Seizures Research Articles

Hughlings Jackson's Second Thoughts on Mental States in Epilepsy.

John Hughlings Jackson (1835-1911) was the pre-eminent British neurologist of the last 3 decades of the 19th century whose most seminal contributions related to the understanding of epileptic seizures. Jackson instructed that his personal papers should be destroyed at his death, and consequently, few examples of his handwriting now survive. We discovered a series of marginalia in Jackson's handwriting annotating one of his papers, "On temporary mental disorders after epileptic paroxysms," first published in 1875 in the West Riding Lunatic Asylum Medical Reports. Two of the most extensive annotations indicate Jackson's later understanding of "epileptic vertigo" and of "mental automatisms." We contextualize the changes in Jackson's thinking suggested by these emendations. These marginalia give insights into Jackson's continuing effort to understand epilepsy and its implications for brain function, an issue that was then, as now, one of the fundamental problems in neurology.

Diagnostic and Therapeutic Challenges of Focal Cortical Dysplasia in Mali: A Case Report

Focal Cortical Dysplasias (FCDs) are a common cause of pharmaco-resistant epilepsy. FCDs are rare conditions, and their pathogenesis remains poorly understood. We report a 12-year-old patient seen in our clinic for focal onset epileptic seizures. Neurological examination and brain CT-scan were nearly normal. However, an electroencephalogram (EEG) revealed a slightly slow background rhythm with slow spikes in the medial and right parietal regions and a brain magnetic resonance imaging (MRI) showed a focal cortical thickening in the right parietal lobe with FLAIR hypersignal, indicating a focal cortical dysplasia. Ongoing seizures marked the disease course under antiepileptic polytherapy after 15 months of treatment. Keywords: Focal cortical dysplasia, pharmaco-resistant epilepsy, Mali, Africa.

Health Literacy and Attitudes Towards Childhood Epilepsy

ABSTRACT Purpose The purpose of this study was to investigate the public attitudes toward childhood epilepsy and the effects of health literacy and some sociodemographic variables on these attitudes. Design It is a descriptive and cross-sectional study. Methods The study was carried out with 311 individuals. Data were collected through face-to-face interviews with individuals using the Sociodemographic Characteristics Information Form, The Childhood Epilepsy Attitude Scale (CEAS), and the Health Literacy Scale (HLS). The data were evaluated using percentage and number, student t-test, One Way Anova, and hierarchical linear regression analysis. Findings The mean CEAS score of the participants was 43.61 ± 7.86 and the mean HLS score was 100.19 ± 17.90. According to the CEAS subscale/total score averages, no statistically significant difference was found between the variables of gender, family type, having children, family history of epilepsy, and history of epilepsy in one’s close circle (p > .05). Conclusions It was concluded that participants’ attitudes toward childhood epilepsy were positive, and that this attitude was affected by variables such as educational status, witnessing individuals having epileptic seizures, and health literacy. Clinical Evidence It is recommended that health professionals organize training programs to increase public understanding of childhood epilepsy and improve individual attitudes toward the condition. Community health nurses can play an important role in raising awareness about childhood epilepsy. Community healthcare centers may be advised to include the issue of childhood epilepsy in their awareness programs.

GLIOMA-RELATED EPILEPSY

Diffuse low-grade gliomas (LGGs), originating from glial tissue, have a propensity to progress to higher-grade tumors over time, presenting a complex challenge in clinical management. Glioma-associated epilepsy is a significant clinical indicator influencing both treatment strategies and prognostication. This study aims to assess the impact of glioma-related epilepsy on treatment outcomes and explore the current management guidelines. Material and Methods A retrospective analysis was conducted on 38 patients diagnosed with LGGs (WHO grades 2 and 3) treated in our neurosurgical department from 2013 to 2023. The focus was on glioma-related epileptic seizures, with outcomes evaluated using the Engel classification six months post-surgery. Additionally, anti-seizure medication (ASM) regimens were reviewed, and current National Institute for Health and Care Excellence (NICE) guidelines on low-grade gliomas were synthesized. Results Of the 38 patients, 30 had diffuse astrocytoma and 8 had oligodendroglioma. Among those with glioma-related epilepsy (n=25), management strategies included biopsy only (8%), gross total resection (GTR) (40%), subtotal resection (StR) (32%), and partial resection (PaR) (20%). No significant correlation was found between seizures and tumor volume, growth rate, or histological findings. However, a positive correlation between the extent of surgical resection and improved Engel outcomes was observed. Discussion Existing research suggests that early seizures may be a favorable prognostic indicator for malignant progression-free and overall survival. Epilepsy significantly impacts the quality of life for glioma patients. Exploring targeted epilepsy surgery for glioma-related seizures could potentially enhance patient outcomes and quality of life posttreatment. Conclusion Advancing approaches in epilepsy surgery for glioma-related seizures holds promise for improving patient quality of life and treatment efficacy. Further investigation into these strategies is warranted.

Epileptic encephalopathy, autism and cognitive deficit caused by the SYNGAP1 gene mutation

The paper analyzes data from scientific publications and presents a clinical case study of a rare genetic epileptic encephalopathy caused by a mutation in the SYNGAP1 gene. The case study focuses on a 4-year-old girl who has been diagnosed with epileptic encephalopathy due to the mutation. The paper describes the anamnesis of the child’s illness, including family history, neurological, neuropsychological, and speech assessments, as well as the results of genetic testing, electroencephalography, and magnetic resonance imaging (MRI). The findings indicate that the main symptoms of the condition are typically epilepsy, autism spectrum disorder, difficulty with phrasal speech, and mental retardation. Common types of seizures include atypical absence seizures, myoclonic seizures, atonic seizures, and eyelid myoclonia with absences. On the electroencephalogram, there is a slowdown in occipital activity and diffuse, prolonged «peak-polypic-slow-wave» complexes. Pathognomonic neuroimaging changes in the brain are typically absent. Valproic acid, levetiracetam, and ethosuximide have been shown to be the most effective treatments for controlling epileptic seizures. Due to the rarity of this syndrome, the authors have provided a detailed clinical case report from their practice.Conclusion. SYNGAP1-related epileptic encephalopathy has a specific clinical presentation, including characteristic EEG findings and a particular pattern of seizures. The diagnostic approach for children with this condition, autism spectrum disorder, and delayed language development should include video electroencephalography with sleep deprivation, as well as genetic testing if necessary, using next-generation sequencing, to ensure early detection and appropriate treatment planning.

ECG-based epileptic seizure prediction: Challenges of current data-driven models.

Up to a third of patients with epilepsy fail to achieve satisfactory seizure control. A reliable method of predicting seizures would alleviate psychological and physical impact. Dysregulation in heart rate variability (HRV) has been found to precede epileptic seizures and may serve as an extracerebral predictive biomarker. This study aims to identify the preictal HRV dynamics and unveil the factors impeding the clinical application of ECG-based seizure prediction. Thirty-nine adult patients (eight women; median age: 38, [IQR = 31, 56.5]) with 252 seizures were included. Each patient had more than three recorded epileptic seizures, each at least 2 hours apart. For each seizure, one hour of ECG prior to seizure onset was analyzed and 97 HRV features were extracted from overlapping three-minute windows with 10s stride. Two separate patient-specific experiments were performed using a support vector machine (SVM). Firstly, the separability of training data was examined in a non-causal trial. Secondly, the prediction was attempted in pseudo-prospective conditions. Finally, visualized HRV data, clinical metadata, and results were correlated. The mean receiver operating characteristic (ROC) area under the curve (AUC) for the non-causal experiment was 0.823 (±0.12), with 208 (82.5%) seizures achieving an improvement over chance (IoC) classification score (p < 0.05, Hanley & McNeil test). In pseudo-prospective classification, the ROC-AUC was 0.569 (±0.17), and 86 (49.4%) seizures were classified with IoC. Off-sample optimized SVMs failed to improve performance. Major limiting factors identified include non-stationarity, variable preictal duration and dynamics. The latter is expressed as both inter-seizure onset zone (SOZ) and intra-SOZ variability. The pseudo-prospective preictal classification achieving IoC in approximately half of tested seizures suggests the presence of genuine preictal HRV dynamics, but the overall performance does not warrant clinical application at present. The limiting factors identified are often overlooked in non-causal study designs. While current deterministic prediction methods prove inadequate, probabilistic approaches may offer a promising alternative. Many patients with epilepsy suffer from uncontrollable seizures and would greatly benefit from a reliable seizure prediction method. Currently, no such system is available to meet this need. Previous studies suggest that changes in the electrocardiogram (ECG) precede seizures by several minutes. In our work, we evaluated whether variations in heart rate could be used to predict epileptic seizures. Our findings indicate that we are still far from achieving results suitable for clinical application and highlight several limiting factors of present seizure prediction approaches.

Seizures and Epilepsy in Association With Neurocysticercosis: A Nosologic Proposal.

Neurocysticercosis is one of the main risk factors of seizures and epilepsy in many regions of the world, which are Taenia solium-endemic but resource-constrained to control the parasite. The nosology of seizures and the classification of epilepsy in the context of neurocysticercosis are somewhat uncertain. Many seizures associated with the infection are customarily referred to as "acute symptomatic seizures." The term, however, seems unsuitable. Neither is the condition acute nor does it allow the avoidance of long-term antiseizure medications, as is the case with acute symptomatic seizures, for instance, associated with traumatic brain injury. We propose that seizures be classified according to the evolutionary stage of parenchymal cysticercosis in addition to the conventional classification of seizures and epilepsy and identification of the epileptogenic zone. An often-ignored aspect is the identification of comorbidities, many of which are specific to neurocysticercosis.

Local field potential-based brain-machine interface to inhibit epileptic seizures by spinal cord electrical stimulation.

This study proposes a closed-loop brain-machine interface (BMI) based on spinal cord stimulation to inhibit epileptic seizures, applying a semi-supervised machine learning approach that learns from Local Field Potential (LFP) patterns acquired on the pre-ictal (preceding the seizure) condition.&#xD; &#xD;Approach. LFP epochs from the hippocampus and motor cortex are band-pass filtered from 1 to 13 Hz, to obtain the time-frequency representation using the continuous Wavelet transform, and successively calculate the phase lock values (PLV). As a novelty, the Z-score-based PLV normalization using both modified k-means and Davies-Bouldin's measure for clustering is proposed here. Consequently, a generic seizure's detector is calibrated for detecting seizures on the normalized PLV, and enables the spinal cord stimulation for periods of 30 s in a closed-loop, while the BMI system detects seizure events. To calibrate the proposed BMI, a dataset with LFP signals recorded on five Wistar rats during basal state and epileptic crisis was used. The epileptic crisis was induced by injecting pentylenetetrazol (PTZ). Afterwards, two experiments without/with our BMI were carried out, inducing epileptic crisis by PTZ in Wistar rats. &#xD;&#xD;Main Results. Stronger seizure events of high LFP amplitudes and long time periods were observed in the rat, when the BMI system was not used. In contrast, short-time seizure events of relative low intensity were observed in the rat, using the proposed BMI. The proposed system detected on unseen data the synchronized seizure activity in the hippocampus and motor cortex, provided stimulation appropriately, and consequently decreased seizure symptoms. &#xD;&#xD;Significance. Low-frequency LFP signals from the hippocampus and motor cortex, and cord spinal stimulation can be used to develop accurate closed-loop BMIs for early epileptic seizures inhibition, as an alternative treatment.

Enhancing Epilepsy Seizure Detection Through Advanced EEG Preprocessing Techniques and Peak-to-Peak Amplitude Fluctuation Analysis

Objectives: Naturally, there are several challenges, such as muscular artifacts, ocular movements and electrical interferences that depend on precise diagnosis and classification, which hamper exact epileptic seizure detection. This study has been conducted to improve seizure detection accuracy in epilepsy patients using an advanced preprocessing technique that could remove such noxious artifacts. Methods: In the frame of this paper, the core tool in the area of epilepsy, EEG, will be applied to record and analyze the electrical patterns of the brain. The dataset includes recordings of seven epilepsy patients taken by the Unit of Neurology and Neurophysiology, University of Siena. The preprocessing techniques employed include advanced artifact removal and signal enhancement methods. We introduced Peak-to-Peak Amplitude Fluctuation (PPAF) to assess amplitude variability within Event-Related Potential (ERP) waveforms. This approach was applied to data from patients experiencing 3–5 seizures, categorized into three distinct groups. Results: The results indicated that the frontal and parietal regions, particularly the electrode areas Cz, Pz and Fp2, are the main contributors to epileptic seizures. Additionally, the implementation of the PPAF metric enhanced the effectiveness of seizure detection and classification algorithms, achieving accuracy rates of 99%, 98% and 95% for datasets with three, four and five seizures, respectively. Conclusions: The present research extends the epilepsy diagnosis with clues on brain activity during seizures and further demonstrates the effectiveness of advanced preprocessing techniques. The introduction of PPAF as a metric could have promising potential in improving both the accuracy and reliability of epilepsy seizure detection algorithms. These observations provide important implications for control and treatment both in focal and in generalized epilepsy.

Peri-ictal yawning: A potential lateralizing sign in temporal lobe epilepsy.

The primary objective of this retrospective analysis was to evaluate the incidence and lateralization value of peri-ictal yawning (PY) in people with temporal lobe epilepsy (TLE). PY has only occasionally been reported as a manifestation of focal epilepsy. We aimed to determine whether PY could serve as an indicator to help lateralize seizure onset during epileptic seizures. Among 236 consecutive TLE patients admitted for video-EEG monitoring, we analyzed the clinical characteristics, along with scalp video-EEG, magnetic resonance imaging (MRI), fluorodeoxyglucose-positron emission tomography (FDG-PET), Wada test, and stereo EEG (SEEG) in patients with PY. Among the 236 patients, 26 (11.0%) exhibited PY, and 36 of 1018 recorded seizures (3.5%) were associated with PY. Of the 26 patients with PY, 19 (73.1%) had non-dominant TLE, while 7 (26.9%) had dominant TLE. The majority of these patients presented with staring, arrest, and automatisms during their seizures with accompanying vegetative signs. PY occurred either during the ictal or postictal phase in all patients. Exception for 10 seizures (10/36, 27.8%) at the early stage (less than 25% total duration), PY was primarily linked to the late ictal and postictal phases. Surgical intervention was performed in 12 patients, 9 of whom (75%) achieved seizure freedom (Engel class I), with 7 of these 9 (77.8%) having non-dominant TLE. Yawning is a physiological phenomenon typically not associated with epilepsy. The present series suggests that PY is relatively uncommon in TLE, but may represent a rare vegetative sign, particularly in cases with non-dominant TLE. Further investigation with a larger cohort of surgically confirmed cases and using intracranial EEG is essential to deepen our understanding of this phenomenon. Yawning is a typical physiological response that is generally not linked to epilepsy. However, it can occasionally indicate seizure activity, particularly in TLE. PY happens more often observed in non-dominant TLE and usually occurs in the later stages of a seizure or just after it. It may hold potential as a lateralizing marker in TLE.

Revealing single-neuron and network-activity interaction by combining high-density microelectrode array and optogenetics.

The synchronous activity of neuronal networks is considered crucial for brain function. However, the interaction between single-neuron activity and network-wide activity remains poorly understood. This study explored this interaction within cultured networks of rat cortical neurons. Employing a combination of high-density microelectrode array recording and optogenetic stimulation, we established an experimental setup enabling simultaneous recording and stimulation at a precise single-neuron level that can be scaled to the level of the whole network. Leveraging our system, we identified a network burst-dependent response change in single neurons, providing a possible mechanism for the network-burst-dependent loss of information within the network and consequent cognitive impairment during epileptic seizures. Additionally, we directly recorded a leader neuron initiating a spontaneous network burst and characterized its firing properties, indicating that the bursting activity of hub neurons in the brain can initiate network-wide activity. Our study offers valuable insights into brain networks characterized by a combination of bottom-up self-organization and top-down regulation.

Adeno-Associated Viral Vectors in the Treatment of Epilepsy

Epilepsy is a brain disorder characterized by a persistent predisposition to epileptic seizures. With various etiologies of epilepsy, a significant proportion of patients develop pharmacoresistance to antiepileptic drugs, which necessitates the search for new therapeutic methods, in particular, using gene therapy. This review discusses the use of adeno-associated viral (AAV) vectors in gene therapy for epilepsy, emphasizing their advantages, such as high efficiency of neuronal tissue transduction and low immunogenicity/cytotoxicity. AAV vectors provide the possibility of personalized therapy due to the diversity of serotypes and genomic constructs, which allows for increasing the specificity and effectiveness of treatment. Promising orientations include the modulation of the expression of neuropeptides, ion channels, transcription, and neurotrophic factors, as well as the use of antisense oligonucleotides to regulate seizure activity, which can reduce the severity of epileptic disorders. This review summarizes the current advances in the use of AAV vectors for the treatment of epilepsy of various etiologies, demonstrating the significant potential of AAV vectors for the development of personalized and more effective approaches to reducing seizure activity and improving patient prognosis.

SURG-40. PEDIATRIC LOWER GRADE GLIOMA SURGERY IN THE ERA OF GENOMIC MEDICINE

Abstract INTRODUCTION In the 2021 WHO Brain Tumor Classification, pediatric-type gliomas are distinctly categorized from their adult counterparts. The continual evolution of cancer genomics has significantly broadened the spectrum of available treatment options. Here we would like to consider surgery for pediatric low-grade gliomas. METHODS We retrospectively analyzed 41 cases of low-grade gliomas or glioneuronal tumors in pediatric patients who underwent surgery at our institute from 2002 to 2023. We discussed surgical strategies based on molecular classification. RESULTS Among the cases, there were 34 gliomas and 7 glioneuronal tumors. According to the new WHO classification, they corresponded to 1) Adult-type diffuse gliomas, 2) Pediatric-type diffuse low-grade gliomas, 3) Circumscribed astrocytic tumors, or 4) Glioneuronal and neuronal tumors. Cases without molecular diagnosis were also considered in light of the new WHO classification. Among molecularly diagnosed astrocytomas involving the cerebral hemisphere, brain stem, spinal cord, there were no cases of 1), and 2) 3) were the main cases. It is important in surgical selection to note that these cases generally have a more favorable prognosis compared to the adult type and have usefulness in diagnosing MAPK pathway abnormalities leading to the selection of molecularly targeted drugs. 3) includes pilocytic astrocytoma, subependymal giant cell astrocytoma, and pleomorphic xanthoastrocytoma. Among these, in the treatment of pilocytic astrocytoma of the visual tract and hypothalamus, biopsy is essential for molecular diagnosis and therapeutic agent selection. 4) is mainly an epilepsy-related tumor. While their removal contributes to genetic diagnosis and epileptic seizure control, total removal may not always be deemed necessary. CONCLUSION Based on the new WHO classification, a reevaluation of treatment strategies for pediatric brain tumors is necessary.

Focused ultrasound for treatment of epilepsy: a systematic review and meta-analysis of preclinical and clinical studies.

Various preclinical and clinical studies have demonstrated the neuromodulatory and ablative effects of focused ultrasound (FUS). However, the safety and efficacy of FUS in clinical settings for treating epilepsy have not been well established. This study aims to provide a systematic review of all preclinical and clinical studies that have used FUS for the treatment of epilepsy. A systematic search was conducted using Scopus, Web of Science, PubMed, and Embase databases. All preclinical and clinical studies reporting outcomes of FUS in the treatment of epilepsy were included in the systematic review.Random-effect meta-analysis was performedtodetermine safety in clinical studies and seizure activity reduction in preclinical studies. A total of 24 articles were included in the study. Meta-analysis demonstrated that adverse events occurred in 13% (95% CI = 2-57%) of patients with epilepsy who underwent FUS. The frequency of adverse events was higher with the use of FUS for lesioning (36%, 95% CI = 4-88%) in comparison to neuromodulation (5%, 95% CI = 0-71%), although this difference was not significant (P = 0.31). Three-level meta-analysis in preclinical studies demonstrated a reduced spike rate in neuromodulating FUS compared to the control group (P = 0.02). According to this systematic review and meta-analysis, FUS can be considered a safe and feasible approach for treating epileptic seizures, especially in drug-resistant patients. While the efficacy of FUS has been demonstrated in several preclinical studies, further research is necessary to confirm its effectiveness in clinical practice and to determine the adverse events.

Characteristics and clinical course of myoclonus in Cavalier King Charles Spaniels.

Myoclonus has been described in aging Cavalier King Charles Spaniels (CKCS), but the natural course of the disease and response to treatment have not been described. Report the clinical features and course of myoclonus in CKCS. Twenty-seven caregivers provided questionnaire responses at a median of 24 months after the onset of myoclonus in their CKCS. Fifteen caregivers completed a second follow-up questionnaire at a median of 17 months after submission of the first questionnaire. The caregivers of affected CKCS were invited to provide video footage for review. Owners of CKCS with videos demonstrating myoclonus then completed the online questionnaire for further evaluation. A second shortened questionnaire was sent to participants at least 6 months after completion of the first. Most CKCS displayed spontaneous myoclonus affecting predominantly the head (25/27). Overall, the majority had episodes that increased in frequency (20/27) and severity (17/27). Eighteen dogs had developed changes in behavior since the onset of myoclonus. These dogs were typically older and had experienced myoclonic episodes for longer than dogs without behavioral changes. Generalized epileptic seizures were reported in 4/27 dogs. Ten dogs received medical treatment. Eight were prescribed levetiracetam; all had an initial decrease in episode frequency, but a subsequent increase in both frequency and severity of episodes was common. Myoclonus in CKCS tends to progress in frequency and severity regardless of treatment. Progressive behavioral changes suggestive of cognitive decline are common. These findings support the possibility of an underlying neurodegenerative process.

Topological Reinforcement Adaptive Algorithm (TOREADA) Application to the Alerting of Convulsive Seizures and Validation with Monte Carlo Numerical Simulations

The detection of adverse events—for example, convulsive epileptic seizures—can be critical for patients suffering from a variety of pathological syndromes. Algorithms using remote sensing modalities, such as a video camera input, can be effective for real-time alerting, but the broad variability of environments and numerous nonstationary factors may limit their precision. In this work, we address the issue of adaptive reinforcement that can provide flexible applications in alerting devices. The general concept of our approach is the topological reinforced adaptive algorithm (TOREADA). Three essential steps—embedding, assessment, and envelope—act iteratively during the operation of the system, thus providing continuous, on-the-fly, reinforced learning. We apply this concept in the case of detecting convulsive epileptic seizures, where three parameters define the decision manifold. Monte Carlo-type simulations validate the effectiveness and robustness of the approach. We show that the adaptive procedure finds the correct detection parameters, providing optimal accuracy from a large variety of initial states. With respect to the separation quality between simulated seizure and normal epochs, the detection reinforcement algorithm is robust within the broad margins of signal-generation scenarios. We conclude that our technique is applicable to a large variety of event detection systems.

Tailored sacroplasty for sacral fracture secondary to an epileptic seizure

Tailored sacroplasty for sacral fracture secondary to an epileptic seizure

LPM682000012, a Synthetic Neuroactive Steroid That Ameliorates Epileptic Seizures by Downregulating the Serpina3n/NF-κB Signaling Pathway

Epilepsy is characterized by abnormal neuronal firing in the brain. Several therapeutic strategies exist for epilepsy; however, several patients remain poorly treated. Therefore, the development of effective treatments remains a high priority in the field. Neuroactive steroids can potentiate extra-synaptic and synaptic GABAA receptors, thereby providing therapeutic benefits relative to benzodiazepines. This research study investigated the therapeutic effectiveness and underlying mechanisms of LPM682000012, a new synthetic neuroactive steroid-positive allosteric modulator (PAM) of GABAA receptors employed for treating epilepsy. Acute and chronic rat epilepsy models were established to identify the anti-seizure potency of LPM682000012. The dose-dependent sedative effects of LPM682000012 and Ganaxolone in normal rats were evaluated, which revealed that they both dose-dependently alleviated acute epileptic seizure in the pentylenetetrazol (PTZ)-mediated seizure model. Furthermore, LPM682000012 indicated an enhanced safety profile than Ganaxolone. Moreover, LPM682000012 also indicated therapeutic effects in the kainic acid (KA)-induced chronic spontaneous seizure model. Morphologically, LPM682000012 decreased neuronal loss in the hippocampal CA1 and CA3 regions and increased dendritic spine density in the CA1 region. In addition, mechanical analyses, including transcriptomics, Western blot, and proteomics analyses, revealed that the Serpina3n/NF-κB signaling pathway was up-regulated in epileptic rat hippocampal tissue, and LPM682000012 treatment reversed these changes. In summary, this report demonstrated that the novel neurosteroid GABAA PAM LPM682000012 activated the synaptic and extra-synaptic GABAA receptors and alleviated KA-induced neuronal loss and synaptic remodeling, potentially by down-regulating the Serpina3n/NF-κB signaling pathways. The results provide evidence that LPM682000012 is a potential anti-seizure pharmacotherapy candidate for epilepsy and warrants further research.

Burden and impact of substance abuse among epileptic patients attending epilepsy outpatient clinic

BackgroundTo date, the burden and impact of substance use among epileptic patients were studied in a small number of studies and showed inconsistent findings, which may be attributed to the variation in age, test batteries, epilepsy subtypes, and substance use characteristics across research. The aim of the study was to determine the burden and impact of substance abuse among a sample of epileptic patients attending Alexandria University outpatient clinics. This study was conducted on 200 epileptic patients (100 male and 100 female patients). The diagnosis of epilepsy in those patients was confirmed by expert neurologists. Using the international league against epilepsy 2017 classification, they underwent a complete physical examination. EEG was done for all patients. Every patient was assessed using a semi-structured interview and a self-designed questionnaire to collect data concerning history of epilepsy, seizure type, EEG findings, as well as questions derived from the Addiction Severity Index (ASI). The Timeline between epilepsy and substance abuse, as well as the Effect of substance intake on epileptic seizures, were assessed.ResultsA total of 27 epileptic patients had a history of substance abuse; hence, the percentage of substance use among epileptic patients was 13.5%. Mean age in the male age group was (29.74 ± 11.52) years and (27.34 ± 9.35) years in females; mean seizure frequency per month was higher among males than females and this was statistically significant (P = 0.037*). More male (24%) than females (3%) had history of substance use and this was statistically significant (P < 0.001*). Regarding the Effect of substance intake on epileptic seizures, the male group (91.7%) had Seizure worsening, while in the female group, all three patients (100%) had seizures worsening with substance use. The mean Frequency of seizures was 4.48 ± 5.08 attacks per month for substance users and 2.49 ± 3.84 attacks per month for non-users; this was statistically significant. (t = 2.392) (P = 0.018*). Non-substance use patients had better compliance to treatment (79%) in comparison to 44.4%) of Substance use patients and this was statistically significant (P < 0.001*).ConclusionDrug abuse can have a negative impact on epilepsy in both sexes regarding seizure severity frequency, and even compliance with medication.

Indian Hedgehog (IHh) Protein and COX-2 as Biomarkers to Define the Mechanism of Epilepsy and Gastrointestinal Problems as Comorbid Medical Illnesses in Autism Spectrum Disorder: Combining ROC Curves to Improve Diagnostic Values

Background/Objectives: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is increasing throughout the world. Nevertheless, no specific diagnostic or even risk assessment marker is available. Combining more than one marker can improve the diagnostic value of each marker alone and maximize the AUC for ROC curve. Hedgehog (Hh) signaling modulates both intestinal inflammation and immunity. Cyclooxygenase-2 (COX-2) is required for inflammation, and it has been related to epileptic seizures. COX-2 generates prostaglandins-EP2 (PGE2) in the brain, which plays a major role in neuropathology and epilepsy. This study aims to understand the pathophysiology of ASD by investigating the diagnostic value of COX-2 and IHh using independent and combined ROC curves. Methods: COX-2 and IHh were measured in 40 children with ASD and 41 age and sex-matched controls using ELISA. Statistical analyses were performed using ROC curves, odds ratios, and multiple logistic regression models. Results: Higher levels of COX-2 and IHh were observed in the plasma of patients with autism than in controls. The ROC curve of HIh and COX-2 independently showed poor and fair AUCs of 0.662 and 0.776, respectively, while the combined ROC for both variables in relation to the control group increased the AUC = 0.831 significantly (p &lt; 0.001). Conclusions: Thus, combining these variables could be a useful diagnostic marker for ASD.