Pentylenetetrazole kindling induces dynamic changes in GAD65 expression in hippocampal somatostatin interneurons

INTRODUCTION

One of the mechanisms of epileptgenesis is impairment of inhibitory neural circuits. Several studies have compared neural changes among subtypes of gamma-aminobutyric acid-related (GABAergic) neurons after acquired epileptic seizure. However, it is unclear that GABAergic neural modifications that occur during acquisition process of epileptic seizure.

METHODS

Male rats were injected with pentylenetetrazole (PTZ kindling: n = 30) or saline (control: n = 15) every other day to observe the development of epileptic seizure stages. Two time points were identified: the point at which seizures were most difficult to induce, and the point at which seizures were most easy to induce. The expression of GABAergic neuron-related proteins in the hippocampus was immunohistochemically compared among GABAergic subtypes at each of these time points.

RESULTS

Bimodal changes in seizure stages were observed in response to PTZ kindling. The increase of seizure stage was transiently suppressed after 8 or 10 injections, and then progressed again by the 16th injection. Based on these results, we defined 10 injections as a short-term injection period during which seizures are less likely to occur, and 20 injections as a long-term injection period during which continuous seizures are likely to occur. The immunohistochemical analysis showed that hippocampal glutamic acid decarboxylase 65 (GAD65) expression was increased after short-term kindling but unchanged after long-term kindling. Increased GAD65 expression was limited to somatostatin-positive (SOM+) cells among several GABAergic subtypes. By contrast, GAD, GABA, GABAAR α1, GABABR1, and VGAT cells showed no change following short- or long-term PTZ kindling.

CONCLUSION

PTZ kindling induces bimodal changes in the epileptic seizure stage. Seizure stage is transiently suppressed after short-term PTZ injection with GAD65 upregulation in SOM+ cells. The seizure stage is progressed again after long-term PTZ injection with GAD65 reduction to baseline level.

Emergency medical service response for cases of stroke-suspected seizure: A population-based study

OBJECTIVES

We evaluated the on-scene time of emergency medical services (EMS) for cases where discrimination between acute stroke and epileptic seizures at the initial examination was difficult and identified factors linked to delays in such scenarios.

MATERIALS AND METHODS

A retrospective review of cases with suspected seizure using the EMS database of fire departments across six Japanese cities between 2016 and 2021 was conducted. Patient classification was based on transport codes. We defined cases with stroke-suspected seizure as those in whom epileptic seizure was difficult to differentiate from stroke and evaluated their EMS on-scene time compared to those with epileptic seizures.

RESULTS

Among 30,439 cases with any seizures, 292 cases of stroke-suspected seizure and 8,737 cases of epileptic seizure were included. EMS on-scene time in cases of stroke-suspected seizure was shorter than in those with epileptic seizure after propensity score matching (15.1±7.2 min vs. 17.0±9.0 min; p = 0.007). Factors associated with delays included transport during nighttime (odds ratio [OR], 1.73, 95 % confidence interval [CI] 1.02-2.93, p = 0.041) and transport during the 2020-2021 pandemic (OR, 1.77, 95 % CI 1.08-2.90, p = 0.022).

CONCLUSION

This study highlighted the difference between the characteristics in EMS for stroke and epileptic seizure by evaluating the response to cases with stroke-suspected seizure. Facilitating prompt and smooth transfers of such cases to an appropriate medical facility after admission could optimize the operation of specialized medical resources.

Schizophrenia and epileptic comorbidity

Epileptic seizures have been widely considered as a complication of external or iatrogenic factors in schizophrenia. However, epidemiologic, neurodevelopmental and genetic data have changed regards on this topic considering the complexity of the bidirectional link between epilepsy and schizophrenia. We will examine these data constituting the pathophysiological aspects of this particular association and detail the particular impact of antipsychotics on the occurence of epileptic seizure in schizophrenia as well as the management strategies.

Perceptions and metaphors of patients about epileptic seizures and postictal state in Medellín-Colombia: A qualitative study

INTRODUCTION

PWE describe epileptic seizures and the postictal state with the description of experienced symptoms or through metaphorical language. For treating physicians, this metaphoric language may go unnoticed. The purpose of the study is to identify both the real and metaphorical descriptions of epileptic seizures and postictal state referred by PWE from Medellín Colombia.

METHODS

It is a qualitative study that uses grounded theory applied in ten semi-structured interviews of PWE from the Metropolitan Area of Medellín, Colombia. Descriptions of epileptic seizures and the postictal state were identified. For their classification into metaphorical and literal characteristics, the texts of "The Living Metaphor" by Paul Riccoeur, "The Illness and its Metaphors - AIDS and its Metaphors" by Susan Sontag, and "Metaphors of Everyday Life" by Lakoff and Johnson were used as references.

RESULTS

Ten clinical and fourteen metaphorical descriptions of epileptic seizures were identified. Regarding the postictal state, eight clinical and six metaphorical descriptions were identified. The metaphors were classified into three categories: a. external force b. depreciation and division and c. the absence of continuity (slowness, disconnection).

CONCLUSION

Metaphors are frequent in the description of epileptic seizures and can be useful in seizure classification, neuroanatomical localization, and therapeutic approach. Metaphors can be an initial stage in the construction of otherness as a form of identity.

Validation of different predictive scoring scales in patients with new-onset epileptic seizures or epilepsy related to neuronal surface antibody-mediated autoimmune encephalitis

OBJECTIVE

To validate the different predictive scoring scales in the Chinese population with new-onset epileptic seizures or epilepsy of unknown etiology related to neuronal surface antibody (Ab)-mediated autoimmune encephalitis (AE).

METHODS

We retrospectively reviewed the charts of 174 consecutive patients from October 2018 to December 2022, whose serum and cerebrospinal fluid samples were tested for neuronal surface Abs. The antibody prevalence in epilepsy and encephalopathy (APE2), antibodies contributing to focal epilepsy signs and symptoms (ACES), "obvious" indications for neural antibody testing in epilepsy or seizures (ONES) checklist, and the combinations were used to validate the predictive models of neuronal surface Ab-mediated AE.

RESULTS

A total of 139 patients with new-onset epileptic seizures or epilepsy of unknown etiology were enrolled. Abs were detected in 37 patients (26.6%). The APE2/ONES reflex score had the highest sensitivity (89.2%) and lowest specificity (41.7%). The ACES score had the lowest sensitivity (67.5%) and highest specificity (64.7%). Variations in the performance were observed in the different types of AE. 100% of patients with anti-γ-aminobutyric acid B-B receptor encephalitis were predicted by ONES, APE2/ONES reflex, and ACES/ONES reflex scores. Only 75% of patients with anti-N-methyl-D-aspartate receptor encephalitis were predicted by the APE2/ONES and ACES/ONES reflex scores.

CONCLUSION

Our study was the first to validate various predictive scoring scales in the Chinese cohort of patients with new-onset epileptic seizures or epilepsy of unknown etiology related to neuronal surface Ab-mediated AE. Based upon clinical suspicion, more than one scoring scale should be performed to predict the chance of AE in those patients.

A novel wearable device for automated real-time detection of epileptic seizures

BACKGROUND

Epilepsy is a neurological disorder that has a variety of origins. It is caused by hyperexcitability and an imbalance between excitation and inhibition, which results in seizures. The World Health Organization (WHO) and its partners have classified epilepsy as a major public health concern. Over 50 million individuals globally are affected by epilepsy which shows that the patient's family, social, educational, and vocational activities are severely limited if seizures are not controlled. Patients who suffer from epileptic seizures have emotional, behavioral, and neurological issues. Alerting systems using a wearable sensor are commonly used to detect epileptic seizures. However, most of the devices have no multimodal systems that increase sensitivity and lower the false discovery rate for screening and intervention of epileptic seizures. Therefore, the objective of this project was, to design and develop an efficient, economical, and automatically detecting epileptic seizure device in real-time.

METHODS

Our design incorporates different sensors to assess the patient's condition such as an accelerometer, pulsoxymeter and vibration sensor which process body movement, heart rate variability, oxygen denaturation, and jerky movement respectively. The algorithm for real-time detection of epileptic seizures is based on the following: acceleration increases to a higher value of 23.4 m/s² or decreases to a lower value of 10 m/s² as energy is absorbed by the body, the heart rate increases by 10 bpm from the normal heart rate, oxygen denaturation is below 90% and vibration should be out of the range of 3 Hz -17 Hz. Then, a pulsoxymeter device was used as a gold standard to compare the heart rate variability and oxygen saturation sensor readings. The accuracy of the accelerometer and vibration sensor was also tested by a fast-moving and vibrating normal person's hand.

RESULTS

The prototype was built and subjected to different tests and iterations. The proposed device was tested for accuracy, cost-effectiveness and ease of use. An acceptable accuracy was achieved for the accelerometer, pulsoxymeter, and vibration sensor measurements, and the prototype was built only with a component cost of less than 40 USD excluding design, manufacturing, and other costs. The design is tested to see if it fits the design criteria; the results of the tests reveal that a large portion of the scientific procedures utilized in this study to identify epileptic seizures is effective.

CONCLUSION

This project is objectively targeted to design a medical device with multimodal systems that enable us to accurately detect epileptic seizures by detecting symptoms commonly associated with an episode of epileptic seizure and notifying a caregiver for immediate assistance. The proposed device has a great impact on reducing epileptic seizer mortality, especially in low-resource settings where both expertise and treatment are scarce.

Use of video alone for differentiation of epileptic seizures from non-epileptic spells: A systematic review and meta-analysis

INTRODUCTION

Review of videos (without electroencephalography) to differentiate epileptic seizures (ES) from non-epileptic spells (NES) may be helpful where epilepsy monitoring is not feasible. Previous studies of video-based diagnosis have suffered from variable accuracy, sensitivity, and specificity.

METHODS

We systematically reviewed relevant literature in PubMed, Embase, and Web of Science from inception to September 2022, identifying articles that reported on the video-based diagnosis of ES and NES. In primary analysis, for each study, the most expert group was chosen when different groups of reviewers classified the videos (e.g., epilepsy specialists and general neurologists). In secondary analysis, we compared the diagnostic accuracy of different expertise levels (e.g., epileptologists, general neurologists, residents, medical students). Meta-analysis was performed to obtain pooled estimates of reliability measures.

RESULTS

From 5245 articles identified, 13 met the inclusion criteria, with cumulative data from 683 patients (696 videos) reviewed by 95 independent reviewers in primary analysis. Video alone had a strong ability to differentiate ES from NES as evidenced by the following metrics- area under the curve- 0.9 (considered "outstanding"), sensitivity- 82.2% (95% Confidence Interval [C.I], 80.2%-84.0%), specificity- 84.7% (C.I., 82.8%-86.5%), and diagnostic odds ratio- 24.7 (C.I., 11.5-52.9). The secondary analysis showed reviewer-dependent accuracy with epileptologists showing the highest accuracy (DOR 81.2, C.I., 90.0%-94.6%).

CONCLUSIONS

Video alone has reliable diagnostic performance for differentiating ES from NES. Meta-analysis limitations include inter-study heterogeneity including variable video quality and reviewer expertise. Combined video-EEG remains the gold standard for the diagnosis of epilepsy and NES.

A modification to the Kuramoto model to simulate epileptic seizures as synchronization

The Kuramoto model was developed to describe the coupling of oscillators, motivated by the natural synchronization phenomena. We are interested in modeling an epileptic seizure considering it as the synchronization of action potentials using and modifying this model. In this article, we propose to modify this model, changing the constant coupling force for a function with logistic growth to simulate the onset and epileptic seizure level in an adult male rat caused by the administration of lithium-pilocarpine. Later, we select some frequencies and their respective amplitude values using an algorithm based on the fast Fourier transform (FFT) from an electroencephalography signal when the rat is in basal conditions. Then, we take these values as the natural frequencies of the oscillators in the modified Kuramoto model, considering every oscillator as a single neuron to simulate the emergence of an epileptic seizure numerically by increasing the synchronization value in the coupling function. Finally, using Dynamic Time Warping algorithm, we compare the simulated signal by the Kuramoto model with an FFT approximation of the epileptic seizure.

Influence of weather regime and local geomagnetic activity on the occurrence of epileptic seizures

Epilepsy is a common neurologic disease and presents a major public health problem. Patients with epilepsy have unexpected occurrence of seizures with many triggered by existing triggering factors such as alcohol, stress etc. Other potential triggers include certain weather or atmospheric parameters and local geomagnetic activity. We have analyzed the impact of atmospheric parameters grouped in 6 grouped weather types or weather regimes and the local geomagnetic activity through the K - index. In the prospective study, we analyzed a total of 431 seizures over a 17-month period. In the results obtained, we found that the most severely common weather regime grouped type of weather was radiation and then precipitation regime. It was also found that grouped weather types of weather regimes had more impact on generalized than focal epileptic seizures. Local geomagnetic activity had no direct effect on the occurrence of epileptic seizures. Those results confirm the thesis how the impact of certain external factors is complex and that the further study is required in that respect.

The validity and reliability of Turkish version of the self-efficacy scale in nursing care of children with epilepsy

PURPOSE

This study was conducted to the Turkish validity and reliability study of the 'Scale of Self-efficacy in Nursing Care of Children with Epilepsy' (SSENCCE).

DESIGN AND METHODS

The construct validity of the scale was evaluated with explanatory factor analysis (EFA) and confirmatory factor analysis. The reliability of the scales used in the research was examined with composite reliability and Cronbach's alpha coefficients.

RESULTS

A total of 144 nurses participated in the study. The variance explained in the 12-item scale was 53.6%, and the eigenvalue was found as 6.442. The commonality values of the scale items ranged from 0.304 to 0.712, and the factor loads ranged from 0.552 to 0.844. Cronbach's α of the SSENCCE was calculated as 0.907.

CONCLUSION

The Turkish version of the ESSENCE is a valid, reliable, and appropriate tool for assessing the self-efficacy of nurses providing care for children with epilepsy.

PRACTICE IMPLICATIONS

Considering that there is no scale that is used to evaluate the self-efficacy of nurses who provide care for children with epilepsy in Turkey, it is thought that this study will guide future research on the subject and the improvement of the clinical experience of nurses.

Epileptic seizures in patients with anti-IgLON5 disease

BACKGROUND

Anti-IgLON5 is a rare neurologic disease that can present with epileptic seizures. However, epileptic seizures have not been characterized and are underreported. We aimed to investigate the clinical characteristics and demographics of epileptic seizures in patients with anti-IgLON5 disease.

METHODS

We reported a case of anti-IgLON5 disease presenting with epileptic seizures and presented a comprehensive literature review on epileptic seizures in patients with the anti-IgLON5 disease. We searched the Medline, Pubmed, and Web of Science databases using the following search algorithm: "IgLON5" or "anti-IgLON5" or "IgLON5 antibody" limited to publications in English.

RESULTS

We identified 183 cases from 66 publications. In addition to our case, nine (4.9%) patients with anti-IgLON5 disease had reported epileptic seizures, either focal or generalized. Of those, epileptic seizures were one of the main reasons for neurology consultation in six (3.2%). Patients with epileptic seizures affected both sexes similarly and usually developed in middle age. In addition to epileptic seizures, a majority of patients had sleep disorders and cognitive impairment. The frequency of epileptic seizures was reduced with the treatment of immunotherapy and antiseizure medication.

CONCLUSION

Anti-IgLON5 disease can present with epileptic seizures, and our study expands the clinical spectrum of the anti-IgLON5 disease.

Cannabidiol in canine epilepsy

The anticonvulsant effect of cannabidiol (CBD), which has been confirmed by findings from animal models and human trials, has attracted the interest of veterinary practitioners and dog owners. Moreover, social media and public pressure has sparked a renewed awareness of cannabinoids, which have been used for epilepsy since ancient times. Unfortunately, at this moment veterinarians and veterinary neurologists have difficulty prescribing cannabinoids because of the paucity of sound scientific studies. Pharmacokinetic studies in dogs have demonstrated a low oral bioavailability of CBD and a high first-pass effect through the liver. Administering CBD in oil-based formulations and/or with food has been shown to enhance the bioavailability in dogs, rats and humans. Tolerability studies in healthy dogs and dogs with epilepsy have demonstrated that CBD was safe and well tolerated with only mild to moderate adverse effects. In this context, it should be noted that the quality of available CBD varies widely, underscoring the importance of pharmaceutical quality and its control. One clinical trial in dogs with drug-resistant idiopathic epilepsy failed to confirm a difference in response rates between the CBD group and the placebo group, while in another cross-over trial a ≥ 50 % reduction in epileptic seizure frequency was found in six of 14 dogs in the treatment phase, a reduction that was not observed during the placebo phase. Based on the current state of knowledge it is not possible to provide clear-cut recommendations for the use of CBD in canine epilepsy. Randomized controlled canine trials with large sample sizes are needed to determine the range of therapeutic plasma concentrations, develop evidence-based dosing regimens, determine the efficacy of cannabidiol in drug-refractory epilepsy, and explore potential associations between treatment effects and different etiologies, epilepsy types, and drug combinations.

Sudden death of a 2-year-old child due to alpha-ketoadipic aciduria

Alpha-ketoadipic acid is one of the metabolic intermediates of lysine and tryptophan, and it is known as the biochemical hallmark of alpha-ketoadipic aciduria (α-KA). α-KA is a rare autosomal recessive disorder. Its pathophysiology is reduced alpha-ketoadipic acid dehydrogenase activity, and that makes it difficult to metabolize lysine and tryptophan. The symptoms of this disease are multiple, e.g., psychomotor retardation, epilepsy, and ataxia, and it can even be asymptomatic. We present a case of sudden death in a 2-year-old boy with alpha-ketoadipic aciduria. Postmortem computed tomography (CT) and autopsy were performed to elucidate the cause of death. No obvious lesions could be identified except for a marked fatty liver. Urinalysis showed elevated excretion of α-ketoadipic acid.

Aortic dissection with epileptic seizure: A case report

BACKGROUND

Aortic dissection (AoD) is a life-threatening disease. Its diversified clinical manifestations, especially the atypical ones, make it difficult to diagnose. The epileptic seizure is a neurological problem caused by various kinds of diseases, but AoD with epileptic seizure as the first symptom is rare.

CASE SUMMARY

A 53-year-old male patient suffered from loss of consciousness for 1 h and tonic-clonic convulsion for 2 min. The patient performed persistent hypomania and chest discomfort for 30 min after admission. He had a history of hypertension without regular antihypertensive drugs, and the results of his bilateral blood pressure varied greatly. Then the electroencephalogram showed the existence of epileptic waves. The thoracic aorta computed tomography angiography showed the appearance of AoD, and it originated at the lower part of the ascending aorta. Finally, the diagnosis was AoD (DeBakey, type I), acute aortic syndrome, hypertension (Grade 3), and secondary epileptic seizure. He was given symptomatic treatment to relieve symptoms and prevent complications. Thereafter, the medical therapy was effective but he refused our surgical advice.

CONCLUSION

The AoD symptoms are varied. When diagnosing the epileptic seizure etiologically, AoD is important to consider by clinical and imaging examinations.

Giant intracranial arteriovenous malformation as a possibility of epileptic seizures in a case of drowning

A male in his late 50s had been complaining of headaches and dizziness for 25 years. He also had episodes of losing consciousness, but had not sought treatment because of financial hardship. He was found in the ocean. Autopsy revealed foamy liquid leaking from his nose and mouth, and pleural effusions. The trachea and bronchi contained the same foamy liquid. The lungs were swollen and edematous, and leaked a large amount of foamy liquid. His cause of death was diagnosed as drowning. In the brain, the veins on the frontal lobe and the temporal pole, each on the right cerebral hemisphere, were dilated. A vascular lesion measuring 5 × 5 × 8 cm was found on the bottom of the right frontal lobe, and was located between the right middle cerebral artery and those veins. This vascular lesion extended to the brain parenchyma, and the basal ganglia of the right cerebrum was displaced outward and upward. The vascular lesions in the brain showed blood vessels of various sizes and shapes, and some of the vessel walls were thickened. The vascular lesion on the right frontal lobe was diagnosed as an arteriovenous malformation (AVM). According to the police investigation, the harbor where his body was found was a place he often came for fishing and walking. The possibility of suicide cannot be ruled out. Moreover, it was considered that his AVM might have rendered him unconscious, causing him to fall into the ocean.

Predictive value of video alone in diagnosis of epileptic vs paroxysmal nonepileptic events in children

OBJECTIVE

Previous studies examined the use of video-based diagnosis and the predictive value of videos for differentiation of epileptic seizures (ES) from paroxysmal nonepileptic events (PNEE) in the adult population. However, there are no such published studies strictly on the pediatric population. Using video-EEG diagnosis as a gold standard, we aimed to determine the diagnostic predictive value of videos of habitual events with or without additional clinical data in differentiating the PNEE from ES in children.

METHODS

Consecutive admissions to our epilepsy monitoring unit between June 2020 and December 2020 were analyzed for events of interest. Four child neurologists blinded to the patient's diagnosis formulated a diagnostic impression based upon the review of the video alone and again after having access to basic clinical information, in addition to the video. Features of the video which helped to make a diagnosis were identified by the reviewers as a part of a survey.

RESULTS

A total of 54 patients were included (ES n = 24, PNEE n = 30). Diagnostic accuracy was calculated for each reviewer and combined across all the ratings. Diagnostic accuracy by video alone was 74.5% (sensitivity 80.8%, specificity 66.7%). Providing reviewers with basic clinical information in addition to the videos significantly improved diagnostic accuracy compared to viewing the videos alone. Inter-rater reliability between four reviewers based on the video alone showed moderate agreement (κ = 0.51) and unchanged when additional clinical data were presented (κ = 0.51). The ES group was significantly more likely to demonstrate changes in facial expression, generalized stiffening, repetitive eye blinks, and eye deviation when compared with the PNEE group, which was more likely to display bilateral myoclonic jerking.

CONCLUSIONS

Video review of habitual events by Child Neurologists may be helpful in reliably distinguishing ES from PNEE in children, even without included clinical information.

First aid knowledge and practice toward students with epileptic seizure among governmental high school teachers in Addis Ababa, Ethiopia: Cross-sectional study

BACKGROUND

Epilepsy is one of the most common serious chronic brain disorders and is poorly understood by the general population, having been associated with numerous misconceptions and beliefs. This, coupled with its dramatic clinical manifestations, has resulted in a strong social stigma, and physical trauma due to the unknown delivery of first aid care.

METHODS

An institution-based cross-sectional study was conducted from February 19 to March 31, 2021. Structured self-administered questionnaires were used to collect data, which were comprised of knowledge and practice questions. Knowledge and practice among participants could be measured using the Chi-square (χ²) test of independence at p-values <0.05.

RESULT

A total of 378 participants with a mean age of 34.2 ± 7.8 SD have participated, with a response rate of 92%. Of the total respondents, about 144 (41.1%) and 143 (40.9%) had good knowledge and practice, respectively. Generally, teachers who were trained in first aid had fewer scores (25.6%) than those who were not (43.1%). Teachers who had heard about epilepsy (44.2%) had a higher opportunity to have good knowledge than those who had not heard about epilepsy.

CONCLUSION

This study showed that there was a gap in the knowledge and practice of teachers regarding epileptic seizures.

Seizure classification with selected frequency bands and EEG montages: a Natural Language Processing approach

Individualized treatment is crucial for epileptic patients with different types of seizures. The differences among patients impact the drug choice as well as the surgery procedure. With the advance in machine learning, automatic seizure detection can ease the manual time-consuming and labor-intensive procedure for diagnose seizure in the clinical setting. In this paper, we present an electroencephalography (EEG) frequency bands (sub-bands) and montages selection (sub-zones) method for classifier training that exploits Natural Language Processing from individual patients' clinical report. The proposed approach is targeting for individualized treatment. We integrated the prior knowledge from patient's reports into the classifier-building process, mimicking the authentic thinking process of experienced neurologist's when diagnosing seizure using EEG. The keywords from clinical documents are mapped to the EEG data in terms of frequency bands and scalp EEG electrodes. The data of experiments are from the Temple University Hospital EEG seizure corpus, and the dataset is divided based on each group of patients with same seizure type and same recording electrode references. The classifier includes Random Forest, Support Vector Machine and Multi-Layer Perceptron. The classification performance indicates that competitive results can be achieve with a small portion of EEG the data. Using the sub-zones selection for Generalized Seizures (GNSZ) on all three electrodes, data are reduced by nearly 50% while the performance metrics remain at the same level with the whole frequency and zones. Moreover, when selecting by sub-zones and sub-bands together for GNSZ with Linked Ears reference, the data range reduced to 0.3% of whole range, and the performance deviates less than 3% from the results with whole range of data. Results show that using proposed approach may lead to more efficient implementations of the seizure classifier to be executed on power-efficient devices for long lasting real-time seizures detection.

[Epilepsy detection and analysis method for specific patient based on data augmentation and deep learning]

In recent years, epileptic seizure detection based on electroencephalogram (EEG) has attracted the widespread attention of the academic. However, it is difficult to collect data from epileptic seizure, and it is easy to cause over fitting phenomenon under the condition of few training data. In order to solve this problem, this paper took the CHB-MIT epilepsy EEG dataset from Boston Children's Hospital as the research object, and applied wavelet transform for data augmentation by setting different wavelet transform scale factors. In addition, by combining deep learning, ensemble learning, transfer learning and other methods, an epilepsy detection method with high accuracy for specific epilepsy patients was proposed under the condition of insufficient learning samples. In test, the wavelet transform scale factors 2, 4 and 8 were set for experimental comparison and verification. When the wavelet scale factor was 8, the average accuracy, average sensitivity and average specificity was 95.47%, 93.89% and 96.48%, respectively. Through comparative experiments with recent relevant literatures, the advantages of the proposed method were verified. Our results might provide reference for the clinical application of epilepsy detection.

The role of Rho/ROCK in epileptic seizure-related neuronal damage

Epilepsy is one of the most severe neurological disorders characterized by spontaneous recurrent seizures. Although more than two-thirds of patients can be cured with anti-epileptic drugs (AEDs), the rest one-third of epilepsy patients are resistant to AEDs. A series of studies have demonstrated Rho/Rho-associated kinase (ROCK) pathway might be involved in the pathogenesis of epilepsy in the recent twenty years. Several related pathway inhibitors of Rho/ROCK have been used in the treatment of epilepsy. We searched PubMed from Jan 1, 2000 to Dec 31, 2020, using the terms "epilepsy AND Rho AND ROCK" and "seizure AND Rho AND ROCK". We selected articles that characterized Rho/ROCK in animal models of epilepsy and patients. We then chose the most relevant research studies including in-vitro, in-vivo and clinical trials. The expression of Rho/ROCK could be a potential non-invasive biomarker to apply in treatment for patients with epilepsy. RhoA and ROCK show significant upregulation in the acute and chronic stage of epilepsy. ROCK inhibitors can reduce the epilepsy, epileptic seizure-related neuronal death and comorbidities. These findings demonstrate the novel development for diagnosis and treatment for patients with epilepsy. Rho/ROCK signaling pathway inhibitors may show more promising effects in epilepsy and related neurological diseases.

SMART Syndrome (Stroke-like migraine attacks after radiation therapy): When to suspect it?

Background:

Stroke-like migraine attacks after radiation therapy (SMART) syndrome is a benign complication of brain radiation therapy, which presents circa a decade after radiation treatment. Symptoms are stroke-like deficits, epileptic seizures, and migraine. Cranial magnetic resonance imaging is characteristic for alterations in the form of unilateral cortical hyperintensities and gyriform enhancement, most prominent in the parieto-occipital regions. Prompt diagnosis is essential to avoid unnecessary investigations (e.g., brain biopsy and angiography).

Case Description:

We describe a 51-year-old female patient treated initially with cranial irradiation for a left-sided occipital metastatic lung adenocarcinoma. Five years later, she presented with migraine headache, aphasia, and a right sided hemiparesis.

Conclusion:

The triad of migraine, seizure, and hemiparesis within the context of a prior brain radiotherapy should promptly raise the suspicion of SMART syndrome. Prompt diagnosis is essential to avoid unnecessary invasive investigations.

Applying nonlinear measures to the brain rhythms: an effective method for epilepsy diagnosis

Background

Epilepsy is a neurological disorder from which almost 50 million people have been suffering. These statistics indicate the importance of epilepsy diagnosis. Electroencephalogram (EEG) signals analysis is one of the most common methods for epilepsy characterization; hence, various strategies were applied to classify epileptic EEGs.

Methods

In this paper, four different nonlinear features such as Fractal dimensions including Higuchi method (HFD) and Katz method (KFD), Hurst exponent, and L-Z complexity measure were extracted from EEGs and their frequency sub-bands. The features were ranked later by implementing Relieff algorithm. The ranked features were applied sequentially to three different classifiers (MLPNN, Linear SVM, and RBF SVM).

Results

According to the dataset used for this study, there are five classification problems named ABCD/E, AB/CD/E, A/D/E, A/E, and D/E. In all cases, MLPNN was the most accurate classifier. Its performances for mentioned classification problems were 99.91%, 98.19%, 98.5%, 100% and 99.84%, respectively.

Conclusion

The results demonstrate that KFD is the highest-ranking feature; In addition, beta and theta sub-bands are the most important frequency bands because, for all cases, the top features were KFDs extracted from beta and theta sub-bands. Moreover, high levels of accuracy have been obtained just by using these two features which reduce the complexity of the classification.

Recognition of Psychogenic Versus Epileptic Seizures Based on Videos

OBJECTIVE

Ictal semiology interpretation for differentiating psychogenic nonepileptic seizures (PNESs) and epileptic seizures (ESs) is important for the institution of appropriate treatment. Our objective was to assess the ability of different health care professionals (HCPs) or students to distinguish PNES from ES based on video-recorded seizure semiology.

METHODS

This study was designed following the Standards for Reporting of Diagnostic Accuracy Studies (STARD) guidelines. We showed in a random mix 36 videos of PNES or ES (18 each) and asked 558 participants to classify each seizure. The diagnostic accuracy of various groups of HCPs or students for PNES versus ES was assessed, as well as the effect of patient age and sex. Measures of diagnostic accuracy included sensitivity, specificity, and area under the curve (AUC).

RESULTS

The descending order of diagnostic accuracy (AUC) was the following (p ≤ 0.001): (1) neurologists and epileptologists; (2) neurology residents; (3) other specialists and nurses with experience in epilepsy; and (4) undergraduate medical students. Although there was a strong trend toward statistical difference, with AUC 95% confidence intervals (CIs) that were not overlapping, between epileptologists (95% CI 93, 97) compared to neurologists (95% CI 88, 91), and neurologists compared to electroencephalography technicians (95% CI 82, 87), multiple pairwise comparisons with the conservative Tukey-Kramer honest significant difference test revealed no statistical difference (p = 0.25 and 0.1, respectively). Patient age and sex did not have an effect on diagnostic accuracy in neurology specialists.

CONCLUSION

Visual recognition of PNES by HCPs or students varies overall proportionately with the level of expertise in the field of neurology/epilepsy.

Home video prediction of epileptic vs. nonepileptic seizures in US veterans

OBJECTIVE

Using video-EEG (v-EEG) diagnosis as a gold standard, we assessed the predictive diagnostic value of home videos of spells with or without additional limited demographic data in US veterans referred for evaluation of epilepsy. Veterans, in particular, stand to benefit from improved diagnostic tools given higher rates of PNES and limited accessibility to care.

METHODS

This was a prospective, blinded diagnostic accuracy study in adults conducted at the Houston VA Medical Center from 12/2015-06/2019. Patients with a definitive diagnosis of epileptic seizures (ES), psychogenic nonepileptic seizures (PNES), or physiologic nonepileptic events (PhysNEE) from v-EEG monitoring were asked to submit home videos. Four board-certified epileptologists blinded to the original diagnosis formulated a diagnostic impression based upon the home video review alone and video plus limited demographic data.

RESULTS

Fifty patients (30 males; mean age 47.7 years) submitted home videos. Of these, 14 had ES, 33 had PNES, and three had PhysNEE diagnosed by v-EEG. The diagnostic accuracy by video alone was 88.0%, with a sensitivity of 83.9% and specificity of 89.6%. Providing raters with basic patient demographic information in addition to the home videos did not significantly improve diagnostic accuracy when comparing to reviewing the videos alone. Inter-rater agreement between four raters based on video was moderate with both videos alone (kappa = 0.59) and video plus limited demographic data (kappa = 0.60).

SIGNIFICANCE

This study demonstrated that home videos of paroxysmal events could be an important tool in reliably diagnosing ES vs. PNES in veterans referred for evaluation of epilepsy when interpreted by experts. A moderate inter-rater reliability was observed in this study.

Multifuse multilayer multikernel RVFLN+ of process modes decomposition and approximate entropy data from iEEG/sEEG signals for epileptic seizure recognition

In this paper, the extracted features using variational mode decomposition (VMD) and approximate entropy (ApEn) privileged information of the input EEG signals are combined with multilayer multikernel random vector functional link network plus (MMRVFLN+) classifier to recognize the epileptic seizure epochs efficaciously. In our experiment Bonn University single-channel intracranial electroencephalogram (iEEG) and Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) multichannel scalp EEG (sEEG) recordings are considered to evaluate the efficacy of the proposed method. The VMD is applied on chaotic, non-stationary, nonlinear, and complex EEG signal to decompose it into three band-limited intrinsic mode functions (BLIMFs). The Hilbert transform (HT) is applied on BLIMFs to extract informative spectral and temporal features. The ApEn is computed from the raw EEG signals as the privileged information and given to the multi-hidden layer structure to obtain the most discriminative compressed form. The scatter plots show the distinct nature of compressed privileged ApEn information among the seizure pattern classes. The linear as well as nonlinear mapping, local and global kernel function, high-learning speed, less computationally complex MMRVFLN+ classifier is proposed to recognize the seizure events accurately by importing the efficacious features with ApEn as the input. The advanced signal processing algorithm i.e., Hilbert Huang transform (HHT) with ApEn and MMRVFLN+ are combined to compare the performance with the proposed VMDHTApEn-MMRVFLN+ method. The proposed method has remarkable recognition ability, superior classification accuracy, and excellent overall performance as compared to other methods. The digital architecture of the multifuse MMRVFLN+ is developed and implemented on a high-speed reconfigurable FPGA hardware platform to validate the effectiveness of the proposed method. The superior classification accuracy, the negligible false positive rate per hour (FPR/h), simplicity, feasibility, robustness, and practicability of the proposed method validate its ability to recognize the epileptic seizure epochs automatically.

Canine detection of volatile organic compounds unique to human epileptic seizure

OBJECTIVE

Literature accounts of service dogs alerting patients prior to their seizures are a mix of historically poor quality data and confounding diagnoses. In a group of epilepsy patients, Canine Assistants and Florida International University characterized a unique scent combination of volatile organic compounds present during the immediate postictal period, but never at other times. The current study was designed to confirm prospectively if this unique scent, and potential biomarker, can: (1) be detected in an epilepsy monitoring unit (EMU), (2) whether this scent is present with nonepileptic seizures, and (3) whether this scent also precedes the clinical-electrographic seizure.

METHODS

Following consent and approval, sweat samples taken from EMU admissions at Denver Health Medical Center were sent to Canine Assistants in Georgia. Their team of service dogs, who had been imprinted to recognize the unique scent, were then asked to process these sweat samples in a simple yes/no identification paradigm.

RESULTS

Sixty unique subjects were enrolled over a two-year period. In the first part of this study, a total of 298 ictal sweat samples of 680 total observations were collected. The dogs had a 93.7% (OR: 14.89, 95% CI: 9.27, 23.90) probability of correctly distinguishing between ictal and interictal sweat samples. In the nonepileptic seizure population, 18 of the 19 NES events that were accompanied by sweat sample collections were not associated with identification of the unique seizure scent. In the second part of the study, in which subjects had samples collected every hour, dogs identified the unique seizure scent presence before 78.7% of all seizures captured, at a probability of 82.2% (OR: 4.60, 95% CI: 0.98, 21.69) of a positive detection predicting a seizure. The average duration of the warning phase of the scent was 68.2 min. The average duration of the tail phase of the scent faded after 81 min.

SIGNIFICANCE

This study confirms the unique seizure scent identified by Canine Assistants and FIU may be collected and recognized by dogs trained to do so, in a prospective manner. A significant number of seizures appear to be associated with the unique scent presence prior to clinical-electrical onset of the seizure itself, and therefore further study of this biomarker is warranted.

The effect of weather, air pollution and seasonality on the number of patient visits for epileptic seizures: A population-based time-series study

OBJECTIVE

The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures.

METHODS

Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7 days' lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined.

RESULTS

The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH₄, and NO. Six air pollutants, namely CH₄, NO, CO, NO₂, PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R² = 0.422).

CONCLUSION

The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases.

Association of early-onset epileptic encephalopathy with involuntary movements - Case series and literature review

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Epileptic-dyskinetic encephalopathies are rare epileptic disorders characterized by EOEE with involuntary movement.

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The presence of involuntary movements in patients with EOEE caused by gene variants may be a key diagnostic symptom.

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Genetic diagnosis is useful and may provide a reference for treatment selection.

Epileptic-dyskinetic encephalopathies are rare epilepsies characterized by early-onset epileptic encephalopathies (EOEEs) with involuntary movement. Herein, we investigated the impact of gene variants in epileptic-dyskinetic encephalopathies. Four independent patients from four families who exhibited involuntary movements were recruited from Tokyo Metropolitan Neurological Hospital. The inclusion criteria were as follows: onset within 1 year after birth, frequent seizures, severe developmental delay and accompanying involuntary movements.

We detected four genetic mutations, including STXBP1, GNAO1, CYFIP2, and SCN8A variants. The involuntary movements were drug-resistant. However, pallidal electrocoagulation followed by gabapentin were partially effective in treating chorea and ballismus of the extremities in patients with GNAO1 variants, and perampanel partially suppressed seizures and involuntary movements in one patient with a SCN8A variant. Movement disorders are common to many neurodevelopmental disorders, including a variety of EOEEs. Although we could not establish a definitive correlation using genetic variants in patients with EOEE and movement disorders, involuntary movements in patients with EOEEs may be a key diagnostic finding. The usage of genetic variants could prove beneficial in the future as more patients are investigated with epileptic-dyskinetic encephalopathies.

Interactions between carbapenems and valproic acid among the patients in the intensive care units

PURPOSE

To evaluate risk factors for epileptic seizures or status epilepticus (SE) in patients concomitantly receiving valproic acid (VPA) and carbapenems.

MATERIALS AND METHODS

Adult patients in the intensive care units (ICUs) who concomitantly received VPA and carbapenems from 2007 to 2017 were included. The impacts of different carbapenems on serum concentration of VPA were compared.

RESULTS

Among 162 patients included, 104 (64.2%) and 45 (27.8%) developed epileptic seizures and SE, respectively. The risk factors for epileptic seizures were age (per year increase, adjusted odds ratio [aOR], 1.03), initial antiepileptic regimen (monotherapy and polytherapy, aOR, 0.43 and 0.18, respectively), and VPA serum concentration after concomitant carbapenem administration (per 1 μg/mL increase, aOR, 0.96). VPA serum concentration after concomitant carbapenem administration was an independent risk factor for SE (per μg/mL increase, aOR, 0.98). Concomitant imipenem/cilastatin administration did not significantly decrease VPA serum concentration compared to that by meropenem or ertapenem. The length of stay and number of days on ventilation after concomitant carbapenem administration in the ICUs were significantly more in those with epileptic seizures or SE.

CONCLUSIONS

Carbapenems decreased VPA serum concentration and increased the risk of epileptic seizures and SE, which led to increased length of ICU stay.

Effect of acute mitochondrial dysfunction on hyperexcitable network activity in rat hippocampus in vitro

Metabolic stress imposed by epileptic seizures can result in mitochondrial dysfunction, believed to act as positive feedback on epileptogenesis and seizure susceptibility. As the mechanism behind this positive feedback is unclear, the aim of the present study was to investigate the causal link between acute mitochondrial dysfunction and increased seizure susceptibility in hyperexcitable hippocampal networks. Following the induction of spontaneous interictal-like discharges, acute selective pharmacological blockade of either of the mitochondrial respiratory complexes (MRC) I-IV induced seizure-like events (SLE) in 78-100% of experiments. A similar result was obtained by uncoupling the oxidative phosphorylation (OXPHOS) but not by selective blockade of MRCV (ATP synthase) which did not induce SLE. The reactive oxygen species (ROS) scavenger 4-hydroxy-2,2,6,6-tetramethylpiperidine 1-oxyl (tempol, 2 mM) significantly reduced the proconvulsant effect of blocking MRCI but did not reduce the proconvulsant effect of OXPHOS uncoupling. These findings indicate that acute mitochondrial dysfunction can lead to a convulsive state within a short timeframe, and that increased ROS production makes substantial contribution to such induction in addition to other mitochondrial related factors, which appears to be independent of changes in ROS and ATP production.

Dynamic-related protein 1 inhibitor eases epileptic seizures and can regulate equilibrative nucleoside transporter 1 expression

Background

Dynamic-related protein 1 (Drp1) is a key protein involved in the regulation of mitochondrial fission, and it could affect the dynamic balance of mitochondria and appears to be protective against neuronal injury in epileptic seizures. Equilibrative nucleoside transporter 1 (ENT1) is expressed and functional in the mitochondrial membrane that equilibrates adenosine concentration across membranes. Whether Drp1 participates in the pathogenesis of epileptic seizures via regulating function of ENT1 remains unclear.

Methods

In the present study, we used pilocarpine to induce status epilepticus (SE) in rats, and we used mitochondrial division inhibitor 1 (Mdivi-1), a selective inhibitor to Drp1, to suppress mitochondrial fission in pilocarpine-induced SE model. Mdivi-1administered by intraperitoneal injection before SE induction, and the latency to firstepileptic seizure and the number of epileptic seizures was thereafter observed. The distribution of Drp1 was detected by immunofluorescence, and the expression patterns of Drp1 and ENT1 were detected by Western blot. Furthermore, the mitochondrial ultrastructure of neurons in the hippocampal CA1 region was observed by transmission electron microscopy.

Results

We found that Drp1 was expressed mainly in neurons and Drp1 expression was significantly upregulated in the hippocampal and temporal neocortex tissues at 6 h and 24 h after induction of SE. Mitochondrial fission inhibitor 1 attenuated epileptic seizures after induction of SE, reduced mitochondrial damage and ENT1 expression.

Conclusions

These data indicate that Drp1 is upregulated in hippocampus and temporal neocortex after pilocarpine-induced SE and the inhibition of Drp1 may lead to potential therapeutic target for SE by regulating ENT1 after pilocarpine-induced SE.

Adults discharged after an epileptic seizure: a model of 30-day risk for adverse outcomes

OBJECTIVES

To develop a risk model to predict adverse outcomes within 30 days of discharge in adults attended by hospital emergency departments for an epileptic seizure.

METHODS

ACESUR (Acute Epileptic Seizures in the Emergency Department) is a prospective multicenter, multipurpose registry of cases obtained by systematic sampling. We made follow-up telephone calls to registered patients 30 days after discharge. Clinical variables for the index visit were extracted from the register and variables at 30 days were collected by telephone. The main outcome variable was the occurrence of any adverse outcome (seizure recurrence, emergency department revisit, hospitalization, or death) within 30 days of discharge.

RESULTS

Of the patients from the ACESUR registry discharged from 18 hospitals, we included 489 (74%) with complete follow-up information. The median (interquartile range) age was de 48 (34-66) years. One hundred forty-four patients (29.4%) experienced an adverse outcome within 30 days of discharge. Factors included in the ACESUR risk model were generalized nonconvulsive tonic-clonic epileptic seizure as the reason for the index visit (odds ratio [OR], 2.42; 95% CI, 1.49-3.90; P<.001), ongoing use of 3 or more medications (OR, 1.98; 95% CI, 1.28-3.07; P=.002), and an emergency visit for any reason in the 6 months prior to the index event (OR, 2.34; 95% CI, 1.47-3.70; P<.001). Each factor contributed 1 point to the risk score. A score of 3 was associated with a 62.2% risk of an adverse outcome within 30 days, a score of 2 was associated with a 38.5% risk, a score of 1 with a 25.9% risk, and a score of 0 with a 10.9% risk. The area under the curve receiver operating characteristic curve was 0.72 (95% CI, 0.675-0.772; P=.025).

CONCLUSION

The ACESUR risk model may provide a useful score for identifying patients at high risk of an adverse outcome within 30 days of emergency department discharge after an epileptic seizure.

HAP1 Modulates Epileptic Seizures by Regulating GABAAR Function in Patients with Temporal Lobe Epilepsy and in the PTZ-Induced Epileptic Model

The number of γ-aminobutyric acid type A receptors (GABA_ARs) expressed on the surface membrane and at synaptic sites is implicated in the enhanced excitation of neuronal circuits and abnormal network oscillations in epilepsy. Huntingtin-associated protein 1 (HAP1), a key mediator of pathological alterations in protein trafficking, directly interacts with GABA_ARs and facilitates their recycling back to synapses after internalization from the surface; thus, HAP1 regulates the strength of inhibitory synaptic transmission. Here, we show that HAP1 modulates epileptic seizures by regulating GABA_AR function in patients with temporal lobe epilepsy (TLE) and in the pentylenetetrazol (PTZ)-induced epileptic model. We demonstrate that GABA_ARβ^2/3 and HAP1 expression are decreased and that the HAP1-GABA_ARβ^2/3 complex is disrupted in the epileptic rat brain. We found that HAP1 upregulation exerts antiepileptic activity in the PTZ-induced seizure and that these changes are associated with increased surface GABA_ARβ^2/3 expression and the amplitude of miniature inhibitory postsynaptic currents (mIPSCs). This study provides evidence that hippocampal HAP1 is linked to GABA_ARs in evoking seizures and suggests that this mechanism is involved in epileptic seizures in the brain, representing a potential therapeutic target for epilepsy.

Evaluation of electrocardiographic parameters in patients with epileptic seizure

The aim of the study is to evaluate the changes in electrocardiographic parameters, including QTc dispersion (QTcd), Tpeak-Tend (Tp-e)/QTc ratio and P-wave dispersion (Pd), during the period without seizure activation in patients, presented to the emergency department (ED) with epileptic seizures. This prospective case-control study was conducted between January 2017 and January 2018. Patients, over 18 years old and presented to the ED with epileptic seizure, were consecutively included in the study. Interictal period ECGs of patients were obtained at least 2 hours after the end of the postictal period. ST-segment changes, QT interval, corrected QT interval (QTc), QTd, Pd, Tp-e, Tp-e dispersion (Tp-ed), Tp-e/QTc ratio and arrhythmias were evaluated in interictal ECGs. A total of 103 epileptic patients and 31 control cases were included in the study. Heart rate, QTc, QTcd, Pd, Tp-ed and Tp-e/QTc ratio were significantly higher in the epilepsy group than in the control group (p < 0.05 for all values). No statistically significant difference in those parameters was observed between the patients with known epilepsy and the patients who had seizure for the first time. There was also no statistically significant difference between patients who had recurrent seizures during the observation period and who did not. The patients with epileptic seizures had increased Pd, QTd, QTcd, Tp-ed and Tpe/QTc ratio during interictal period compared to healthy subjects. These electrocardiographic changes might be associated with an increased risk of dysrhythmia. However, prospective large cohorts with short- and long-term follow-up are needed for clinical reflections.

Knowledge and current practices of physiotherapists on the physical activity and exercise in the rehabilitation of children with epileptic seizures

BACKGROUND

Physiotherapists play a key role in the rehabilitation of children with epileptic seizures. Regular physical exercise generates psychological and physiological benefits for people with epilepsy.

DESIGN

This study was a cross-sectional design.

PURPOSE

The purpose of this study was to evaluate the knowledge and current practices of physiotherapists on the physical activity and exercise in the rehabilitation of children with epileptic seizures in Nigeria.

METHODS

Physiotherapists with minimum bachelor's degrees were invited to participate in the study using an electronic questionnaire. The subjects (N = 117) answered a questionnaire comprising 33 simple closed-ended questions with three domains: personal information, knowledge, and current practices.

RESULTS

Out of the 117 physiotherapists, 77.7% (n = 91) had postgraduate degrees, 16.2% (n = 19) had bachelor's degree in physiotherapy, and only 5.9% (n = 7) had Doctor of Physical Therapy (DPT). The results also indicated that 79.5% (n = 93) of physiotherapists had sufficient knowledge about epilepsy, and 86.3% (n = 101) of physiotherapists were using current skills/physical activity to rehabilitate children with epileptic seizures.

CONCLUSIONS

It was concluded that physiotherapists had sufficient knowledge about epilepsy and were using current skills/physical activity in the rehabilitation of children with epileptic seizures.

The exploration of the spectrum of motor manifestations of anti-LGI1 encephalitis beyond FBDS

PURPOSE

The purpose of this study was to characterize the spectrum of motor events in patients with acute anti-leucine-rich glioma-inactivated protein 1 (anti-LGI1) encephalitis through video-electroencephalogram (VEEG) recordings.

METHOD

We collected data retrospectively from 16 patients diagnosed with anti-LGI1 encephalitis who had completed VEEG recording during hospitalization.

RESULTS

VEEG monitoring lasted a median of 11.0 h (range 4.5∼20). Fourteen types of seizures were recorded in 9 patients (56.3 %). Eight of the 14 types of seizures demonstrated typical ictal EEG evolution (including 2 subclinical seizures), 3/14 demonstrated EEG electrodecremental events (EDE) at onset but without further evolution, and 3/14 could be only judged by analyzing semiology. FBDS was recorded in 6 patients (37.5 %), and all these attacks were followed by epileptic seizures. Simple hyperkinetic movements (HMs), such as jerk-like or twisting movements, were found in 8 (50 %) patients, and 6 of them had complex HMs, such as manipulating movements or mimics of daily activities, during sleep.

CONCLUSIONS

1. Atypical seizures, for instance, seizures without EEG evolution, are not rare but likely to be overlooked. 2. FBDS is closely linked with epileptic seizures, revealing FBDS to be a part of epileptic attacks. 3. HMs could expand the spectrum of motor manifestations, overlapping with sleep disorders. 4. The high prevalence of these motor events might be due to the disrupted cortical-subcortical network, which is critical in motor control and sleep.

The effect of simulation-based education on childhood epileptic seizure management knowledge, skills, and attitudes of nursing students

BACKGROUND

Lack of knowledge about epileptic seizure management and negative attitudes toward children with epilepsy among nursing students may negatively affect the quality of healthcare services they deliver.

AIM

This study aimed to examine the effect of training given to nursing students using simulation and standard child mannequins on their childhood epileptic seizure management knowledge, skills, and attitudes.

METHODS

Participants (n = 72) were recruited from a Nursing Faculty in Izmir, Turkey. Students were randomly assigned to the intervention and control groups (n = 36 in each). The intervention group received simulation-based training on epilepsy while the control group received standard child mannequin training on epilepsy. One week after the training, the students were asked to demonstrate their epileptic seizure management knowledge and skills on a simulation model or a standard child mannequin. During this process, they were observed and assessed by two independent observers on the basis of a list of epileptic seizure management skills. All participants completed the personal information form, the Epilepsy and Epileptic Seizure Management Knowledge Test, and the Epilepsy Knowledge and Attitude Scale before, and after the training, McNemar's test, repeated measure ANOVA (intravenous), dependent t-test, chi-square test, Fisher's exact test, independent t-test, Pearson's correlation analysis, and Pearson's chi-square test were used to compare the groups. Intraclass correlation coefficient (ICC) was used to evaluate the consistency between observers.

RESULTS

The epilepsy knowledge scale mean scores of both groups significantly increased after their respective trainings (p < 0.001), but the difference between the groups was not statistically significant (p = 0.829). There was no statistically significant difference between the pre- and posttraining epilepsy attitude scale mean scores of the control group (p = 0.630), however, a statistically significant increase was observed in the epilepsy attitude scale mean score of the intervention group (p = 0.008). In addition, both groups' self-confidence in epileptic seizure management significantly increased after the training (p = 0.000).

CONCLUSIONS

Simulation-based training was beneficial for students insofar as it helped them to develop positive attitudes toward epilepsy.

Model-based robust suppression of epileptic seizures without sensory measurements

Uncontrolled seizures may lead to irreversible damages in the brain and various limitations in the patient's life. There exist experimental studies to stabilize the patient seizures. However, the experimental setups have many sensory devices to measure the dynamics of the brain cortex. These equipments prevent to produce small portable stabilizers for patients in everyday life. Recently, a comprehensive cortex model is introduced to apply model-based observers and controllers. However, this cortex model can be uncertain and have time-varying parameters. Therefore, in this paper, a robust Takagi-Sugeno (TS) controller and observer are designed to suppress the epileptic seizures without sensory measurements. The unavailable sensory measurements are provided by the designed nonlinear observer. The exponential convergence of the observer and controller is satisfied by the feedback parameter design using linear matrix inequalities. In addition, TS fuzzy observer-controller design has been compared with the conventional PID method in terms of control performance and design problem. The numerical computations show that the epileptic seizures are more effectively suppressed by the TS fuzzy observer-based controller under uncertain membrane potential dynamics.

Extended-release vinpocetine: a possible adjuvant treatment for focal onset epileptic seizures

Background

Extended-release vinpocetine is effective to control focal onset epileptic seizures with a low rate of adverse events. A clinical study was performed to evaluate the efficacy and tolerability of vinpocetine as an adjuvant treatment in patients with this condition.

Methods

A double-blind clinical study of parallel groups was conducted, in which 87 patients with a diagnosis of focal epilepsy treated with one to three antiepileptic drugs were recruited. Patients were randomized to receive vinpocetine (n = 41) or placebo (n = 46) adjuvant to their treatment. Patients entered the baseline phase (4 weeks), the titration phase (4 weeks) and the evaluation phase (8 weeks), maintaining stable doses of vinpocetine and their respective antiepileptic drug treatment.

Results

Vinpocetine was more effective than placebo in reducing seizures at the end of the evaluation phase (p < 0.0001). Sixty-nine percent of the vinpocetine-treated patients had a 50% reduction in seizures compared to 13% of placebo-treated patients. No significant differences in the presence of adverse effects in patients treated with vinpocetine compared to those treated with placebo were observed. The most frequent adverse events observed with vinpocetine were headache (7.9%) and diplopia (5.2%).

Conclusions

As an adjuvant treatment, vinpocetine (2 mg/kg/day) effectively reduced the frequency of epileptic seizures and proved to be well tolerated. Vinpocetine has a wide safety profile and well-known adverse events, which are transient and with no sequelae.

Epileptic seizures and criminal acts: Is there a relationship?

BACKGROUND

The relation between epilepsy and criminal acts has been debated for over a century. The general perception persists that epileptic seizures can be associated with violent behavior. Some studies have provided evidence for such an association; however, it remains uncertain whether it really exists. This review critically evaluates the scientific literature on the possible relation between epileptic seizures and criminal acts.

METHODS

A PubMed search was undertaken using the search terms "epilepsy and crime", "epilepsy and automatism", "epilepsy and law", and "epilepsy and dyscontrol syndrome" with the aim of identifying studies examining the possible association between epileptic seizure and crime.

RESULTS

The combined keywords "epilepsy and crime" yielded 495 articles, the keywords "epilepsy and automatism" 402 results, the keywords "epilepsy and law" 969 articles, and the keywords "epilepsy and dyscontrol syndrome" resulted in 22 search results. After removing publications such as reviews and opinion pieces, we identified and analyzed a total of 24 research articles with relevant original data. These included single case reports. The reviewed literature suggests that there are very rare occasions when criminal acts are committed during the ictal or postictal period, mostly by patients with focal epilepsy.

CONCLUSION

The literature on the relation between epileptic seizures and criminal acts is not conclusive. Behavioral disturbances often seem more closely related to comorbidities of epilepsy than particular seizures characteristics. These comorbidities are often not well-described. There is an urgent need for more systematic and detailed data gathering and reporting, in order to allow a more detailed investigation of the relation between epileptic seizures and criminal acts.

Seizure detection by convolutional neural network-based analysis of scalp electroencephalography plot images

We hypothesized that expert epileptologists can detect seizures directly by visually analyzing EEG plot images, unlike automated methods that analyze spectro-temporal features or complex, non-stationary features of EEG signals. If so, seizure detection could benefit from convolutional neural networks because their visual recognition ability is comparable to that of humans. We explored image-based seizure detection by applying convolutional neural networks to long-term EEG that included epileptic seizures. After filtering, EEG data were divided into short segments based on a given time window and converted into plot EEG images, each of which was classified by convolutional neural networks as ‘seizure’ or ‘non-seizure’. These resultant labels were then used to design a clinically practical index for seizure detection. The best true positive rate was obtained using a 1-s time window. The median true positive rate of convolutional neural networks labelling by seconds was 74%, which was higher than that of commercially available seizure detection software (20% by BESA and 31% by Persyst). For practical use, the median of detected seizure rate by minutes was 100% by convolutional neural networks, which was higher than the 73.3% by BESA and 81.7% by Persyst. The false alarm of convolutional neural networks' seizure detection was issued at 0.2 per hour, which appears acceptable for clinical practice. Moreover, we demonstrated that seizure detection improved when training was performed using EEG patterns similar to those of testing data, suggesting that adding a variety of seizure patterns to the training dataset will improve our method. Thus, artificial visual recognition by convolutional neural networks allows for seizure detection, which otherwise currently relies on skillful visual inspection by expert epileptologists during clinical diagnosis.

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Artificial visual recognition of scalp EEG plot images successfully detects seizures.

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CNN-based automatic detection performed better than commercial software.

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Customized CNN learning using large datasets improves detection.

Transition of brain networks from an interictal to a preictal state preceding a seizure revealed by scalp EEG network analysis

Epilepsy is a neurological disorder in the brain that is characterized by unprovoked seizures. Epileptic seizures are attributed to abnormal synchronous neuronal activity in the brain. To detect the seizure as early as possible, the identification of specific electroencephalogram (EEG) dynamics is of great importance in investigating the transition of brain activity as the epileptic seizure approaches. In this study, we investigated the transition of brain activity from interictal to preictal states preceding a seizure by combining EEG network and clustering analyses together in different frequency bands. The findings of this study demonstrated the best clustering performance of k-medoids in the beta band; in addition, compared to the interictal state, the preictal state experienced increased synchronization of EEG network connectivity, characterized by relatively higher network properties. These findings can provide helpful insight into the mechanism of epilepsy, which can also be used in the prediction of epileptic seizures and subsequent intervention.

A rare case of bilateral luxatio erecta with bilateral greater tuberosity fracture following a fall due to seizure

Luxatio erecta is the least common form of shoulder dislocations. Bilateral luxatio erecta with concomitant greater tuberosity fracture is further rare with only couple of cases reported so far in the literature. We present an uncommon and a rare case of post epileptic seizure related bilateral luxatio erecta with greater tuberosity fracture in a young Indian male which is unique in its etiology, method of management and rarity of its type among so far reported cases.

A multi-context learning approach for EEG epileptic seizure detection

Background

Epilepsy is a neurological disease characterized by unprovoked seizures in the brain. The recent advances in sensor technologies allow researchers to analyze the collected biological records to improve the treatment of epilepsy. Electroencephalogram (EEG) is the most commonly used biological measurement to effectively capture the abnormalities of different brain areas during the EEG seizures. To avoid manual visual inspection from long-term EEG readings, automatic epileptic EEG seizure detection has become an important research issue in bioinformatics.

Results

We present a multi-context learning approach to automatically detect EEG seizures by incorporating a feature fusion strategy. We generate EEG scalogram sequences from the EEG records by utilizing waveform transform to describe the frequency content over time. We propose a multi-stage unsupervised model that integrates the features extracted from the global handcrafted engineering, channel-wise deep learning, and EEG embeddings, respectively. The learned multi-context features are subsequently merged to train a seizure detector.

Conclusions

To validate the effectiveness of the proposed approach, extensive experiments against several baseline methods are carried out on two benchmark biological datasets. The experimental results demonstrate that the representative context features from multiple perspectives can be learned by the proposed model, and further improve the performance for the task of EEG seizure detection.

Acute epileptic seizures in myelin oligodendrocyte glycoprotein encephalomyelitis and neuromyelitis optica spectrum disorder: A comparative cohort study

BACKGROUND

Little is known about the incidence and characteristics of acute epileptic seizures in myelin oligodendrocyte glycoprotein encephalomyelitis (MOG-EM) and neuromyelitis optica spectrum disorder (NMOSD). In this study, we compared the incidence and characteristics of acute epileptic seizures in MOG-EM and NMOSD patients.

METHODS

MOG-EM (n = 61) and NMOSD (n = 565) cases obtained from the MSNMOBase (2011-2018) were retrospectively reviewed.

RESULTS

Acute epileptic seizures were observed in 13 (21.3%) patients with MOG-EM and two (0.4%) patients with NMOSD (P < 0.001). In both MOG-EM and NMOSD patients, more than half of seizures were single and of focal onset; slow wave and cortical/subcortical lesions were the most common abnormalities. In MOG-EM patients, no difference was found in the proportion of single seizure with and without anti-epileptic drugs (AEDs; 64.3% vs. 45.5%, P = 0.435). Long-term AED use did not significantly reduce the occurrence of acute epileptic seizures, which was 66.7% before and after treatment. In patients with MOG-EM and NMOSD, mycophenolate mofetil significantly reduced acute epileptic seizure occurrence (P = 0.024).

CONCLUSION

Acute epileptic seizures were more common in MOG-EM patients than in NMOSD patients. The long-term use of AEDs might be unnecessary given the use of immunotherapy in cases of MOG-EM.

Diffuse Low-Grade Glioma-Related Epilepsy

The World Health Organization classifies diffuse low-grade gliomas (DLGGs) are highly epileptogenic primary brain tumors; epileptic seizures occur in more than 90% of cases. Epileptic seizures and drug resistance progress during the course of DLGGs. The glioma-related epileptogenic mechanisms are multifactorial; epileptogenic foci lie within the infiltrated peritumoral neocortex. A short seizure duration before surgery and a large extent of resection are the main predictors of postoperative seizure control in DLGGs. A supratotal resection of a DLGG can improve postoperative seizure control. Epileptic seizure at diagnosis positively affects DLGGs malignant transformation and overall survival.

The diagnostic value of serum UCHL-1 and S100-B levels in differentiate epileptic seizures from psychogenic attacks

OBJECTIVE

To assess the value of postictal serum Ubiquitin C-terminal hydrolase (UCHL-1), a neuronal biomarker, and S100-B, a glial biomarker, levels, in differentiate epileptic seizures (ES) form psychogenic attacks.

METHODS

In this analytical cross-sectional study, serum UCHL-1 and S100-B levels were measured within six hours of occurring seizure, in 43 patients with ES, 20 patients with psychogenic non-epileptic seizures (PNES) and 19 healthy individuals by electrochemiluminescence immunoassay.

RESULTS

Both serum UCHL-1 and S100-B levels were significantly higher in patients with ES than PNES (P < 0.05) and controls (P < 0.01). PNES patients had significantly higher serum S100-B levels compared to controls (P < 0.01). There was a significant correlation between the serum UCHL-1 and S100-B levels in patients with ES (r = 0.46, P = 0.002).

CONCLUSIONS

Our study showed that serum UCHL-1 level could be potentially used in differentiate ES from PNES (sensitivity 72%, specificity 59%). Serum S100-B level had lower value compared to UCHL-1 (AUC 0.68 for UCHL-1 v/s 0.59 for S100B). Post-seizure serum UCHL-1 and S100-B levels could be used in future studies to better understand the underlying mechanism of seizures and may offer as an adjunctive diagnostic test in differentiate ES from PNES.

Significance of noncompliance when treating patients with epilepsy

INTRODUCTION

The absence of patient's cooperation when it comes to his/her treatment ("noncompliance") is typical to chronic diseases and it is significant problem in medical practice. The term "compliance" means patient's capability of strictly adhering to the recommendations concerning the prescribed treatment. The noncompliance with drug regime is frequent case in patients with epilepsy, it is related to increased risk of epileptic seizures' occurrence and other undesired consequences, including increased costs in the healthcare area.

OBJECTIVE

The objective of our research is assessing the interconnection between compliance with the treatment and social-demographic and clinical factors in patients with epilepsy.

CONTINGENT AND METHODS

The research covers 131 consecutively included patients with epilepsy of various social-demographic and clinical characteristics. We have utilized analysis of the medical documentation, anamnesis, study of the somatic and neurological status, self-assessment scales and statistical methods.

RESULTS

We established statistically significant positive correlations between the number of patients with poor compliance and the absence of professional/educational occupation, frequency of epileptic seizures, number of the antiepileptic drugs taken during the present and past treatment, the simultaneous presence of poor control of epileptic seizures and adverse drug events being the reason behind the modification of the previous treatment.

CONCLUSION

Patient's poor compliance, the great frequency of seizures, the higher number of antiepileptic drugs and the adverse drug reactions have negative impact on the course of the epileptic disease. The improved compliance results in optimizing the antiepileptic treatment, improving patients' condition and significantly cutting down costs incurred in the healthcare area.