Management of status epilepticus in pregnancy: a clinician survey.

BACKGROUND: Status epilepticus in pregnancy (SEP) is rare and life-threatening for both mother and fetus. There are well-established guidelines for the management of women with epilepsy during pregnancy; however, there is little evidence guiding the management of SEP, leading to uncertainty among treating physicians. Therefore, this survey aims to investigate the real-world practices of physicians treating SEP to explore management approaches for improvements in care. METHODS: An anonymous, electronic survey was created and distributed to neurointensivists and neurologists between September and December 2021. RESULTS: One hundred physicians initiated the survey and 95 completed it in full: 87 (87%, 87/100) identified neurology as their primary specialty, 31 had subspecialty training in neurocritical care, and 48 had subspecialty training in epilepsy and/or clinical neurophysiology. Over half of the survey respondents (67%, 67/100) reported having participated in the management of SEP, with 48.9% (49/98) having done so in the past year. Most survey respondents (73%, 73/100) reported that their management approach to SEP is different than that of non-pregnant patients. Survey respondents were more likely to involve epilepsy consultants when treating SEP (58.5%, 58/99) and the vast majority involved Obstetrics/Maternal Fetal Medicine consultants (90.8%, 89/98). Survey respondents showed a clear preference for levetiracetam (89.7%, 87/97) in the treatment of benzodiazepine refractory status epilepticus followed by lacosamide (61%, 60/98) if an additional second line agent was needed. Valproate and phenobarbital were unlikely to be used. There was less agreement for the management of refractory and super-refractory SEP. CONCLUSIONS: Levetiracetam is the most frequently used anti-seizure medication (ASM) for benzodiazepine-refractory SEP. Survey participants tended to manage SEP differently than in non-pregnant patients including greater involvement of interdisciplinary teams as well as avoidance of ASMs associated with known teratogenicity.

Electroencephalography as a Biomarker of Prognosis in Acute Brain Injury.

Electroencephalography (EEG) is a noninvasive tool that allows the monitoring of cerebral brain function in critically ill patients, aiding with diagnosis, management, and prognostication. Specific EEG features have shown utility in the prediction of outcomes in critically ill patients with status epilepticus, acute brain injury (ischemic stroke, intracranial hemorrhage, subarachnoid hemorrhage, and traumatic brain injury), anoxic brain injury, and toxic-metabolic encephalopathy. Studies have also found an association between particular EEG patterns and long-term functional and cognitive outcomes as well as prediction of recovery of consciousness following acute brain injury. This review summarizes these findings and demonstrates the value of utilizing EEG findings in the determination of prognosis.

Ellen R. Grass Lecture: Disparities in Access to Neurodiagnostic Testing.

Limited access to EEG services in rural areas creates health disparities in neurological care, including unnecessary transfers and delays in diagnosis and treatment. Rural facilities face several challenges to expanding EEG resources, including a lack of neurologists, technologists, EEG equipment, and adequate IT infrastructure. Potential solutions include investment in innovative technology, expansion of the workforce, and development of hub-and-spoke EEG networks. Bridging the EEG gap requires collaboration between academic and community practices to advance practical technologies, train competent personnel and develop cost-effective resource-sharing strategies.

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

OBJECTIVES: Status epilepticus (SE) is associated with significantly higher morbidity and mortality than isolated seizures. Our objective was to identify clinical diagnoses and rhythmic and periodic electroencephalogram patterns (RPPs) associated with SE and seizures. DESIGN: Retrospective cohort study. SETTING: Tertiary-care hospitals. SUBJECTS: Twelve thousand four hundred fifty adult hospitalized patients undergoing continuous electroencephalogram (cEEG) monitoring in selected participating sites in the Critical Care EEG Monitoring Research Consortium database (February 2013 to June 2021). INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: We defined an ordinal outcome in the first 72 hours of cEEG: no seizures, isolated seizures without SE, or SE (with or without isolated seizures). Composite groups included isolated seizures or SE (AnySz) and no seizure or isolated seizures. In this cohort (mean age: 60 ± 17 yr), 1,226 patients (9.8%) had AnySz and 439 patients (3.5%) had SE. In a multivariate model, factors independently associated with SE were cardiac arrest (9.2% with SE; adjusted odds ratio, 8.8 [6.3-12.1]), clinical seizures before cEEG (5.7%; 3.3 [2.5-4.3]), brain neoplasms (3.2%; 1.6 [1.0-2.6]), lateralized periodic discharges (LPDs) (15.4%; 7.3 [5.7-9.4]), brief potentially ictal rhythmic discharges (BIRDs) (22.5%; 3.8 [2.6-5.5]), and generalized periodic discharges (GPDs) (7.2%; 2.4 [1.7-3.3]). All above variables and lateralized rhythmic delta activity (LRDA) were also associated with AnySz. Factors disproportionately increasing odds of SE over isolated seizures were cardiac arrest (7.3 [4.4-12.1]), clinical seizures (1.7 [1.3-2.4]), GPDs (2.3 [1.4-3.5]), and LPDs (1.4 [1.0-1.9]). LRDA had lower odds of SE compared with isolated seizures (0.5 [0.3-0.9]). RPP modifiers did not improve SE prediction beyond RPPs presence/absence ( p = 0.8). CONCLUSIONS: Using the largest existing cEEG database, we identified specific predictors of SE (cardiac arrest, clinical seizures prior to cEEG, brain neoplasms, LPDs, GPDs, and BIRDs) and seizures (all previous and LRDA). These findings could be used to tailor cEEG monitoring for critically ill patients.

Clinical Neurophysiology Fellowship Program Directors Survey on a Standardized Fellowship Match Process: A Call for Action.

PURPOSE: To survey US Clinical Neurophysiology (CNP) fellowship program directors on the nature of CNP and related training programs, current recruitment cycle, and views for a standardized process. METHODS: A 23-question electronic survey was sent to all 93 US Accreditation Council for Graduate Medical Education-accredited CNP fellowship program directors from December 2020 to January 2021. RESULTS: The response rate was 60%. There was great variability in the number of CNP positions and CNP tracks offered. The following tracks were identified: 48% EEG dominant, 26% EMG dominant, 22% split equally between EEG and EMG, and 2% and 1% were neurophysiologic intraoperative monitoring and autonomic dominant, respectively. Of the responding institutions, 43% offered a second year of training options to CNP fellows, mainly in conjunction with Epilepsy fellowship, which was pursued by 25% of CNP fellows. Many programs indicated flexibility in their design between different CNP tracks or between CNP and other related training programs based on the available candidates. The median percentage of CNP fellowship positions filled over the last 5 years was 80%, and there was great variation in the recruitment timeline across institutions. Overall, 86% of program directors favored a universal timeline and 71% favored a formal match for CNP. The respondents were split between an independent CNP match (39%) and joining the initiatives of affiliate societies on a standardized process (61%). CONCLUSIONS: There is significant heterogeneity in the makeup of the CNP fellowship programs and the recruitment process. The majority of CNP program directors are in favor of standardization of the recruitment process.

Impact of the COVID-19 Pandemic on Continuous EEG Utilization.

PURPOSE: The coronavirus disease 2019 (COVID-19) has significantly impacted healthcare delivery and utilization. The aim of this article was to assess the impact of the COVID-19 pandemic on in-hospital continuous electroencephalography (cEEG) utilization and identify areas for process improvement. METHODS: A 38-question web-based survey was distributed to site principal investigators of the Critical Care EEG Monitoring Research Consortium, and institutional contacts for the Neurodiagnostic Credentialing and Accreditation Board. The survey addressed the following aspects of cEEG utilization: (1) general center characteristics, (2) cEEG utilization and review, (3) staffing and workflow, and (4) health impact on EEG technologists. RESULTS: The survey was open from June 12, 2020 to June 30, 2020 and distributed to 174 centers with 79 responses (45.4%). Forty centers were located in COVID-19 hotspots. Fifty-seven centers (72.1%) reported cEEG volume reduction. Centers in the Northeast were most likely to report cEEG volume reduction (odds ratio [OR] 7.19 [1.53-33.83]; P = 0.012). Additionally, centers reporting decrease in outside hospital transfers reported cEEG volume reduction; OR 21.67 [4.57-102.81]; P ≤ 0.0001. Twenty-six centers (32.91%) reported reduction in EEG technologist coverage. Eighteen centers had personal protective equipment shortages for EEG technologists. Technologists at these centers were more likely to quarantine for suspected or confirmed COVID-19; OR 3.14 [1.01-9.63]; P = 0.058. CONCLUSIONS: There has been a widespread reduction in cEEG volume during the pandemic. Given the anticipated duration of the pandemic and the importance of cEEG in managing hospitalized patients, methods to optimize use need to be prioritized to provide optimal care. Because the survey provides a cross-sectional assessment, follow-up studies can determine the long-term impact of the pandemic on cEEG utilization.

Continuous EEG Findings in Autoimmune Encephalitis.

PURPOSE: Autoimmune encephalitis (AE) is a cause of new-onset seizures, including new-onset refractory status epilepticus, yet there have been few studies assessing the EEG signature of AE. METHODS: Multicenter retrospective review of patients diagnosed with AE who underwent continuous EEG monitoring. RESULTS: We identified 64 patients (male, 39%; white, 49%; median age, 44 years); of whom, 43 (67%) were antibody-proven AE patients. Of the patients with confirmed antibody AE, the following were identified: N-methyl-D-aspartate receptor (n = 17, 27%), voltage-gated potassium channel (n = 16, 25%), glutamic acid decarboxylase (n = 6, 9%), and other (n = 4, 6%). The remaining patients were classified as probable antibody-negative AE (n = 11, 17%), definite limbic encephalitis (antibody-negative) (n = 2, 3%), and Hashimoto encephalopathy (n = 8, 13%). Fifty-three percent exhibited electrographic seizures. New-onset refractory status epilepticus was identified in 19% of patients. Sixty-three percent had periodic or rhythmic patterns; of which, 38% had plus modifiers. Generalized rhythmic delta activity was identified in 33% of patients. Generalized rhythmic delta activity and generalized rhythmic delta activity plus fast activity were more common in anti-N-methyl-D-aspartate AE (P = 0.0001 and 0.0003, respectively). No other periodic or rhythmic patterns exhibited AE subtype association. Forty-two percent had good outcome on discharge. Periodic or rhythmic patterns, seizures, and new-onset refractory status epilepticus conferred an increased risk of poor outcome (OR, 6.4; P = 0.0012; OR, 3; P = 0.0372; OR, 12.3; P = 0.02, respectively). CONCLUSION: Our study confirms a signature EEG pattern in anti-N-methyl-D-aspartate AE, termed extreme delta brush, identified as generalized rhythmic delta activity plus fast activity in our study. We found no other pattern association with other AE subtypes. We also found a high incidence of seizures among patients with AE. Finally, periodic or rhythmic patterns, seizures, and new-onset refractory status epilepticus conferred an increased risk of poor outcome regardless of AE subtype.

Addressing the epilepsy surgery gap: Impact of community/tertiary epilepsy center collaboration.

To assess whether a formal collaboration between a non-surgical, community epilepsy center and a surgical, tertiary-care epilepsy center can improve patient progress throughout the pre-surgical referral process, and to elucidate predictors of referral completion among inter-center referrals. The inter-center referral process was tracked, and the number of patients completing surgical conference (primary outcome) and epilepsy surgery at the tertiary center were collected and compared in the 45-month immediate pre/post-collaboration periods. Demographic and clinical variables were collected on post-collaboration inter-center patient referrals to explore factors associated with completion of the referral process. Compared to the pre-collaboration period, the proportion of tertiary center epilepsy surgery conference patients referred from the community epilepsy center increased from 3/88 to 14/113 (263% increase, p = .01) during the post-collaboration period. The proportion of patients completing surgery via the community to tertiary referral process increased from 2/63 pre-collaboration to 8/71 post-collaboration (254% increase, p = .04). Referral completion was associated with higher seizure frequency, shorter travel distance, private insurance status and positive employment status (p < 0.05). Collaboration agreements between community and tertiary-care epilepsy centers may improve patient completion of the epilepsy surgery referral process. Implementation of similar programs at other centers may be beneficial in reducing the epilepsy surgery gap.

Stigma and functional neurological disorder: a research agenda targeting the clinical encounter.

Stigma against patients with functional neurological disorder (FND) presents obstacles to diagnosis, treatment, and research. The lack of biomarkers and the potential for symptoms to be misunderstood, invalidated, or dismissed can leave patients, families, and healthcare professionals at a loss. Stigma exacerbates suffering and unmet needs of patients and families, and can result in poor clinical management and prolonged, repetitive use of healthcare resources. Our current understanding of stigma in FND comes from surveys documenting frustration experienced by providers and distressing healthcare interactions experienced by patients. However, little is known about the origins of FND stigma, its prevalence across different healthcare contexts, its impact on patient health outcomes, and optimal methods for reduction. In this paper, we set forth a research agenda directed at better understanding the prevalence and context of stigma, clarifying its impact on patients and providers, and promoting best practices for stigma reduction.

Interictal Epileptiform Discharge Detection in EEG in Different Practice Settings.

OBJECTIVE: The goal of the study was to measure the performance of academic and private practice (PP) neurologists in detecting interictal epileptiform discharges in routine scalp EEG recordings. METHODS: Thirty-five EEG scorers (EEGers) participated (19 academic and 16 PP) and marked the location of ETs in 200 30-second EEG segments using a web-based EEG annotation system. All participants provided board certification status, years of Epilepsy Fellowship Training (EFT), and years in practice. The Persyst P13 automated IED detection algorithm was also run on the EEG segments for comparison. RESULTS: Academic EEGers had an average of 1.66 years of EFT versus 0.50 years of EFT for PP EEGers (P < 0.0001) and had higher rates of board certification. Inter-rater agreement for the 35 EEGers was fair. There was higher performance for EEGers in academics, with at least 1.5 years of EFT, and with American Board of Clinical Neurophysiology and American Board of Psychiatry and Neurology-E specialty board certification. The Persyst P13 algorithm at its default setting (perception value = 0.4) did not perform as well at the EEGers, but at substantially higher perception value settings, the algorithm performed almost as well human experts. CONCLUSIONS: Inter-rater agreement among EEGers in both academic and PP settings varies considerably. Practice location, years of EFT, and board certification are associated with significantly higher performance for IED detection in routine scalp EEG. Continued medical education of PP neurologists and neurologists without EFT is needed to improve routine scalp EEG interpretation skills. The performance of automated detection algorithms is approaching that of human experts.

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.

Association of an Electroencephalography-Based Risk Score With Seizure Probability in Hospitalized Patients.

Importance: Continuous electroencephalography (EEG) use in critically ill patients is expanding. There is no validated method to combine risk factors and guide clinicians in assessing seizure risk. Objective: To use seizure risk factors from EEG and clinical history to create a simple scoring system associated with the probability of seizures in patients with acute illness. Design, Setting, and Participants: We used a prospective multicenter (Emory University Hospital, Brigham and Women's Hospital, and Yale University Hospital) database containing clinical and electrographic variables on 5427 continuous EEG sessions from eligible patients if they had continuous EEG for clinical indications, excluding epilepsy monitoring unit admissions. We created a scoring system model to estimate seizure risk in acutely ill patients undergoing continuous EEG. The model was built using a new machine learning method (RiskSLIM) that is designed to produce accurate, risk-calibrated scoring systems with a limited number of variables and small integer weights. We validated the accuracy and risk calibration of our model using cross-validation and compared its performance with models built with state-of-the-art logistic regression methods. The database was developed by the Critical Care EEG Research Consortium and used data collected over 3 years. The EEG variables were interpreted using standardized terminology by certified reviewers. Exposures: All patients had more than 6 hours of uninterrupted EEG recordings. Main Outcomes and Measures: The main outcome was the average risk calibration error. Results: There were 5427 continuous EEGs performed on 4772 participants (2868 men, 49.9%; median age, 61 years) performed at 3 institutions, without further demographic stratification. Our final model, 2HELPS2B, had an area under the curve of 0.819 and average calibration error of 2.7% (95% CI, 2.0%-3.6%). It included 6 variables with the following point assignments: (1) brief (ictal) rhythmic discharges (B[I]RDs) (2 points); (2) presence of lateralized periodic discharges, lateralized rhythmic delta activity, or bilateral independent periodic discharges (1 point); (3) prior seizure (1 point); (4) sporadic epileptiform discharges (1 point); (5) frequency greater than 2.0 Hz for any periodic or rhythmic pattern (1 point); and (6) presence of "plus" features (superimposed, rhythmic, sharp, or fast activity) (1 point). The probable seizure risk of each score was 5% for a score of 0, 12% for a score of 1, 27% for a score of 2, 50% for a score of 3, 73% for a score of 4, 88% for a score of 5, and greater than 95% for a score of 6 or 7. Conclusions and Relevance: The 2HELPS2B model is a quick accurate tool to aid clinical judgment of the risk of seizures in critically ill patients.

Disentangling Stigma from Functional Neurological Disorders: Conference Report and Roadmap for the Future.

A multidisciplinary expert review of key issues and future directions from the conference "Controversial labels and clinical uncertainties: psychogenic disorders, conversion disorder, and functional symptoms." On October 9 and 10, 2015, a conference entitled "Controversial labels and clinical uncertainties: psychogenic disorders, conversion disorder, and functional symptoms" was held at the Center for Ethics, Emory University, Atlanta, GA, USA. This conference brought together a select group of 30 distinguished thought leaders and practitioners, including ethicists, researchers, clinicians, humanities scholars, and advocates to discuss the unique challenges and controversies related to the diagnosis, treatment, and stigma for patients with what is currently recognized as functional ("psychogenic") neurological disorders. Our group of experts explored the conflicts and ethical tensions within health care that must be addressed in order to advance care for these disorders. What follows is a reflection on the conversations between conference attendees outlining key challenges and value conflicts in the diagnosis and treatment of patients with functional disorders. With this report, we aim to provide a roadmap for reducing stigma and improving care for functional neurological disorders (FND). A path forward would involve (1) setting a multifactorial research agenda that equally prioritized access to effective psychotherapy as well as identification of novel biomarkers; (2) empowering patients with FND to be heard and to drive changes in care; and (3) reducing isolation for clinicians by providing formal training and setting up multidisciplinary care teams and support networks.

Survey of the diagnostic and therapeutic approach to new-onset refractory status epilepticus.

PURPOSE: We conducted a survey of providers to assess for practice patterns in diagnosing and treating new-onset refractory status epilepticus (NORSE). NORSE is the occurrence of prolonged seizures that are not responsive to initial therapies in otherwise healthy individuals without obvious cause on initial presentation. This entity is thought to have multiple etiologies, including autoimmune. METHOD: A 29-question electronic survey was sent to providers included in the Neurocritical Care Society emailing list. Questions regarded responders' demographics, existing institutional practice protocols, diagnostic work-up, therapeutic management and expected outcomes in NORSE. Responses were collected from October 23, 2014, to November 25, 2014. RESULTS: There were 107 respondents out of 1334 (8%). CT head, continuous EEG, lumbar puncture and microbe serologies were suggested within 24h of presentation as part of a diagnostic work-up. MRI brain, autoimmune work-up (systemic and anti-neuronal antibodies) and cytology/flow cytometry were favored later in the course. About 25% of providers would never perform an autoimmune work-up in this setting. Initial treatment included up to 3 anticonvulsants (including one anesthetic), followed by additional anticonvulsants/anesthetics along with antimicrobials, followed by steroids, plasma exchange, hypothermia and ketogenic diet. Many respondents would never use IV immunoglobulin or steroid-sparing immunosuppressants (29% and 42%, respectively) for NORSE. CONCLUSIONS: This survey could serve as the foundation for development of a standardized approach for the diagnosis and treatment of NORSE.

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

OBJECTIVE: Continuous EEG (cEEG) monitoring of critically ill patients has gained widespread use, but there is substantial reported variability in its use. We analyzed cEEG and antiseizure drug (ASD) usage at three high volume centers. METHODS: We utilized a multicenter cEEG database used daily as a clinical reporting tool in three tertiary care sites (Emory Hospital, Brigham and Women's Hospital and Yale - New Haven Hospital). We compared the cEEG usage patterns, seizure frequency, detection of rhythmic/periodic patterns (RPP), and ASD use between the sites. RESULTS: 5792 cEEG sessions were analyzed. Indication for cEEG monitoring and recording duration were similar between the sites. Seizures detection rate was nearly identical between the three sites, ranging between 12.3% and 13.6%. Median time to first seizure and detection rate of RPPs were similar. There were significant differences in doses of levetiracetam, valproic acid, and lacosamide used between the three sites. CONCLUSIONS: There was remarkable uniformity in seizure detection rates within three high volume centers. In contrast, dose of ASD used frequently differed between the three sites. SIGNIFICANCE: These large volume data are in line with recent guidelines regarding cEEG use. Difference in ASD use suggests discrepancies in how cEEG results influence patient management.

Association of Periodic and Rhythmic Electroencephalographic Patterns With Seizures in Critically Ill Patients.

IMPORTANCE: Periodic and rhythmic electroencephalographic patterns have been associated with risk of seizures in critically ill patients. However, specific features that confer higher seizure risk remain unclear. OBJECTIVE: To analyze the association of distinct characteristics of periodic and rhythmic patterns with seizures. DESIGN, SETTING, AND PARTICIPANTS: We reviewed electroencephalographic recordings from 4772 critically ill adults in 3 academic medical centers from February 2013 to September 2015 and performed a multivariate analysis to determine features associated with seizures. INTERVENTIONS: Continuous electroencephalography. MAIN OUTCOMES AND MEASURES: Association of periodic and rhythmic patterns and specific characteristics, such as pattern frequency (hertz), Plus modifier, prevalence, and stimulation-induced patterns, and the risk for seizures. RESULTS: Of the 4772 patients included in our study, 2868 were men and 1904 were women. Lateralized periodic discharges (LPDs) had the highest association with seizures regardless of frequency and the association was greater when the Plus modifier was present (58%; odds ratio [OR], 2.00, P < .001). Generalized periodic discharges (GPDs) and lateralized rhythmic delta activity (LRDA) were associated with seizures in a frequency-dependent manner (1.5-2 Hz: GPDs, 24%,OR, 2.31, P = .02; LRDA, 24%, OR, 1.79, P = .05; ≥ 2 Hz: GPDs, 32%, OR, 3.30, P < .001; LRDA, 40%, OR, 3.98, P < .001) as was the association with Plus (GPDs, 28%, OR, 3.57, P < .001; LRDA, 40%, P < .001). There was no difference in seizure incidence in patients with generalized rhythmic delta activity compared with no periodic or rhythmic pattern (13%, OR, 1.18, P = .26). Higher prevalence of LPDs and GPDs also conferred increased seizure risk (37% frequent vs 45% abundant/continuous, OR, 1.64, P = .03 for difference; 8% rare/occasional vs 15% frequent, OR, 2.71, P = .03, vs 23% abundant/continuous, OR, 1.95, P = .04). Patterns associated with stimulation did not show an additional risk for seizures from the underlying pattern risk (P > .10). CONCLUSIONS AND RELEVANCE: In this study, LPDs, LRDA, and GPDs were associated with seizures while generalized rhythmic delta activity was not. Lateralized periodic discharges were associated with seizures at all frequencies with and without Plus modifier, but LRDA and GPDs were associated with seizures when the frequency was 1.5 Hz or faster or when associated with a Plus modifier. Increased pattern prevalence was associated with increased risk for seizures in LPDs and GPDs. Stimulus-induced patterns were not associated with such risk. These findings highlight the importance of detailed electroencephalographic interpretation using standardized nomenclature for seizure risk stratification and clinical decision making.

Characteristics of EEG Interpreters Associated With Higher Interrater Agreement.

PURPOSE: The goal of the project is to determine characteristics of academic neurophysiologist EEG interpreters (EEGers), which predict good interrater agreement (IRA) and to determine the number of EEGers needed to develop an ideal standardized testing and training data set for epileptiform transient (ET) detection algorithms. METHODS: A three-phase scoring method was used. In phase 1, 19 EEGers marked the location of ETs in two hundred 30-second segments of EEG from 200 different patients. In phase 2, EEG events marked by at least 2 EEGers were annotated by 18 EEGers on a 5-point scale to indicate whether they were ETs. In phase 3, a third opinion was obtained from EEGers on any inconsistencies between phase 1 and phase 2 scoring. RESULTS: The IRA for the 18 EEGers was only fair. A select group of the EEGers had good IRA and the other EEGers had low IRA. Board certification by the American Board of Clinical Neurophysiology was associated with better IRA performance but other board certifications, years of fellowship training, and years of practice were not. As the number of EEGers used for scoring is increased, the amount of change in the consensus opinion decreases steadily and is quite low as the group size approaches 10. CONCLUSIONS: The IRA among EEGers varies considerably. The EEGers must be tested before use as scorers for ET annotation research projects. The American Board of Clinical Neurophysiology certification is associated with improved performance. The optimal size for a group of experts scoring ETs in EEG is probably in the 6 to 10 range.

Randomized double-blind comparison of cognitive and EEG effects of lacosamide and carbamazepine.

Differential effectiveness of antiepileptic drugs (AEDs) is more commonly determined by tolerability than efficacy. Cognitive effects of AEDs can adversely affect tolerability and quality of life. This study evaluated cognitive and EEG effects of lacosamide (LCM) compared with carbamazepine immediate-release (CBZ-IR). A randomized, double-blind, double-dummy, two-period crossover, fixed-dose study in healthy subjects compared neuropsychological and EEG effects of LCM (150mg, b.i.d.) and CBZ-IR (200mg, t.i.d.). Testing was conducted at screening, predrug baseline, the end of each treatment period (3-week titration; 3-week maintenance), and the end of each washout period (4weeks after treatment). A composite Z-score was derived for the primary outcome variable (computerized cognitive tests and traditional neuropsychological measures) and separately for the EEG measures. Other variables included individual computer, neuropsychological, and EEG scores and adverse events (AEs). Subjects included 60 healthy adults (57% female; mean age: 34.4years [SD: 10.5]); 44 completed both treatments; 41 were per protocol subjects. Carbamazepine immediate-release had worse scores compared with LCM for the primary composite neuropsychological outcome (mean difference=0.33 [SD: 1.36], p=0.011) and for the composite EEG score (mean difference=0.92 [SD: 1.77], p=0.003). Secondary analyses across the individual variables revealed that CBZ-IR was statistically worse than LCM on 36% (4/11) of the neuropsychological tests (computerized and noncomputerized) and 0% of the four EEG measures; none favored CBZ-IR. Drug-related AEs occurred more with CBZ-IR (49%) than LCM (22%). Lacosamide had fewer untoward neuropsychological and EEG effects and fewer AEs and AE-related discontinuations than CBZ-IR in healthy subjects. Lacosamide exhibits a favorable cognitive profile.

Sensitivity of quantitative EEG for seizure identification in the intensive care unit.

OBJECTIVE: To evaluate the sensitivity of quantitative EEG (QEEG) for electrographic seizure identification in the intensive care unit (ICU). METHODS: Six-hour EEG epochs chosen from 15 patients underwent transformation into QEEG displays. Each epoch was reviewed in 3 formats: raw EEG, QEEG + raw, and QEEG-only. Epochs were also analyzed by a proprietary seizure detection algorithm. Nine neurophysiologists reviewed raw EEGs to identify seizures to serve as the gold standard. Nine other neurophysiologists with experience in QEEG evaluated the epochs in QEEG formats, with and without concomitant raw EEG. Sensitivity and false-positive rates (FPRs) for seizure identification were calculated and median review time assessed. RESULTS: Mean sensitivity for seizure identification ranged from 51% to 67% for QEEG-only and 63%-68% for QEEG + raw. FPRs averaged 1/h for QEEG-only and 0.5/h for QEEG + raw. Mean sensitivity of seizure probability software was 26.2%-26.7%, with FPR of 0.07/h. Epochs with the highest sensitivities contained frequent, intermittent seizures. Lower sensitivities were seen with slow-frequency, low-amplitude seizures and epochs with rhythmic or periodic patterns. Median review times were shorter for QEEG (6 minutes) and QEEG + raw analysis (14.5 minutes) vs raw EEG (19 minutes; p = 0.00003). CONCLUSIONS: A panel of QEEG trends can be used by experts to shorten EEG review time for seizure identification with reasonable sensitivity and low FPRs. The prevalence of false detections confirms that raw EEG review must be used in conjunction with QEEG. Studies are needed to identify optimal QEEG trend configurations and the utility of QEEG as a screening tool for non-EEG personnel. CLASSIFICATION OF EVIDENCE REVIEW: This study provides Class II evidence that QEEG + raw interpreted by experts identifies seizures in patients in the ICU with a sensitivity of 63%-68% and FPR of 0.5 seizures per hour.