studies are required to confirm our findings, it seems that with epilepsy developing in almost one‐third cases in less than 2‐year follow‐up period, such patients may potentially be ideal candidates for epilepsy prevention clinical trials.

Randomized trial of lacosamide versus fosphenytoin for nonconvulsive seizures

OBJECTIVE

The optimal treatment of nonconvulsive seizures in critically ill patients is uncertain. We evaluated the comparative effectiveness of the antiseizure drugs lacosamide (LCM) and fosphenytoin (fPHT) in this population.

METHODS

The TRENdS (Treatment of Recurrent Electrographic Nonconvulsive Seizures) study was a noninferiority, prospective, multicenter, randomized treatment trial of patients diagnosed with nonconvulsive seizures (NCSs) by continuous electroencephalography (cEEG). Treatment was randomized to intravenous (IV) LCM 400mg or IV fPHT 20mg phenytoin equivalents/kg. The primary endpoint was absence of electrographic seizures for 24 hours as determined by 1 blinded EEG reviewer. The frequency with which NCS control was achieved in each arm was compared, and the 90% confidence interval (CI) was determined. Noninferiority of LCM to fPHT was to be concluded if the lower bound of the CI for relative risk was >0.8.

RESULTS

Seventy-four subjects were enrolled (37 LCM, 37 fPHT) between August 21, 2012 and December 20, 2013. The mean age was 63.6 years; 38 were women. Seizures were controlled in 19 of 30 (63.3%) subjects in the LCM arm and 16 of 32 (50%) subjects in the fPHT arm. LCM was noninferior to fPHT (p = 0.02), with a risk ratio of 1.27 (90% CI = 0.88-1.83). Treatment emergent adverse events (TEAEs) were similar in both arms, occurring in 9 of 35 (25.7%) LCM and 9 of 37 (24.3%) fPHT subjects (p = 1.0).

INTERPRETATION

LCM was noninferior to fPHT in controlling NCS, and TEAEs were comparable. LCM can be considered an alternative to fPHT in the treatment of NCSs detected on cEEG. Ann Neurol 2018;83:1174-1185.

Monitoring for seizures in the intensive care unit

Acute symptomatic seizures have been known to occur in critically ill patients for many years. It was not until the widespread use of continuous EEG (cEEG) in the critically ill did we appreciate the incidence of electrographic seizures and status epilepticus in the ICU (Newey and Kinzy, 2018). Many of the seizures that occur are without any apparent clinical signs at the time of the recording. The patients often have convulsive seizures at onset then over the next few hours they lose the ability to have a generalized tonic clonic convulsion. They may then have subtle clinical signs (ictal nystagmus, facial twitching, etc.) or lose any apparent motor response. The end result is that many of the patients lose any clinical signs for their seizures by the time they are in the ICU and their seizures are termed "nonconvulsive." The recognition of seizures in the ICU is important for the effects the seizures have on outcome, particularly in morbidity and mortality and the risk of developing epilepsy after the acute symptomatic event. The use of cEEG in the ICU population has not only highlighted the high incidence of seizure activity but has also been used to assess overall cerebral function with applications in ischemia monitoring and prognostication, and to assess the degree of encephalopathy. This chapter will illustrate the core principles of cEEG monitoring in the critical care population including the incidence of seizures, determining who is at highest risk for seizures, how long patients should be monitored and ICU EEG seizure.

Continuous EEG is associated with favorable hospitalization outcomes for critically ill patients

OBJECTIVE

To characterize continuous EEG (cEEG) use patterns in the critically ill and to determine the association with hospitalization outcomes for specific diagnoses.

METHODS

We performed a retrospective cross-sectional study with National Inpatient Sample data from 2004 to 2013. We sampled hospitalized adult patients who received intensive care and then compared patients who underwent cEEG to those who did not. We considered diagnostic subgroups of seizure/status epilepticus, subarachnoid or intracerebral hemorrhage, and altered consciousness. Outcomes were in-hospital mortality, hospitalization cost, and length of stay.

RESULTS

In total, 7,102,399 critically ill patients were identified, of whom 22,728 received cEEG. From 2004 to 2013, the proportion of patients who received cEEG increased from 0.06% (95% confidence interval [CI] 0.03%-0.09%) to 0.80% (95% CI 0.62%-0.98%). While the cEEG cohort appeared more ill, cEEG use was associated with reduced in-hospital mortality after adjustment for patient and hospital characteristics (odds ratio [OR] 0.83, 95% CI 0.75-0.93, p < 0.001). This finding held for the diagnoses of subarachnoid or intracerebral hemorrhage and for altered consciousness but not for the seizure/status epilepticus subgroup. Cost and length of hospitalization were increased for the cEEG cohort (OR 1.17 and OR 1.11, respectively, p < 0.001).

CONCLUSIONS

There was a >10-fold increase in cEEG use from 2004 to 2013. However, this procedure may still be underused; cEEG was associated with lower in-hospital mortality but used for only 0.3% of the critically ill population. While administrative claims analysis supports the utility of cEEG for critically ill patients, our findings suggest variable benefit by diagnosis, and investigation with greater clinical detail is warranted.

Definition and Classification of Periodic and Rhythmic Patterns

The growing use of continuous video-EEG recording in the inpatient setting, in particular in patients with varying degrees of encephalopathy, has yielded a window to the brain with an excellent temporal resolution. This increasingly available tool has become more than an instrument to detect nonconvulsive seizures (its primary use), and clinical indications span from ischemia detection in acute brain injuries, neuroprognostication of comatose patients, to monitoring the degree of encephalopathy. In this context, abnormal findings such as periodic discharges and rhythmic delta activity were increasingly recognized; however, significant subjectivity remained in the interpretation of these findings pertaining to key features regarding their spatial involvement, prevalence of occurrence, duration, associated morphologic features, and behavior. In 2005, the American Clinical Neurophysiology Society proposed standardized definitions and classification of electroencephalographic rhythmic and periodic patterns. This was subsequently revised in 2011 and in 2012 and is now being used by centers worldwide, with the final version published in early 2013 as an official guideline of the ACNS. The resulting uniform terminology has allowed for significant advances in the understanding of the pathophysiology, epileptogenic potential, and overall clinical implication of these patterns. Investigators across multiple institutions are now able to collaborate while exploring diagnostic and therapeutic algorithms to these patterns, an effort that may soon provide definitive evidence guiding treating clinicians on the management of these patients.

Sensitivity of a Reduced EEG Montage for Seizure Detection in the Neurocritical Care Setting

INTRODUCTION

Neurocritical care units commonly implement the double-distance reduced EEG montage in postoperative neurosurgic patients who have structural barriers that hinder the placement of a standard 10-20 system array. Despite its widespread use, its sensitivity has not been adequately addressed. We evaluated the sensitivity and specificity of this montage for seizure detection.

METHODS

One hundred fifty-five full-montage continuous EEGs (cEEGs) completed in the Johns Hopkins University neurocritical care unit containing unequivocal electrographic seizures, status epilepticus, or other abnormalities were selected, comprising 73 ictal and 82 nonictal EEGs. EEGs were reformatted to the reduced montage, and 2-hour clips were reviewed independently by 2 epileptologists who documented the presence of seizures, status, or background abnormalities.

RESULTS

The sensitivity and specificity of the reduced montage for electrographic seizure detection was 81% and 92% with substantial interrater agreement (kappa 0.71). The sensitivity for status epilepticus was lower at 69%, but specificity remained high at 97% (kappa 0.67). Several EEGs miscategorized as nonictal were labeled as rather having rhythmic activity or periodic discharges. Evaluation of background patterns on the ictal-interictal continuum resulted in sensitivities ranging from 68% to 83%.

CONCLUSIONS

Although the specificity of the reduced array is good, epileptologists should remain vigilant when monitoring patients using this montage, given its reduced sensitivity for epileptic activity, especially status epilepticus.

Generalized and Lateralized Rhythmic Patterns

The relationship between generalized and lateralized rhythmic delta activity (RDA) and seizures is more ambiguous than the relationship between periodic discharges and seizures. Although frontally predominant generalized RDA is not associated with seizures, occipitally predominant RDA may be associated with the absence of seizures. Lateralized RDA seems to be more strongly associated with the presence of seizure activity. Appropriate recognition of generalized RDA and lateralized rhythmic delta activity may be confounded by benign etiologies of RDA, such as phi rhythm, slow alpha variant, subclinical rhythmic electrographic discharges of adults, or hyperventilation-induced high-amplitude rhythmic slowing. Angelman syndrome and NMDA-receptor antibody encephalitis can also produce morphologically distinct patterns of RDA.

Effect of epileptiform abnormality burden on neurologic outcome and antiepileptic drug management after subarachnoid hemorrhage

OBJECTIVE

To quantify the burden of epileptiform abnormalities (EAs) including seizures, periodic and rhythmic activity, and sporadic discharges in patients with aneurysmal subarachnoid hemorrhage (aSAH), and assess the effect of EA burden and treatment on outcomes.

METHODS

Retrospective analysis of 136 high-grade aSAH patients. EAs were defined using the American Clinical Neurophysiology Society nomenclature. Burden was defined as prevalence of <1%, 1-9%, 10-49%, 50-89%, and >90% for each 18-24 hour epoch. Our outcome measure was 3-month Glasgow Outcome Score.

RESULTS

47.8% patients had EAs. After adjusting for clinical covariates EA burden on first day of recording and maximum daily burden were associated with worse outcomes. Patients with higher EA burden were more likely to be treated with anti-epileptic drugs (AEDs) beyond the standard prophylactic protocol. There was no difference in outcomes between patients continued on AEDs beyond standard prophylaxis compared to those who were not.

CONCLUSIONS

Higher burden of EAs in aSAH independently predicts worse outcome. Although nearly half of these patients received treatment, our data suggest current AED management practices may not influence outcome.

SIGNIFICANCE

EA burden predicts worse outcomes and may serve as a target for prospective interventional controlled studies to directly assess the impact of AEDs, and create evidence-based treatment protocols.

Detecting silent seizures by their sound

OBJECTIVE

The traditional approach to interpreting electroencephalograms (EEGs) requires physicians with formal training to visually assess the waveforms. This approach can be less practical in critical settings where a trained EEG specialist is not readily available to review the EEG and diagnose ongoing subclinical seizures, such as nonconvulsive status epilepticus.

METHODS

We have developed a novel method by which EEG data are converted to sound in real time by letting the underlying electrophysiological signal modulate a voice tone that is in the audible range. Here, we explored whether individuals without any prior EEG training could listen to 15-second sonified EEG and determine whether the EEG represents seizures or nonseizure conditions. We selected 84 EEG samples to represent seizures (n = 7), seizure-like activity (n = 25), or nonperiodic, nonrhythmic activity (normal or focal/generalized slowing, n = 52). EEGs from single channels in the left and right hemispheres were then converted to sound files. After a 4-minute training video, medical students (n = 34) and nurses (n = 30) were asked to designate each audio sample as "seizure" or "nonseizure." We then compared their performance with that of EEG-trained neurologists (n = 12) and medical students (n = 29) who also diagnosed the same EEGs on visual display.

RESULTS

Nonexperts listening to single-channel sonified EEGs detected seizures with remarkable sensitivity (students, 98% ± 5%; nurses, 95% ± 14%) compared to experts or nonexperts reviewing the same EEGs on visual display (neurologists, 88% ± 11%; students, 76% ± 19%). If the EEGs contained seizures or seizure-like activity, nonexperts listening to sonified EEGs rated them as seizures with high specificity (students, 85% ± 9%; nurses, 82% ± 12%) compared to experts or nonexperts viewing the EEGs visually (neurologists, 90% ± 7%; students, 65% ± 20%).

SIGNIFICANCE

Our study confirms that individuals without EEG training can detect ongoing seizures or seizure-like rhythmic periodic patterns by listening to sonified EEG. Although sonification of EEG cannot replace the traditional approaches to EEG interpretation, it provides a meaningful triage tool for fast assessment of patients with suspected subclinical seizures.

An update on the recognition and treatment of non-convulsive status epilepticus in the intensive care unit

INTRODUCTION

Non-convulsive status epilepticus (NCSE) is a complex and diverse condition which is often an under-recognised entity in the intensive care unit. When NCSE is identified the optimal treatment strategy is not always clear. Areas covered: This review is based on a literature review of the key literature in the field over the last 5-10 years. The articles were selected based on their importance to the field by the authors. Expert commentary: This review discusses the complex situations when a neurological consultation may occur in a critical care setting and provides an update on the latest evidence regarding the recognition of NCSE and the decision making around determining the aggressiveness of treatment. It also considers the ictal-interictal continuum of conditions which may be met with, particularly in the era of continuous EEG, and provides an approach for dealing with these. Suggestions for how the field will develop are discussed.