Long-term video-EEG Research Articles

The Importance of Long-Term Video Electroencephalography Monitoring in the Differential Diagnosis of Epilepsy in Children.

Objective: Epilepsy is a condition in which abnormal, recurring, and excessive neuronal discharges caused by many different disorders in the central nervous system are observed. The rate of detecting epileptiform activity in the first interictal electroencephalography (EEG) of patients with epilepsy is around 40%, even when routine activation methods are applied. Video recordings simultaneously with EEG recordings enable the establishment of correlations between abnormalities.Patients and methods: The long-term video-EEG monitoring (VEM) reports and images of 87 patients hospitalized in the video EEG service in the Pediatric Neurology Clinic of İnönü University between 2016 and 2020 were retrospectively analyzed in this study. Demographic information of the patients, such as age, gender, diagnosis/history, and length of hospital stay, was analyzed.Results: A total of 87 patients were included in the study. Of the patients, 54 (62.1%) were male and 33 (37.9%) were female. The mean age was 107.57 ± 64.40 months. While 10 (11.5%) patients followed up with non-epileptic paroxysmal events (NEPE) were taking antiepileptic drugs (AEDs), AED treatments were discontinued after VEM. The diagnosis of 18 (20.69%) patients changed after VEM. The medications of 27 (31%) patients who took AEDs before VEM were discontinued after VEM. During VEM, sleep movement, psychogenic seizures, infantile masturbation, and tic disorder were observed in 19 (41.3%), 17 (36.9%), three (6.5%), and three (6.5%) patients, respectively.Conclusion: In conclusion, VEM is the gold standard diagnostic method used to distinguish between epilepsy and NEPEs. After VEM, the clinical diagnosis of patients can change, and unnecessary drug administration may be prevented. Psychogenic nonepileptic seizures and NEPEs are common in the pediatric population; however, they are often overlooked.

A Role for Insulin-like Growth Factor 1 in the Generation of Epileptic Spasms in a murine model.

Infantile spasms are associated with a wide variety of clinical conditions, including perinatal brain injuries. We have created a model in which prolonged infusion of tetrodotoxin (TTX) into the neocortex, beginning in infancy, produces a localized lesion and reproduces the behavioral spasms, electroencephalogram (EEG) abnormalities, and drug responsiveness seen clinically. Here, we undertook experiments to explore the possibility that the growth factor IGF-1 plays a role in generating epileptic spasms. We combined long-term video EEG recordings with quantitative immunohistochemical and biochemical analyses to unravel IGF-1's role in spasm generation. Immunohistochemistry was undertaken in surgically resected tissue from infantile spasms patients. We used viral injections in neonatal conditional IGF-1R knock-out mice to show that an IGF-1-derived tripeptide (1-3)IGF-1, acts through the IGF-1 receptor to abolish spasms. Immunohistochemical methods revealed widespread loss of IGF-1 from cortical neurons, but an increase in IGF-1 in the reactive astrocytes in the TTX-induced lesion. Very similar changes were observed in the neocortex from patients with spasms. In animals, we observed reduced signaling through the IGF-1 growth pathways in areas remote from the lesion. To show the reduction in IGF-1 expression plays a role in spasm generation, epileptic rats were treated with (1-3)IGF-1. We provide 3 lines of evidence that (1-3)IGF-1 activates the IGF-1 signaling pathway by acting through the receptor for IGF-1. Treatment with (1-3)IGF-1 abolished spasms and hypsarrhythmia-like activity in the majority of animals. Results implicate IGF-1 in the pathogenesis of infantile spasms and IGF-1 analogues as potential novel therapies for this neurodevelopmental disorder. ANN NEUROL 2022;92:45-60.

Detection of interictal epileptiform discharges in an extended scalp EEG array and high-density EEG-A prospective multicenter study.

High counts of averaged interictal epileptiform discharges (IEDs) are key components of accurate interictal electric source imaging (ESI) in patients with focal epilepsy. Automated detections may be time-efficient, but they need to identify the correct IED types. Thus we compared semiautomated and automated detection of IED types in long-term video-EEG (electroencephalography) monitoring (LTM) using an extended scalp EEG array and short-term high-density EEG (hdEEG) with visual detection of IED types and the seizure-onset zone (SOZ). We prospectively recruited consecutive patients from four epilepsy centers who underwent both LTM with 40-electrode scalp EEG and short-term hdEEG with 256 electrodes. Only patients with a single circumscribed SOZ in LTM were included. In LTM and hdEEG, IED types were identified visually, semiautomatically and automatically. Concordances of semiautomated and automated detections in LTM and hdEEG, as well as visual detections in hdEEG, were compared against visually detected IED types and the SOZ in LTM. Fifty-two of 62 patients with LTM and hdEEG were included. The most frequent IED types per patient, detected semiautomatically and automatically in LTM and visually in hdEEG, were significantly concordant with the most frequently visually identified IED type in LTM and the SOZ. Semiautomated and automated detections of IED types in hdEEG were significantly concordant with visually identified IED types in LTM, only when IED types with more than 50 detected single IEDs were selected. The threshold of 50 detected IED in hdEEG was reached in half of the patients. For all IED types per patient, agreement between visual and semiautomated detections in LTM was high. Semiautomated and automated detections of IED types in LTM show significant agreement with visually detected IED types and the SOZ. In short-term hdEEG, semiautomated detections of IED types are concordant with visually detected IED types and the SOZ in LTM if high IED counts were detected.

Deep Learning Enabled Diagnosis of Children's ADHD Based on the Big Data of Video Screen Long-Range EEG.

Attention-deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children. At the same time, ADHD is prone to coexist with other mental disorders, so the diagnosis of ADHD in children is very important. Electroencephalogram (EEG) is the sum of the electrical activity of local neurons recorded from the extracranial scalp or intracranial. At present, there are two main methods of long-range EEG monitoring commonly used in clinical practice: one is ambulatory EEG monitoring, and the other is long-range video EEG monitoring. The purpose of this study is to summarize the brain electrical activity and clinical characteristics of children with ADHD through the video long-range computer graphics data of children with ADHD and to explore the clinical significance of video long-range EEG in the diagnosis of children with ADHD. For a more effective analysis, this study further processed the video data of long-range computer graphics of children with ADHD and constructed several neural network algorithm models based on deep learning, mainly including fully connected neural network models and two-dimensional convolutional neural networks. Model and long- and short-term memory neural network model. By comparing the recognition effects of these several algorithms, find the appropriate recognition algorithm to improve the accuracy and then establish a recognition method for the diagnosis of children's ADHD based on deep learning long-range EEG big data. Finally, it is concluded that long-term video EEG can analyze the EEG relationship of children with ADHD and provide a diagnostic basis for the diagnosis of ADHD.

A different look on the importance of lateralization and localization of figure 4 symptoms in epilepsy

Background Clinical seizure semiology provides valuable information in the evaluation of focal-onset bilateral tonic–clonic seizures. In the evaluation of these patients, long-term video-EEG monitoring (VEM) and neuroimaging studies are of great significance in determining lateralization together with clinical semiology. In this study, we examined the features of the figure 4 sign that we detected in patients with refractory epilepsy whom we followed up in the VEM unit.MethodsIn the study, 175 patients followed in the VEM unit were examined. Twenty-two patients for whom the figure 4 sign was detected were included in the study. Patients with the side indicated by the figure 4 sign comply with ictal EEG compatible were named as 1st group (G1), and those not were named as 2nd group (G2). Demographic characteristics, seizure type, number of seizures per month, duration of epilepsy, number of seizures during VEM, duration of figure 4 sign, medical history, and cranial MRI characteristics were compared between the two groups.ResultsWhen G1 and G2 were compared, it was observed that temporal lobe seizures were statistically significantly higher in G1. When the figure 4 sign durations were examined, this period was 16.3 ± 8.2 s in frontal lobe seizures and 20.8 ± 7.4 s in temporal lobe seizures. When the duration of the figure 4 sign was examined by gender, it was found that the duration was longer in males, which was statistically significant.ConclusionIn conclusion, it is essential to evaluate ictal EEG findings together with brain imaging while performing semiological localization and lateralization in epileptic patients.

Evaluation of Sleep Disturbances in Patients with Nocturnal Epileptic Seizures in a Romanian Cross-Sectional Study.

(1) Background: Based on the premise that epilepsy is frequently associated with hypnopathies, in this study we aim to analyze the prevalence of sleep disturbances among patients with epilepsy, with exclusively or predominantly nocturnal seizures, in relation to demographic factors as well as clinical and electroencephalography (EEG) aspects. (2) Methods: 69 patients with nocturnal epilepsy were included in our study. Sleep disturbances were measured with the Pittsburgh Sleep Quality Index (PSQI) questionnaire, followed by a long-term video-EEG monitoring during sleep. We analyzed the PSQI results in relation to patients’ gender and age and determined the correlations between the PSQI scores and the modifications on video-EEG recordings, in comparison to a control group of 25 patients with epilepsy but without nocturnal seizures. (3) Results: We found a statistically significant difference between the PSQI of patients with nocturnal seizures compared to those without nocturnal epileptic manifestations. In the experimental group, the mean PSQI score was 7.36 ± 3.91 versus 5.04 ± 2.56 in controls. In women, the average PSQI score was 8.26, whilst in men it only reached 6.41, highlighting a statistically significant difference between genders (p ˂ 0.01). By examining the relationships between the PSQI scores and certain sleep-related factors, evidenced on the nocturnal video-EEG, we found a statistically significant difference between PSQI values of patients who reached the N2 stage, and those who reached the N3 stage of nonrapid eye movement (NREM) sleep, highlighting that those with a more superficial nocturnal sleep also had higher PSQI scores. There were no statistically significant differences regarding the PSQI scores between patients with or without interictal epileptiform discharges, and also in the few patients with nocturnal seizures where we captured ictal activity. (4) Conclusions: we evidenced in this study a poor quality of sleep in patients with nocturnal epilepsy, mostly in women, independent of age. We observed that sleep disturbances were due to superficial and fragmented sleep with frequent microarousals, not necessarily caused by the electrical epileptiform activity.

Psychogenic nonepileptic seizures: Are they a freeze reaction?

Psychogenic nonepileptic seizures (PNES) clinically resemble epileptic seizures (ES) but lack epileptic activity at the time of the seizure and are also not due to any other pathophysiological disorder. The integrative cognitive model (ICM) suggests that PNES is an automatic reaction generated from distorted memory and is perceived as uncontrollable and unwanted. Furthermore, the ICM model implies that a PNES event occurs due to an external or internal cue. Intrigued by this assumption, we wanted to examine why a PNES event occurs at a particular moment by investigating the pre-ictal behavior.This study is a retrospective study. We included all patients diagnosed with PNES or ES admitted to our long-term video-EEG monitoring unit (LTVEM) between 01/01/2018 and 30/08/2020.Using thorough video analysis, we checked the patient's state at the onset of the event and looked back to see what the patient was doing before the event onset.We defined 4 types of pre-ictal behavior A. Inactivity. B. Environment arrangement c. Other.D. No apparent pre-ictal behavior.Thirty patients with PNES and 30 patients with ES were included in the study.In total, 46 PNES events and 56 ES events were recorded and analyzed.In 33 /46 PNES seizures (72%), a type A, A + B or C pre-ictal behavior was observed compared to 1/56 ES (1.78%) with type A pre-ictal behavior. All other pre-ictal behavior in the ES group were of type D.Patients with PNES have a unique pre-ictal behavior before most PNES events with motor manifestations. Since the pre-ictal behavior consists mainly of inactivity, we believe it may imply that PNES represents a freeze reaction or a reconstruction of a freeze reaction.

Incidence of Seizure and Associated Risk Factors in Patients in the Medical Intensive Care Unit (ICU) at Memorial Sloan Kettering Cancer Center (MSK) from 2016-2017.

Background: Seizures and status epilepticus are common neurologic complications in the intensive care unit (ICU) but the incidence in a cancer ICU is unknown. It is important to understand seizure risk factors in cancer patients to properly diagnose the seizure type to ensure appropriate therapy. Methods: We identified patients admitted to the medical ICU at Memorial Sloan Kettering Cancer Center (MSK) from January 2016 to December 2017 who had continuous or routine electroencephalography (EEG) and identified clinical and electrographic seizures by chart review. Results: Of the 1059 patients admitted to the ICU between 2016 and 2017, 50 patients had clinical and/or electrographic seizures (incidence of 4.7%, 95% CI: 3.4-6.0). The incidences of clinical and electrographic seizure were 4.1% and 1.1%, respectively. In a multivariable stepwise regression model, history of seizure (OR: 2.9, 95% CI: 1.1-7.8, P: .03), brain metastasis (OR: 2.5, 95% CI: 1.1-5.8, P: .03), vasopressor requirement (OR: 2.2, 95% CI: 1.0-4.9, P: .05), and age < 65 (2.4, 95% CI: 1.2-5.0, P: .02) were associated with increased risk of seizure (either clinical or electrographic). Obtaining continuous EEG instead of routine EEG increased the yield of seizure detection significantly (OR: 3.9, 95% CI: 1.3-11.1, P: .01). No chemotherapy in the past 30 days, no antibiotic use, vasopressor requirement, and having a brain tumor increased risk of electrographic seizure. Length of continuous EEG > 24 h significantly increased the chances of both clinical and electrographic seizure detection, (OR: 2.6 [95% CI: 1.2-5.7] and 15.0 [95% CI: 2.7-82.5], respectively). Conclusions: We identified known and cancer-related risk factors which can aid clinicians in diagnosing seizures in cancer ICUs. Long-term video EEG monitoring should be considered, particularly given the treatable and reversible nature of seizures.

Associated Factors and Prognostic Implications of Non-convulsive Status Epilepticus in Ischemic Stroke Patients With Impaired Consciousness.

Background and Purpose: Non-convulsive status epilepticus (NCSE) is common in patients with disorders of consciousness and can cause secondary brain injury. Our study aimed to explore the determinants and prognostic significance of NCSE in stroke patients with impaired consciousness.Method: Consecutive ischemic stroke patients with impaired consciousness who were admitted to a neuro intensive care unit were enrolled for this study. Univariate and multivariable logistic regression were used to identify factors associated with NCSE and their correlation with prognosis.Results: Among the 80 patients studied, 20 (25%) died during hospitalization, and 51 (63.75%) had unfavorable outcomes at the 3-month follow-up. A total of 31 patients (38.75%) developed NCSE during 24-h electroencephalogram (EEG) monitoring. Logistic regression revealed that NCSE was significantly associated with an increased risk of death during hospital stay and adverse outcomes at the 3-month follow-up. Patients with stroke involving the cerebral cortex or those who had a severely depressed level of consciousness were more prone to epileptogenesis after stroke.Conclusion: Our results suggest that NCSE is a common complication of ischemic stroke, and is associated with both in-hospital mortality and dependency at the 3-month follow-up. Long-term video EEG monitoring of stroke patients is, therefore required, especially for those with severe consciousness disorders (stupor or coma) or cortical injury.

The Role of Focal Epilepsy Features in Defining SCN1A Mutation-positive Dravet Syndrome as Generalized and Focal Epilepsy.

Background and PurposeThis study was aimed to describe focal epilepsy features of SCN1A mutation-positive Dravet syndrome patients.MethodsA total of 82 SCN1A mutation-positive patients were reviewed retrospectively (39 boys and 43 girls). Seizure type and electroencephalography (EEG) findings were investigated according to the stage, disease onset, and steady state (after age 2 years). Long-term video EEG data were used to classify the seizure type.ResultsFocal seizures at onset and the steady state were found in 54.9% (45/82) and 90% (63/70) of patients, respectively. Afebrile focal seizures were an initial seizure in about one fourth of the patients (22/82, 26.8%). Of 48 seizures captured during long-term video EEG monitoring of 30 patients, 19 seizures were classified as focal onset (39.6%). Of the 19 focal seizures, 12 were either focal motor or focal non-motor seizures, and seven were focal onset bilateral tonic-clonic seizure. Focal epileptiform discharges were more frequent than generalized epileptiform discharges at seizure onset and during the clinical course on conventional EEG (3.7% vs. 0%, 52.9% vs. 32.9%, respectively).ConclusionsOur study provides a comprehensive description of focal epilepsy features of SCN1A mutation-positive Dravet syndrome patients. Recognizing these features as defining the clinical spectrum of Dravet syndrome may lead to earlier genetic diagnosis and tailored management.

Neuronal synchrony abnormalities associated with subclinical epileptiform activity in early-onset Alzheimer's disease.

Since the first demonstrations of network hyperexcitability in scientific models of Alzheimer's disease, a growing body of clinical studies have identified subclinical epileptiform activity and associated cognitive decline in patients with Alzheimer's disease. An obvious problem presented in these studies is lack of sensitive measures to detect and quantify network hyperexcitability in human subjects. In this study we examined whether altered neuronal synchrony can be a surrogate marker to quantify network hyperexcitability in patients with Alzheimer's disease. Using magnetoencephalography (MEG) at rest, we studied 30 Alzheimer's disease patients without subclinical epileptiform activity, 20 Alzheimer's disease patients with subclinical epileptiform activity and 35 age-matched controls. Presence of subclinical epileptiform activity was assessed in patients with Alzheimer's disease by long-term video-EEG and a 1-h resting MEG with simultaneous EEG. Using the resting-state source-space reconstructed MEG signal, in patients and controls we computed the global imaginary coherence in alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillatory frequencies. We found that Alzheimer's disease patients with subclinical epileptiform activity have greater reductions in alpha imaginary coherence and greater enhancements in delta-theta imaginary coherence than Alzheimer's disease patients without subclinical epileptiform activity, and that these changes can distinguish between Alzheimer's disease patients with subclinical epileptiform activity and Alzheimer's disease patients without subclinical epileptiform activity with high accuracy. Finally, a principal component regression analysis showed that the variance of frequency-specific neuronal synchrony predicts longitudinal changes in Mini-Mental State Examination in patients and controls. Our results demonstrate that quantitative neurophysiological measures are sensitive biomarkers of network hyperexcitability and can be used to improve diagnosis and to select appropriate patients for the right therapy in the next-generation clinical trials. The current results provide an integrative framework for investigating network hyperexcitability and network dysfunction together with cognitive and clinical correlates in patients with Alzheimer's disease.

Novel UBE3A pathogenic variant in a large Georgian family produces non-convulsive status epilepticus responsive to ketogenic diet

PurposeTo report the effect of the ketogenic diet (KD) on non-convulsive status epilepticus (NCSE) due to Angelman syndrome (AS) in two members of a large Georgian family affected by a novel frameshift variant in the UBE3A gene (NM_000462.3). MethodsWe evaluated two members of this family who were affected with clinical and EEG features of AS. Clinical history with special emphasis on development, seizure type, frequency, and treatment was reviewed. Routine and long-term video EEG monitoring were conducted, particularly during NCSE. A non-fasting inpatient KD protocol was implemented using blended food orally with full administration of 4:1 (fat to non-fat) ratio. Urine ketone bodies (KBs), measured with urine ketone acetone strips readings, reached 150 mg/dL in both patients. ResultsPatients had characteristic signs of AS and presented with epilepsy between the age of 2–4 years. As methylation tests were negative, next generation sequencing disclosed a c.2365del variant. For both, NCSE was revealed by cognitive deterioration and did not respond to anti-seizure medication. As recommended, IV pyridoxine, benzodiazepines, and valproic acid were administered, but without success. For both patients, NCSE resolved on the second-third day of KD initiation, before the appearance of ketonuria and resulting in improved communication, mood and sleep. ConclusionKD is safe and effective for the treatment of NCSE due to AS. Resolution before the appearance of ketone bodies points to a possible mechanism of action of KD.

Mood Disturbances, Anxiety, and Impact on Quality of Life in Patients Admitted to Epilepsy Monitoring Units.

Introduction: The overall combined prevalence of anxiety and depression in patients with epilepsy has been estimated at 20.2 and 22.9%, respectively, and is considered more severe in drug-refractory epilepsy. Patients admitted to epilepsy monitoring units constitute a particular group. Also, patients with psychogenic non-epileptic seizures can reach more than 20% of all admissions. This study aims to characterize these symptoms in a large cohort of patients admitted for evaluation in a tertiary epilepsy center.Materials and Methods: The study was conducted among 493 consecutive patients (age: 38.78 ± 12.7, 57% females) admitted for long-term video EEG from January 2013 to February 2021. Demographic, clinical, and mood disorder patients' data were collected. Anxiety and depression symptoms were assessed through the Hospital Anxiety Depression Scale (HADS-A and HADS-D), the State Trait Anxiety Inventory (STAI), and Beck Depression Inventory (BDI-II). Quality of life was determined using the QOLIE-10. Patients were divided into three groups: patients with epilepsy (n = 395), psychogenic non-epileptic seizures (PNES) (n = 56), and combined (n = 33). A univariate and multivariate regression analysis was performed for variables associated with quality of life.Results: Of 493 patients, 45.0% had structural etiology, and considering epilepsy classification, 43.6% were of temporal lobe origin. In addition, 32.45% of patients had a previous psychiatric history, 49.9% of patients had depressive symptoms in BDI, and 30.9% according to HADS-D; 56.42 and 52.63% of patients presented pathological anxiety scores in STAI-T and STAI-S, respectively; and 44.78% according to HADS-A. PNES and combined groups revealed a higher incidence of pathologic BDI scores (64.29 and 78.79%, p < 0.001) as well as pathologic HADS-A scores (p = 0.001). Anxiety and depression pathologic results are more prevalent in females, HADS-A (females = 50.7%, males = 36.8%; p = 0.0027) and BDI > 13 (females = 56.6%, males = 41.0%; p = 0.0006). QOLIE-10 showed that 71% of the patients had their quality of life affected with significantly higher scores in the combined group than in the epilepsy and PNES groups (p = 0.0015).Conclusions: Subjective anxiety, depression, and reduced quality of life are highly prevalent in patients with refractory epilepsy. These symptoms are more evident when PNES are associated with epilepsy and more severe among female patients. Most of the cases were not previously diagnosed. These factors should be considered in everyday clinical practice, and specific approaches might be adapted depending on the patient's profile.

Automatic detection of epileptiform potentials and seizures in the EEG

Automatic computer-based algorithms for the detection of epileptiform potentials and seizure patterns on EEG facilitate a time-saving, objective method of quantitative EEG interpretation which is available 7/24. For the automatic detection of interictal epileptiform potentials sensitivities range from 65 to 99% with false positive detections of 0,09 to 13,4 per minute. Recent studies documented equal or even better performance of automatic spike detection programs compared with experienced human EEG readers. The seizure detection problem-one of the major problems in clinical epileptology-consists of the fact that the majority of focal onset seizures with impaired awareness and of seizures arising out of sleep occur unnoticed by patients and their caregivers. Automatic seizure detection systems could facilitate objective seizure documentation and thus help to solve the seizure detection problem. Furthermore, seizure detection systems may help to prevent seizure-related injuries and sudden unexpected death in epilepsy (SUDEP), and could be an integral part of novel, seizure-triggered on-demand therapies in epilepsy. During long-term video-EEG monitoring seizure detection systems could improve patient safety, provide a time-saving objective and reproducible analysis of seizure patterns and facilitate automatic computer-based patient testing during seizures. Sensitivities of seizure detection systems range from 75 to 90% with extratemporal seizures being more difficult to detect than temporal seizures. The false positive alarm rate ranges from 0,1 to 5 per 24 hours. Finally, machine learning algorithms, especially deep learning approaches, open a new highly promising era in automatic spike and seizure detection.

Food intake precipitates seizures in temporal lobe epilepsy

Various factors have been considered as potential seizure precipitants. We here assessed the temporal association of food intake and seizure occurrence, and characteristics of seizures and epilepsy syndromes involved. 596 seizures from 100 consecutive patients undergoing long-term video-EEG monitoring were analyzed. Preictal periods of 60 min were assessed as to the occurrence of food intake, and latencies between food intake and seizure onset were analyzed. Seizures of temporal origin were highly significantly more frequently preceded by food intake compared to those of extratemporal origin; and were associated with shorter food intake-seizure latency. Seizure precipitation by food intake showed male predominance. Shorter food intake-seizure latency was associated with less severe seizures and less frequent contralateral spread of epileptic discharges. We here show for the first time that not only in specific rare reflex epilepsies but in the most frequent form of focal epilepsy, temporal lobe epilepsy, seizures are significantly precipitated by food intake. Seizure occurrence was increased over a period of up to one hour following food intake, and remained more localized in terms of both ictal EEG spread and as reflected by seizure severity. This finding supports the emerging concepts of ictogenesis, implying a continuum between reflex and spontaneous seizures—instead a dichotomy between them.

Association between semiologic, autonomic, and electrographic seizure characteristics in children with generalized tonic-clonic seizures

IntroductionGeneralized tonic-clonic seizures (GTCS) are associated with elevated electrodermal activity (EDA) and postictal generalized electroencephalographic suppression (PGES), markers that may indicate sudden unexpected death in epilepsy (SUDEP) risk. This study investigated the association of GTCS semiology, EDA, and PGES in children with epilepsy. MethodsPatients admitted to the Boston Children’s Hospital long-term video-EEG monitoring unit wore a sensor that records EDA. We selected patients with at least one GTCS and reviewed video-EEGs for semiology, tonic and clonic phase duration, total clinical seizure duration, electrographic onset, offset, and PGES. We grouped patients into three semiology classes: GTCS 1: bilateral symmetric tonic arm extension, GTCS 2: no specific tonic arm extension or flexion, GTCS 3: unilateral or asymmetrical arm extension, tonic arm flexion or posturing that does not fit into GTCS 1 or 2. We analyzed the correlation between semiology, EDA, and PGES, and measured the area under the curve (AUC) of the ictal EDA (seizure onset to one hour after), subtracting baseline EDA (one-hour seizure-free before seizure onset). Using generalized estimating equation (GEE) and linear regression, we analyzed all seizures and single episodes per patient. ResultsWe included 30 patients (median age 13.8 ± 3.6 years, 46.7% females) and 53 seizures. With GEE, GTCS 1 was associated with longer PGES duration compared to GTCS 2 (Estimate (β) = −26.32 s, 95% Confidence Interval (CI): −36.46 to −16.18, p < 0.001), and the presence of PGES was associated with greater EDA change (β = 429604 μS, 95% CI: 3550.96 to 855657.04, p = 0.048). With single-episode analysis, GTCS 1 had greater EDA change than GTCS 2 ((β = −601339 μS, 95% CI: −1167016.56 to −35661.44, p = 0.047). EDA increased with PGES presence (β = 637500 μS, 95% CI: 183571.84 to 1091428.16, p = 0.01) and duration (β = 16794 μS, 95% CI: 5729.8 to 27858.2, p = 0.006). Patients with GTCS 1 had longer PGES duration compared to GTCS 2 (β = −30.53 s, 95% CI: −44.6 to −16.46, p < 0.001) and GTCS 3 (β = −22.07 s, 95% CI: −38.95 to −5.19, p = 0.016). ConclusionIn children with epilepsy, PGES correlates with greater ictal EDA. GTCS 1 correlated with longer PGES duration and may indirectly correlate with greater ictal EDA. Our study suggests potential applications in monitoring and preventing SUDEP in these patients.

Reversible MRI Changes in the Splenium Related to Recent Cessation of Antiepileptic Medications

A 21-year-old male with history of refractory epilepsy presented for long-term video EEG monitoring. His home antiepileptic medications were weaned off over a seven-day period. On hospital day 4, he had a right temporal electro clinical seizure with secondary generalization and a second right temporal electrographic seizure. On hospital day 8, MRI brain identified an ovoid circumscribed lesion in the splenium of the corpus callosum which had not been present on prior scans (Figure 1).

P-MD017. Spinal segmental myoclonus masquerading as a pshycogenic movement disorder

Introduction . Spinal generated movement disorders are uncommon. An elderly gentleman presented with distressing jerks of both lower limbs which caused him much social embarrassment. He had received psychiatric treatment for these abnormal muscular spasms without relief. He had become depressed and withdrawn when he first presented to our outpatient department. In view of his clinical presentation, long term video EEG was done with simultaneous EMG recording from the left tibialis anterior muscle. During his hospital stay, this gentleman experienced several involuntary rhythmic contractions of both legs. The movements were characterized by a sudden brief flexion of the trunk and hips with the thighs and legs bending forwards and ankles dorsiflexing. The patient was fully conscious, alert and awake during the attack. These jerks occurred in the recumbent position, but he could lose his balance if they occurred on standing. These attacks were not stimulus sensitive and could be provoked by stress. Myoclonic jerks of both lower limbs were recorded with no EEG correlate. During jerking, EMG recording showed persistent contractions of the left tibialis muscle occurring at frequency of 4–8 bursts per second, with each burst comprising of 4–5 motor unit discharges. The burst of tibialis anterior muscle activity was involuntary and was absent during voluntary leg movements. Results . A routine clinical examination followed by a long-term video EEG with simultaneous EMG clinched the diagnosis of a spinal segmental myoclonus. He underwent spinal decompression surgery with fixation followed by treatment with levetericetam and clonazepam which relieved his symptoms. Conclusion . Spinal generated movement disorders are uncommon and are often attributed to a psychiatric disorder in the absence of a better explanation. We take this opportunity to elaborate on the case details, investigations and the treatment of spinal myoclonus.

Vasovagal Syncope in Epilepsy Monitoring Unit: A Case Report and Review

ABSTRACT Falls are a common adverse event (AE) in general hospital admissions and in the epilepsy monitoring unit (EMU) and can cause serious physical injury for patients; however, fall prevention policies widely vary between epilepsy centers. Patient safety, including minimizing AEs, such as falls, continue to be a major goal of quality improvement in the EMU. The bathroom area in an EMU is highly prone for falls due to the need for patient privacy. Syncope is a physiologic non-epileptic event with high prevalence in general population and is a potential cause for fall. It is also reported in people diagnosed with epilepsy. We report a case of vasovagal syncope (VVS) associated with injury in a young female during long-term video EEG recording in our EMU facility. We also briefly address concerns for identifying patients at risk for syncope and its prevention. A multidisciplinary team including EEG technologists can play a vital role in educating patients and caretakers about the risk factors of syncopal fall and its preventive measures.

Seizures and Interictal Epileptiform Activity in the Rat Collagenase Model for Intracerebral Hemorrhage.

AimsIntracerebral hemorrhage (ICH) is a known risk factor for the development of acute symptomatic as well as late unprovoked seizures. The underlying pathophysiology of post-ICH seizures is incompletely understood and there are no reliable predictive biomarkers. An animal model to study post-ICH seizures is currently lacking. The aim of this study was to investigate (1) the occurrence of seizures and interictal epileptiform activity in the ICH rat collagenase model using long-term video-EEG monitoring (VEM) and (2) whether seizure occurrence was associated with interictal epileptiform activity and histological features.MethodsMale Sprague-Dawley rats were implanted with epidural electrodes. After 1 week of baseline VEM, collagenase was injected in left striatum to induce an ICH. VEM was continued for 180 days to assess the occurrence of post-ICH seizures and interictal epileptiform activity (spikes and epileptiform discharges). At the end of the experiment, animals were euthanized for histological characterization of the hemorrhagic lesion, using cresyl violet, Prussian blue and immunofluorescence staining.ResultsAcute symptomatic seizures occurred in 4/12 animals between 46 and 80 h after ICH induction. Late unprovoked seizures were present in 2/12 animals and started at 90 and 103 days post-ICH. Animals with late unprovoked seizures did not have acute symptomatic seizures. All electrographic seizures were accompanied by clear behavioral changes. Interictal spikes and epileptiform discharges were observed in all animals but occurred more frequently in rats with late seizures (p = 0.019 and p < 0.001, respectively). Animals with acute symptomatic seizures had more extended hemorrhagic lesions and hemosiderin deposits in the piriform cortex.ConclusionBoth acute symptomatic and late unprovoked seizures were observed in the rat collagenase model. Interictal epileptiform activity was more frequently seen in animals with late seizures. Rats with acute symptomatic seizures showed more extensive lesions and hemosiderin deposits in the piriform cortex. This model could be used to further explore possible biomarkers for epileptogenesis.