Search

Background: For patients with epilepsy, antiseizure medication remains the primary treatment; however, it is ineffective in approximately 30% of cases. These patients experience progressive neuronal damage and poor outcomes. Therefore, there is an urgent need for disease-modifying therapy (DMT) that targets the pathogenesis of epilepsy. Glycyrrhizin has shown potential as a DMT in epilepsy due to its multiple targets and diverse mechanisms. Previous studies suggest that glycyrrhizin may regulate key processes involved in epilepsy pathogenesis, such as neuroinflammation and cell death, but its effects on pyroptosis have not been reported. Methods: This study employed bioinformatics techniques to identify potential molecular targets for glycyrrhizin in epilepsy treatment and then validated using a kainic acid-induced status epilepticus mouse model. Results: Glycyrrhizin treatment significantly prolonged seizure latency, reduced seizure duration, and alleviated neuronal damage in the status epilepticus mouse model. Molecular experiments indicated that glycyrrhizin may regulate pyroptosis through mediation of the high mobility group box 1 (HMGB1)/Toll-like receptor 4 (TLR4)/nuclear factor kappa-B (NF-κB) signaling pathway. Conclusion: Glycyrrhizin exerts neuroprotective and anticonvulsant effects in epilepsy by regulating pyroptosis via the HMGB1/TLR4/NF-κB signaling pathway, offering novel insights into its potential as a DMT for epilepsy. [ABSTRACT FROM AUTHOR]

Introduction: The prevalence of epilepsy in sub-Saharan Africa varies considerably, and the exact estimate for Ghana remains unclear, particularly in peri-urban areas where data are scarce. More community-based studies are required to understand better the actual burden of epilepsy in these areas and the difficulties in accessing healthcare. Objective: To adapt and validate a household survey epilepsy-screening instrument in Shai-Osudoku and Ningo-Prampram District of Greater Accra Region, Ghana. Methods: We developed a 17-item epilepsy screening instrument by modifying previously validated English language questionnaires. We included questions that could identify convulsive and non-convulsive seizures. Language experts forward- and back-translated the questionnaires into the two languages: Asante Twi and Dangme. Cases were people with confirmed epilepsy attending healthcare facilities where these languages are used. Controls were unaffected relatives of cases or people attending the same healthcare facilities for other medical conditions. We matched cases and controls for geographical location and ethnicity. An affirmative response to one of the seventeen questions by a participant was deemed a positive screen. The questionnaires were divided into two stages. The first stage consisted of broader, more general questions aimed at identifying potential cases of epilepsy. The second stage involved a more detailed and focused set of questions administered to those who screened positive in the first stage. Results: One hundred and forty Dangme speakers (70 cases and 70 controls) and 100 Asante Twi speakers (50 cases and 50 controls) were recruited. The sensitivity and specificity for Dangme were: Stage 1, 100% and 80%, and Stage 2, 98.6% and 85.7%. The Dangme version reliably identified epilepsy with positive predictive values of 83.3% and 87.3% at stages 1 and 2. The questionnaire excluded epilepsy with 100% and 98.4% negative predictive values. For the Asante Twi version, the sensitivity and specificity were 98% and 92% (95% at Stage 1, and for Stage 2, 96% and 94%. The Asante Twi questionnaire reliably specified epilepsy with positive predictive values of 92.5% and 94.1% at stages 1 and 2. It excluded epilepsy with negative predictive values of 97.9% and 95.9% for the two stages Conclusions: Our questionnaire is valid for the two languages and usable for community-based epilepsy surveys in Ghana. It can also be adapted for other resource-poor settings, although translation and iterative in-country testing will be needed to ensure its validity. [ABSTRACT FROM AUTHOR]

ObjectiveMethodsResultsConclusionTo examine neuropsychological characteristic differences between typical and atypical language dominance in adult persons with epilepsy (PWE) and mesial temporal sclerosis (MTS), including exploring the impact of selected clinical variables on detection of atypical language and neuropsychological performance.Adults with intractable epilepsy and MTS (n = 39) underwent comprehensive, pre-surgical evaluation including fMRI and neuropsychological assessment. Participants with concordant lateralization of MTS and seizure onset were included. Participants were grouped by dichotomized typical or atypical language lateralization based on fMRI results. Neuropsychological performance and other relevant clinical variables of the aforementioned groups were then compared.Those with atypical language demonstrated poorer performance across neuropsychological tasks as compared to those with typical language lateralization. Although, typical neuropsychological measures used to evaluate language lateralization were not among those significantly different between the groups. Differences in neuropsychological performance were particularly pronounced on TMT A, TMT B, Stroop (Color), GPB (Dominant), and GPB (Non-Dominant). ROC Curve was provided to evaluate reproducibility at different thresholds.This pilot study revealed those with atypical language lateralization demonstrated greater cognitive dysfunction across neuropsychological tasks than those with typical language lateralization. Neuropsychological measures outside of the domain of language tests detected subtle changes of functional neuroanatomical reorganization while language domain tasks revealed no significant differences between aforementioned groups in pre-surgical evaluation of PWE. While these preliminary results require further replication, these are important implications for diagnostic and prognostic evaluation. [ABSTRACT FROM AUTHOR]

Background: Depressive symptom is the most common type of psychiatric co-morbidity among persons with epilepsy. Epilepsy patients are identified as at higher risk of suffering depressive symptom explicitly in low- and middle-income countries due to poor mental health care systems and financial burdens. The co-occurrence of depressive symptom among epilepsy patients deteriorates the prognosis of the disease and diminishes the quality of life of both the patients and their families. However, there is limited evidence on the prevalence of depressive symptom and associated factors in Ethiopia. Therefore, this study is intended to assess the prevalence of depressive symptom and associated factors among epilepsy patients attending in Amhara region, Ethiopia. Method: A multi-center institution-based cross-sectional study was done among epilepsy patients attending at Amhara region, Ethiopia. The Hospital Anxiety Depression tool was used to assess depressive symptom. To determine the factors associated with depressive symptom, a binary logistic regression model was used. Adjusted Odds Ratio (AOR) with the 95% Confidence Interval (CI) was reported in the multivariable binary logistic regression analysis. Results: About 406 participants were registered in the study with a response rate of 97.6%. The prevalence of depressive symptom among epilepsy patients was 53.9% [95%CI: 49.1%, 58.8%]. In the multivariable binary logistic regression analysis, taking polytherapy treatment [AOR = 1.87, 95% CI: 1.04, 3.36], perceived stigma [AOR = 5.73, 95%CI: 3.11, 10.55], poor antiepileptic medication adherence [AOR = 3.33, 95%CI: 1.30, 8.54] and having poor [AOR = 5.83, 95%CI: 2.44, 13.90] and moderate social support [AOR = 3.08, 95%CI: 1.34, 7.09] were significantly associated with depressive symptom. Conclusions: This study revealed that the magnitude of depressive symptom among epilepsy patients in Ethiopia was relatively high and multiple factors determined the likelihood of depressive symptom. Thus, healthcare providers and concerned stakeholders should strengthen comprehensive health education to reduce the magnitude and consequences of depressive symptom among this segment of the population. Moreover, strong social support with special attention should be given to epilepsy patients. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance Cognitive deficits are one of the most debilitating comorbidities in epilepsy and other neurodegenerative, neuropsychiatric, and neurodevelopmental brain disorders. Current diagnostic and therapeutic options are limited and lack objective measures of the underlying neural activities. In this study, electrophysiological biomarkers that reflect cognitive functions in clinically validated batteries were determined to aid diagnosis and treatment in specific brain regions.We employed the Cambridge Neuropsychological Test Automated Battery (CANTAB) tasks to probe memory and executive functions in 86 patients with epilepsy undergoing clinical electroencephalography (EEG) monitoring. EEG electrode signals during performance of particular battery tasks were decomposed to identify specific frequency bands and cortical areas that differentiated patients with impaired, normal, and good standardized performance according to their age and gender.The anterior prefrontal cortical EEG power in the theta frequency band was consistently lower in patients with impaired memory and executive function performance (z‐score < −1). This effect was evident in all four behavioral measures of executive, visual, spatial, and working memory functions and was confined to the cortical area of all four frontal pole electrodes (Nz, Fpz, Fp1, and Fp2).Theta EEG power in the anterior prefrontal cortex provides simple, accessible, and objective electrophysiological measure of memory and executive functions in epilepsy. Our results suggest a feasible clinical biomarker for diagnosis, monitoring, and treatment of cognitive deficits with emerging targeted neuromodulation approaches. [ABSTRACT FROM AUTHOR]

Intracranial potentials are used as functional biomarkers of neural networks. As potentials spread away from the source populations, they become mixed in the recordings. In humans, interindividual differences in the gyral architecture of the cortex pose an additional challenge, as functional areas vary in location and extent. We used source separation techniques to disentangle mixing potentials obtained by exploratory deep arrays implanted in epileptic patients of either sex to gain access to the number, location, relative contribution, and dynamics of coactive sources. The unique spatial profiles of separated generators made it possible to discern dozens of independent cortical areas for each patient, whose stability maintained even during seizure, enabling the follow up of activity for days and across states. Through matching these profiles to MRI, we associated each with limited portions of sulci and gyri and determined the local or remote origin of the corresponding sources. We also plotted source-specific 3D coverage across arrays. In average, individual recording sites are contributed to by 3–5 local and distant generators from areas up to several centimeters apart. During seizure, 13–85% of generators were involved, and a few appeared anew. Significant bias in location assignment using raw potentials is revealed, including numerous false positives when determining the site of origin of a seizure. This is not amended by bipolar montage, which introduce additional errors of its own. In this way, source disentangling reveals the multisource nature and far intracranial spread of potentials in humans, while efficiently addressing patient-specific anatomofunctional cortical divergence. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET) mapping for cerebral glucose metabolism in drug-sensitive and drug-resistant pediatric epilepsy patients. Methods: This retrospective study enrolled 40 patients and 25 controls. Patients were categorized into drug-sensitive epilepsy (n = 22) and drug-resistant epilepsy (n = 18) according to the seizure frequency at follow-up. All patients underwent two [18F]FDG PET scans separated by a minimum of one year. Absolute asymmetry index (|AI|) was calculated for assessing metabolic differences and changes in epileptic foci. Statistical Parametric Mapping (SPM) was utilized to reveal voxel-wise metabolic characteristics and alterations throughout the brain. Network analysis based on graph theory was used to investigate network-level differences between the two patient groups. Results: The drug-sensitive group showed a lower |AI| at both baseline (P = 0.038) and follow-up (P = 0.003) PET scans than the drug-resistant group. |AI| decreased in the drug-sensitive group and increased in the drug-resistant group across scans, but these trends were not statistically significant (P = 0.240 and P = 0.450, respectively). Both groups exhibited hypometabolism at baseline. The drug-sensitive group showed less hypometabolic brain regions than the drug-resistant group. The drug-sensitive maintained stable level of hypometabolism between the two scans, whereas the drug-resistant group showed an increasing hypometabolism. Network analysis demonstrated that the drug-sensitive group had a higher global efficiency, average degree, and clustering, along with a shorter characteristic path length compared to the drug-resistant group. Conclusions: For the first time, this study revealed in vivo cerebral glucose metabolic pattern of nonsurgical pediatric epilepsy patients treated by antiepileptic drugs. Especially, drug-resistant epilepsy patients represented significantly extensive and progressive hypometabolism with inefficient brain network connectivity compared with drug-sensitive epilepsy. [18F]FDG PET imaging may be a potential visual approach for theranostics of epilepsy patients. [ABSTRACT FROM AUTHOR]

Objective: There is currently scarce data on the electroclinical characteristics of epilepsy associated with synapsin 1 (SYN1) pathogenic variations. We examined clinical and electro‐encephalographic (EEG) features in patients with epilepsy and SYN1 variants, with the aim of identifying a distinctive electroclinical pattern. Methods: In this retrospective multicenter study, we collected and reviewed demographic, genetic, and epilepsy data of 19 male patients with SYN1 variants. Specifically, we analyzed interictal EEG data for all patients, and electro‐clinical data from 10 epileptic seizures in 5 patients, using prolonged video‐EEG monitoring recordings. Inter‐ictal EEG functional connectivity parameters and frequency spectrum of the 10 patients over 12 years of age, were computed and compared with those of 56 age‐ and sex‐matched controls. Results: The main electroclinical features of epilepsy in patients with SYN1 were (1) EEG background and organization mainly normal; (2) interictal abnormalities are often rare or not visible on EEG; (3) more than 60% of patients had reflex seizures (cutaneous contact with water and defecation being the main triggers) isolated or associated with spontaneous seizures; (4) electro‐clinical semiology of seizures was mainly temporal or temporo‐insulo/perisylvian with a notable autonomic component; and (5) ictal EEG showed a characteristic rhythmic theta/delta activity predominating in temporo‐perisylvian regions at the beginning of most seizures. Comparing patients with SYN1 to healthy subjects, we observed a shift to lower frequency bands in power spectrum of interictal EEG and an increased connectivity in both temporal regions. Interpretation: A distinct epilepsy syndrome emerges in patients with SYN1, with a rather characteristic clinical and EEG pattern suggesting predominant temporo‐insular involvement. ANN NEUROL 2025;97:34–50 [ABSTRACT FROM AUTHOR]

Precise localization of the epileptogenic zone is critical for successful epilepsy surgery. However, imbalanced datasets in terms of epileptic vs. normal electrode contacts and a lack of standardized evaluation guidelines hinder the consistent evaluation of automatic machine learning localization models. This study addresses these challenges by analyzing class imbalance in clinical datasets and evaluating common assessment metrics. Data from 139 drug-resistant epilepsy patients across two Institutions were analyzed. Metric behaviors were examined using clinical and simulated data. Complementary use of Area Under the Receiver Operating Characteristic (AUROC) and Area Under the Precision-Recall Curve (AUPRC) provides an optimal evaluation approach. This must be paired with an analysis of class imbalance and its impact due to significant variations found in clinical datasets. The proposed framework offers a comprehensive and reliable method for evaluating machine learning models in epileptogenic zone localization, improving their precision and clinical relevance. Adopting this framework will improve the comparability and multicenter testing of machine learning models in epileptogenic zone localization, enhancing their reliability and ultimately leading to better surgical outcomes for epilepsy patients. [ABSTRACT FROM AUTHOR]

Aim: To expand the phenotypic spectrum of ADGRL1 and explore the correlation between epilepsy and the ADGRL1 genotype. Method: We performed whole‐exome sequencing in a cohort of 115 families (including 195 males and 150 females) with familial febrile seizure or epilepsy with unexplained aetiology. The damaging effects of variants was predicted using protein modelling and multiple in silico tools. All reported patients with ADGRL1 pathogenic variants were analysed. Results: One new ADGRL1 variant (p.Pro753Leu) was identified in one family with genetic epilepsy with febrile seizures. Further analysis of 12 ADGRL1 variants in 16 patients revealed that six patients had epilepsy. Epilepsy types ranged from early‐onset epileptic encephalopathy to genetic epilepsy with febrile seizures plus (GEFS+). All four variants associated with epilepsy were located in the non‐helix or sheet region of ADGRL1. Three of the four epilepsy‐associated variants were missense variants. Thus, all three variants located in the G‐protein‐coupled receptor autoproteolytic‐inducing domain exhibited epilepsy. Interpretation: We found one new missense variant of ADGRL1 in one family with GEFS+. ADGRL1 may be a potential candidate or susceptibility gene for epilepsy. ADGRL1‐associated epilepsy ranged from benign GEFS+ to severe epileptic encephalopathy; the genotypes and variant locations may help explain the phenotypic heterogeneity of patients with the ADGRL1 variant. [ABSTRACT FROM AUTHOR]

The neural activity in the brain is detected through Electroencephalography (EEG) which enables the analysis and classification of epileptic disorder. The epileptic classification is challenging due to the presence of noise and artifacts in the EEG signal which increases the False Positive Rate (FPR) and minimizes the classification performance. Therefore, this research proposes an Enhanced State Refinement Gated Recurrent Unit with Temporal Activation Regularization (ESRGRU-TAR) for epileptic seizure classification. The ESRGRU optimizes the gating mechanism to enhance the capability to capture long-term dependencies in the data. Particularly, refinements are capable of quality of interactive models that reveal interactions among sample points thereby enhancing interpretability. The message-passing mechanism is developed to highlight useful feature representations between sample points. TAR is beneficial for controlling overfitting because it moderates the model’s activation by adding temporal consistency to the learning process. The BONN and CHB-MIT datasets are used to estimate the proposed ESRGRU-TAR performance based on the classifier. The ESRGRU-TAR achieves better accuracy of 99.91% and 99.89% for BONN and CHB-MIT datasets which is better than existing techniques such as Bidirectional Long Short-Term Memory (BiLSTM). [ABSTRACT FROM AUTHOR]

Aims: Few personalized monitoring models for valproic acid (VPA) in pediatric epilepsy patients (PEPs) incorporate machine learning (ML) algorithms. This study aimed to develop an ensemble ML model for VPA monitoring to enhance clinical precision of VPA usage. Methods: A dataset comprising 366 VPA trough concentrations from 252 PEPs, along with 19 covariates and the target variable (VPA trough concentration), was refined by Spearman correlation and multicollinearity testing (366 × 11). The dataset was split into a training set (292) and testing set (74) at a ratio of 8:2. An ensemble model was formulated by Gradient Boosting Regression Trees (GBRT), Random Forest Regression (RFR), and Support Vector Regression (SVR), and assessed by SHapley Additive exPlanations (SHAP) analysis for covariate importance. The model was optimized for R2, relative accuracy, and absolute accuracy, and validated against two independent external datasets (32 in-hospital and 28 out-of-hospital dataset). Results: Using the R2 weight ratio of GBRT, RFR and SVR optimized at 5:2:3, the ensemble model demonstrated superior performance in terms of relative accuracy (87.8%), absolute accuracy (78.4%), and R2 (0.50), while also exhibiting a lower Mean Absolute Error (9.87) and Root Mean Squared Error (12.24), as validated by the external datasets. Platelet count (PLT) and VPA daily dose were identified as pivotal covariates. Conclusion: The proposed ensemble model effectively monitors VPA trough concentrations in PEPs. By integrating covariates across various ML algorithms, it delivers results closely aligned with clinical practice, offering substantial clinical value for the guided use of VPA. [ABSTRACT FROM AUTHOR]

Aim: miR-134 has been widely reported as upregulated in experimental and human studies of Mesial Temporal Lobe Epilepsy the most common drug-resistant epilepsy (DRE). Studies have shown that the use of antagomirs, anti-miR-134, may be a promising therapeutic approach to these epilepsies. However, data on miR-134 in other epileptic syndromes is scarce. In this study, we aimed to quantify serum levels of miR-134 in a cohort of patients with Mesial Temporal Lobe Epilepsy-Hippocampal Sclerosis (MTLE-HS) and with Genetic Generalized Epilepsies (GGE). Additionally, we explored the correlation between miR-134 serum levels and clinical parameters, such as age at onset or febrile seizures antecedents, to evaluate its potential as a biomarker and therapeutic target in epilepsy. Methods: miR-134 levels were evaluated in cell-free serum of 131 patients with epilepsy (75 women, 56 men; age 41.10 ± 13.12 years; 72 with DRE) and 42 healthy individuals (25 women, 17 men; age 42.40 ± 9.80 years). The epilepsy cohort included 77 MTLE-HS patients and 54 GGE patients. Results: Patients with elevated miR-134 circulating levels were at higher risk of drug-resistant epilepsy (OR [95% CI] = 2.246 [1.111–4.539], p = 0.021). Other risk factors included an older age (OR [95% CI] = 1.032 [1.004–1.061], p = 0.025), history of febrile seizures (OR [95% CI] = 2.994 [1.385–6.471], p = 0.005) and higher disease duration (OR [95% CI] = 1.038 [1.011–1.066], p = 0.006). The strongest predictor of DRE was hippocampal sclerosis (OR [95% CI] = 10.338 [4.566–23.404], p < 0.001). Circulating miR-134 levels were significantly higher in MTLE-HS patients compared to controls (p < 0.05) and GGE patients (p < 0.05). However, the clinical utility of miR-134 in discriminating MTLE-HS patients from controls was only moderated (AUC = 0.651 ± 0.051 95% CI 0.551–0.751, p = 0.007). Conclusion: We show that miR-134 circulating levels are associated with DRE, especially in MTLE-HS, a syndrome characterized by severe hippocampal damage, consistent with activity-regulated miR-134 expression. This overexpression likely contributes to disease progression and our results support the potential of targeting miR-134 as a novel therapeutic approach for refractory epilepsy. [ABSTRACT FROM AUTHOR]

Purpose: To develop a 3D spherical EPTI (sEPTI) acquisition and a comprehensive reconstruction pipeline for rapid high‐quality whole‐brain submillimeter T2*$$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification. Methods: For the sEPTI acquisition, spherical k‐space coverage is utilized with variable echo‐spacing and maximum kx ramp‐sampling to improve efficiency and signal incoherency compared to existing EPTI approaches. For reconstruction, an iterative rank‐shrinking B0 estimation and odd‐even high‐order phase correction algorithms were incorporated into the reconstruction to better mitigate artifacts from field imperfections. A physics‐informed unrolled network was utilized to boost the SNR, where 1‐mm and 0.75‐mm isotropic whole‐brain imaging were performed in 45 and 90 s at 3 T, respectively. These protocols were validated through simulations, phantom, and in vivo experiments. Ten healthy subjects were recruited to provide sufficient data for the unrolled network. The entire pipeline was validated on additional five healthy subjects where different EPTI sampling approaches were compared. Two additional pediatric patients with epilepsy were recruited to demonstrate the generalizability of the unrolled reconstruction. Results: sEPTI achieved 1.4×$$ \times $$ faster imaging with improved image quality and quantitative map precision compared to existing EPTI approaches. The B0 update and the phase correction provide improved reconstruction performance with lower artifacts. The unrolled network boosted the SNR, achieving high‐quality T2*$$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification with single average data. High‐quality reconstruction was also obtained in the pediatric patients using this network. Conclusion: sEPTI achieved whole‐brain distortion‐free multi‐echo imaging and T2*$$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification at 0.75 mm in 90 s which has the potential to be useful for wide clinical applications. [ABSTRACT FROM AUTHOR]

Objective: To investigate the trends in epilepsy prevalence, incidence, mortality, and disability-adjusted life-years (DALYs) in all ages, with risk factors for epilepsy - associated death, from 1990 to 2021. Methods: Using the standardized Global Burden of Disease (GBD) methodologies, we evaluated the burden of epilepsy in 204 countries and regions from 1990 to 2021, aiming to derive a more precise representation of the health burden posed by epilepsy by considering four distinct types of epidemiological data, namely the prevalence, incidence, mortality, and DALYs. The presented data were meticulously estimated and displayed both as numerical counts and as age-standardized rates per 100,000 persons of the population. All estimates were calculated with 95% uncertainty intervals (UI). Finding: In 2021, there were 24,220,856 (95% UI: 18,476,943–30,677,995) patients with epilepsy, with an age-standardized prevalence rate (ASPR) of 307.38 per 100,000 persons (95% UI: 234.71–389.02) and an age-standardized incidence rate (ASIR) of 42.821 per 100,000 persons (95% UI: 31.24–53.72).The global age-standardized mortality rate (ASMR) of epilepsy was 1.74 per 100,000 population (95% UI: 1.46–1.92); The age-standardized DALYs rate (ASDR) were 177.85 per 100,000 population (95% UI: 137.66–225.90); 154.25 per 100,000 population for females [114.73–201.76], and 201.29 per 100,000 population for males [157.93–252.74]. All of the ASPR, ASIR, ASMR and ASDR of males were higher than those of females, and the ASIR of epilepsy was the highest in children aged 0–14, at 61.00(95% UI: 39.09–86.21), while the older adult group aged 70+ has the highest ASMR of 5.67(95% UI: 4.76–6.18). From 1990 to 2021, the number of epilepsy-related deaths and DALYs both decreased. However, the ASPR of epilepsy increased by about 6.9% (95% UI: −0.10–0.26), and the ASIR increased by almost 12% (95% UI: 0.05–0.33). The trends in ASPR, ASIR, ASMR and ASDR exhibited notable variations across different regions. Conclusion: Epilepsy is an increasing global health challenge with rising prevalence and incidence. Results of this cross-sectional study suggest that despite the global decline in deaths and DALYs, Epilepsy remains an important cause of disability and death, especially in low SDI regions. An improved understanding of the epidemiology of epilepsy may potentially have considerable benefits in reducing the global burden of epilepsy, by aiding in policy-making in low-income countries, provide data support for research on epilepsy medications and treatment methods. [ABSTRACT FROM AUTHOR]

Background: Drug-resistant epilepsy (DRE) patients exhibit aberrant large-scale brain networks. Objective: The purpose of investigation is to explore the differences in resting-state electroencephalogram (EEG) microstates between patients with DRE and well-controlled (W-C) epilepsy. Design: Retrospective study. Methods: Clinical data of epilepsy patients treated at the Epilepsy Center of Fujian Medical University Union Hospital from January 2020 to May 2023 were collected for a minimum follow-up period of 2 years. Participants meeting inclusion and exclusion criteria were categorized into two groups based on follow-up records: W-C group and DRE group. To ensure that the recorded EEG data were not influenced by medication, all EEG recordings were collected before patients commenced any antiepileptic drug treatment. Resting-state EEG datasets of all participants underwent microstate analysis. This study comprehensively compared the average duration, frequency per second, coverage, and transition probabilities (TPs) of each microstate between the two groups. Results: A total of 289 individuals who met the criteria were included, categorized into the W-C group (n = 112) and the DRE group (n = 177). EEG microstate analysis revealed substantial variances between the two groups. The analysis highlights differences in three of four microstate classifications. Microstate transition analysis demonstrated altered probabilities in DRE patients. Increased probabilities were observed in TPAB, TPBA, TPBC, TPCB, TPBD, and TPDB. Decreased probabilities included TPCA, TPDA, TPAC, TPAD, TPCD, and TPDC. Conclusion: This study highlights distinctive EEG microstate parameters and TPs in DRE patients compared to those with W-C epilepsy. The results may potentially advance the clinical application of EEG microstates. [ABSTRACT FROM AUTHOR]

Purpose: Epilepsy, a prevalent chronic neurological disorder, is associated with misconceptions, negative attitudes, and stigma because of poor public knowledge and awareness. Therefore, the purpose of the current study was to assess the knowledge, awareness, and attitudes toward epilepsy and its associated factors among the Lebanese general population. Methods: A cross-sectional study was conducted on Lebanese adults between October 2021 and June 2022 using an electronic structured self-administered questionnaire that was circulated online using the different social media platforms. Data related to participants' demographic characteristics, knowledge, awareness, and attitude about epilepsy were measured. Eight items were included in the knowledge score that ranged between "0 and 16", five items were included in the awareness score and ranged between 0 and 10. Likewise, the attitude score was calculated from 14 items and the score ranged between "0 and 28". Data was analyzed using descriptive statistics, and logistic regression was employed to identify factors associated with knowledge and awareness of epilepsy. Results: A total of 301 participants filled the questionnaire with a mean age of 28.68 and majority (66%) were females. The analyzed scores revealed that most of the participants (87.4%) had a good knowledge regarding epilepsy as a disease with mean of 10.2 (± 2.14), 70.1% had good awareness about epilepsy with mean of 6.3 (± 1.4), and 88% had good attitude toward patients with epilepsy with mean of 21.5 (± 6.2). Attending lecture about epilepsy was significantly associated with higher knowledge (OR 5.756, CI 95% 4.652–11.676, p < 0.001), better awareness (OR 4.936, CI 95% 3.062–10.566, p < 0.001) and attitude (OR 5.187, CI 95% 1.687–9.761, p < 0.014) toward the disease. Conclusion: The findings of this study reflected an adequate knowledge and awareness, as well a positive attitude toward patients with epilepsy in Lebanon. However, there is a need for raising societal awareness and understanding of epilepsy to minimize the public misconceptions and reduce the stigma and discriminatory attitudes toward epileptic patients. [ABSTRACT FROM AUTHOR]

Objective: Resistance to antiseizure medications (ASMs) is a major challenge in the treatment of patients with epilepsy. Despite numerous newly marketed ASMs, the proportion of drug-resistant people with epilepsy has not significantly decreased over the years. Therefore, novel and innovative seizure models for preclinical drug screening are highly desirable. Here, we explore the efficacy of a broad spectrum of ASMs in suppressing seizure activity in two established Drosophila melanogaster bang-sensitive mutants. These mutants respond with seizures to mechanical stimulation, providing a promising platform for screening novel ASMs. Methods: Seven frequently used ASMs (brivaracetam, cenobamate, lacosamide, lamotrigine, levetiracetam, phenytoin, and valproate) were administered to the bang-sensitive mutants easily shocked 2F (eas 2F ) and paralytic bss1 (para bss1 ). After 48 h of treatment, the flies were vortexed to induce mechanical stimulation. The seizure probability (i.e., ratio of seizing and non-seizing flies) as well as the seizure duration were analyzed. Results: In case of eas 2F mutants, treatment with the sodium channel blockers phenytoin and lamotrigine resulted in a robust reduction of seizure probability, whereas flies treated with lacosamide showed a decrease in seizure duration. Treatment with valproate resulted in both a reduction in seizure probability and in seizure duration. In contrast, levetiracetam, brivaracetam and cenobamate had no effect on the bang-sensitive phenotype of eas 2F flies. In case of para bss1 flies, none of the tested medications significantly reduced seizure activity, supporting its role as a model of intractable epilepsy. Significance: Our results show that particularly sodium channel blockers as well as valproate are effective in suppressing seizure activity in the bang-sensitive mutant eas 2F . These findings demonstrate the usability of Drosophila for screening drugs with antiseizure properties. Due to fewer ethical concerns, the short life cycle, and low maintenance costs, Drosophila might provide an attractive and innovative high-throughput model for the discovery of novel antiseizure compounds. [ABSTRACT FROM AUTHOR]

Dynamical theories of speech processing propose that the auditory cortex parses acoustic information in parallel at the syllabic and phonemic timescales. We developed a paradigm to independently manipulate both linguistic timescales, and acquired intracranial recordings from 11 patients who are epileptic listening to French sentences. Our results indicate that (i) syllabic and phonemic timescales are both reflected in the acoustic spectral flux; (ii) during comprehension, the auditory cortex tracks the syllabic timescale in the theta range, while neural activity in the alpha-beta range phase locks to the phonemic timescale; (iii) these neural dynamics occur simultaneously and share a joint spatial location; (iv) the spectral flux embeds two timescales--in the theta and low-beta ranges--across 17 natural languages. These findings help us understand how the human brain extracts acoustic information from the continuous speech signal at multiple timescales simultaneously, a prerequisite for subsequent linguistic processing. [ABSTRACT FROM AUTHOR]

Background: Epilepsy is one of the most common neurologic disorders affecting approximately 51 million people globally and is associated with significant cases of age-standardized DALYs (182.6 per 100 000 people). The quality of health care services offered to people suffering from epilepsy often fails to meet standards in Ethiopia or internationally. This study was designed to assess the quality of care and associated factors among patients with epilepsy at public hospitals in Arba Minch Town, 2024. Method: A facility-based cross-sectional study was conducted among 392 adult epileptic patients attending public hospitals in Arba Minch Town. Data entry was performed via Epi-data 3.1 software, and the data were analyzed via SPSS version 24 software. Binary logistic regression analysis was used to evaluate the associations between quality of care and sociodemographic, disease-related, and treatment-related factors. Multivariate logistic regression analysis was applied to identify factors independently associated with quality of care. Results: Three hundred ninety-two adults with epilepsy participated in this study, for a response rate of 92.7%. More than one-half of the 237 (60.5%) patients were males, with a median age of 31 ± 12 years (interquartile range). Fewer than one-half (44.1%) of the patients adhered to antiepileptic medicines. The overall proportion of patients receiving quality care was 213 (54.3%). The seizure control rate was also low, at 130 (33.2%). Patients aged 18–29 years [AOR = 30.8 (95% CI, 8.22–35.616, p < 0.000)] and aged 30–39 years [AOR = 18.4 (95% CI, 5.016–67.613, p < 0.000)], and a seizure frequency of less than three [AOR = 2.318 (95% CI, 1.028–5.225, p < 0.043)] were positively associated with quality of care. Whereas, having poor knowledge about epilepsy [AOR = 0.107 (95% CI, 0.0.057–0.202, p < 0.000)] was negatively associated with quality care. Conclusion: The quality of care provided to adult epilepsy patients at Arba Minch was low. In addition, patient knowledge, medication adherence, and the seizure control rate were also suboptimal. Therefore, addressing identified factors by involving all relevant stakeholders (health professionals, hospitals, zonal health departments, regional health bureaus, and patients) is critical for improving the quality of care. In addition, researchers willing to study this topic should use strong designs that can determine causal determinants of quality care. [ABSTRACT FROM AUTHOR]

Seizure localization is important for managing drug‐resistant focal epilepsy. Here, the capability of a novel deep learning‐based source imaging framework (DeepSIF) for imaging seizure activities from electroencephalogram (EEG) recordings in drug‐resistant focal epilepsy patients is investigated. The neural mass model of ictal oscillations is adopted to generate synthetic training data with spatio‐temporal‐spectra features similar to ictal dynamics. The trained DeepSIF model is rigorously validated using computer simulations and in a cohort of 33 drug‐resistant focal epilepsy patients with high‐density (76‐channel) EEG seizure recordings, by comparing DeepSIF estimates with surgical resection outcome and seizure onset zone (SOZ). These findings show that the trained DeepSIF model outperforms other methods in estimating the spatial and temporal information of origins of ictal activities. It achieves a high spatial specificity of 96% and a low spatial dispersion of 3.80 ± 5.74 mm when compared to the resection region. The source imaging results also demonstrate good coverage of SOZ, with an average distance of 10.89 ± 10.14 mm (from the SOZ to the reconstruction). These promising results suggest that DeepSIF has significant potential for advancing noninvasive imaging of the origins of ictal activities in patients with focal epilepsy, aiding management of intractable epilepsy. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance In onchocerciasis‐endemic areas, limited access to antiseizure medications (ASMs) contributes to a high epilepsy burden. This study evaluated the impact of a community‐based epilepsy care program in Mahenge, Tanzania, an onchocerciasis‐endemic area with high epilepsy prevalence.A baseline survey (2017–2018) identified persons with epilepsy (PWE) in four rural villages. Subsequently, PWE were invited to enroll in the epilepsy treatment program (2019–2022), where trained community health workers (CHWs) screened for epilepsy, promoted ivermectin intake to treat onchocerciasis, distributed ASMs, and monitored seizure frequency and ASM adherence monthly under supervision from the project clinician trained in epilepsy diagnosis and treatment. A concluding survey (2022) collected sociodemographic data and participants' status as alive, deceased, or lost to follow‐up. Mixed‐effects negative binomial regression analyzed risk factors for weekly seizure incidence rate.Of 206 participants, 77.7% reported bilateral tonic–clonic seizures, and 32.0% reported focal seizures. More than one third (38.5%) were suspected of having nodding syndrome. Weekly seizure frequency decreased significantly from a mean of 1.9 seizures (interquartile range [IQR] = 0–2) at enrollment to .4 seizures (IQR = 0–0) at the last follow‐up (Wilcoxon test p < .0001), with significantly improved ASM adherence (57.5%–94.7%, McNemar test p < .0001). Factors associated with lower weekly seizure incidence included longer program participation, ASM adherence, carbamazepine use compared to phenobarbital, and ivermectin intake in 2022. ASM adverse events were associated with increased seizure frequency. The mortality rate was 32.7 deaths per 1000 person‐years, with most deceased not fully adhering to ASM (88%) and having epilepsy‐related causes of death (60%).The community‐based program using CHWs was associated with a significant reduction in seizure frequency and improved ASM adherence. In onchocerciasis‐endemic areas, it should be investigated whether carbamazepine should be a preferred ASM in PWE. Ivermectin's impact on seizure frequency merits further investigation in onchocerciasis‐endemic areas. Community‐based epilepsy care is a promising strategy for scaling up epilepsy care in rural areas in Africa. [ABSTRACT FROM AUTHOR]

Body perception plays a fundamental role in social cognition. Yet, the neural mechanisms underlying this process in humans remain elusive given the spatiotemporal constraints of functional imaging. Here, we present intracortical recordings of single-and multiunit spiking activity in two epilepsy surgery patients in or near the extrastriate body area, a critical region for body perception. Our recordings revealed a strong preference for human bodies over a large range of control stimuli. Notably, body selectivity was driven by a distinct selectivity for body parts. The observed body selectivity generalized to nonphotographic depictions of bodies including silhouettes and stick figures. Overall, our study provides unique neural data that bridge the gap between human neuroimaging and macaque electrophysiology studies, laying a solid foundation for computational models of human body processing. [ABSTRACT FROM AUTHOR]

The precise localization of epileptic foci with the help of EEG or iEEG signals is still a clinical challenge with current methodology, especially if the foci are not close to individual electrodes. On the research side, dipole reconstruction for focus localization is a topic of recent and current developments. Relatively low numbers of recording electrodes cause ill-posed and ill-conditioned problems in the inversion of lead-field matrices to calculate the focus location. Estimations instead of tissue conductivity measurements further deteriorate the precision of location tasks. In addition, time-resolved phase shifts are used to describe connectivity. We hypothesize that correlations over runtime approaches might be feasible to predict seizure foci with adequate precision. In a case study on EEG correlation in a healthy subject, we found repetitive periods of alternating high correlation in the short (20 ms) and long (300 ms) range. During these periods, a numerical determination of proportions of predominant latency and, newly established here, directionality is possible, which supports the identification of loops that, according to current opinion, manifest themselves in epileptic seizures. In the future, this latency and directionality analysis could support focus localization via dipole reconstruction using new triangulation calculations. [ABSTRACT FROM AUTHOR]

TIMM50, an essential TIM23 complex subunit, is suggested to facilitate the import of ~60% of the mitochondrial proteome. In this study, we characterized a TIMM50 disease-causing mutation in human fibroblasts and noted significant decreases in TIM23 core protein levels (TIMM50, TIMM17A/B, and TIMM23). Strikingly, TIMM50 deficiency had no impact on the steady-state levels of most of its putative substrates, suggesting that even low levels of a functional TIM23 complex are sufficient to maintain the majority of TIM23 complex-dependent mitochondrial proteome. As TIMM50 mutations have been linked to severe neurological phenotypes, we aimed to characterize TIMM50 defects in manipulated mammalian neurons. TIMM50 knockdown in mouse neurons had a minor effect on the steady state level of most of the mitochondrial proteome, supporting the results observed in patient fibroblasts. Amongst the few affected TIM23 substrates, a decrease in the steady state level of components of the intricate oxidative phosphorylation and mitochondrial ribosome complexes was evident. This led to declined respiration rates in fibroblasts and neurons, reduced cellular ATP levels, and defective mitochondrial trafficking in neuronal processes, possibly contributing to the developmental defects observed in patients with TIMM50 disease. Finally, increased electrical activity was observed in TIMM50 deficient mice neuronal cells, which correlated with reduced levels of KCNJ10 and KCNA2 plasma membrane potassium channels, likely underlying the patients' epileptic phenotype. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance Studies have shown that a growing number of people with epilepsy belong to minority groups and experience health disparities. Inclusivity in clinical trial enrollment is essential for advancing health access but has not been well studied among epilepsy trials. The objective of this study was to analyze US epilepsy clinical trials to identify the prevalence and trends associated with race and sex enrollment disparities.We queried the Clinicaltrials.gov registry to identify completed epilepsy clinical trials with results reported between 2006 and 2022. Studies were assessed for reporting of participant race and sex information, and measures of trial diversity including the participation to prevalence ratio (PPR), representation ratio (RR), and representation quotient (RQ) were calculated. Other data including funding source, intervention type, location, and trial dates were also extracted.Ninety trials met inclusion criteria, of which 89 (99%) and 53 (59%) reported participant sex and race, respectively. Three trials included only female participants and were excluded from further sex‐specific analyses. Females were underrepresented in 10 of the remaining 86 trials reporting sex information (PPR < .8, 12%). We found that industry‐funded trials were more likely to have equal female representation among participants (p = .0197). Of trials reporting participant race, 52 (98%) exhibited a lack of racial diversity (RQ < 1). Black participants were the most frequently underrepresented racial group (RR < 1, 42 of 53 trials, 79%).Our findings highlight significant disparities in epilepsy clinical trial enrollment, particularly for Black participants. Lack of diversity and underrepresentation of historically marginalized populations may contribute to research biases and perpetuate health inequities. More inclusive research practices are needed to ensure all people with epilepsy have access to effective care. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance Patients with newly diagnosed epilepsy exhibit brain white matter (WM) abnormalities, but the temporal dynamics of these are unknown. The literature suggests these alterations might be present before diagnosis. This study investigates WM microstructural integrity using diffusion imaging in non‐lesional (NL), interictal epileptiform discharge (IED)‐free, unmedicated patients who experienced a first unprovoked seizure compared to healthy controls. Furthermore, we evaluated whether the patients who developed epilepsy within a 1‐year follow‐up had a divergent pattern of WM alterations in contrast to those who did not. We also evaluated patients with established epilepsy.We performed a diffusion imaging analysis in a cohort of 82 subjects. Twenty patients recently experienced a first unprovoked seizure (first‐seizure group), 32 patients had chronic epilepsy (chronic‐epilepsy group), and 30 healthy controls. The first‐seizure patients were later classified into patients who developed epilepsy (early‐epilepsy) and those who did not (single‐seizure). Fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) were calculated. Group differences were analyzed using tract‐based spatial statistics and permutation analysis of linear models.Compared to controls, first‐seizure patients showed decreased FA (p < .05, d = 1.3) in the corpus callosum and forceps minor, among other tracts. Similar changes were found in the single‐seizure group (p < .05, d = 1.3), whereas the early‐epilepsy patients showed decreases only in the corpus callosum (p < .05, d = 2.4). We confirmed that patients with chronic epilepsy have widespread FA decreases (p < .05, d = 1).We provide evidence that, as early as after the first unprovoked seizure, patients considered NL by conventional methods harbor marked microstructural abnormalities detectable with diffusion magnetic resonance imaging (MRI). These findings suggest that WM alterations are present very early in the epileptogenic process even before the diagnosis can currently be made. These results have important implications for better understanding the epileptogenic process and preexisting structural difference in patients after a first seizure. [ABSTRACT FROM AUTHOR]

Nowadays, particularly in countries with high incomes, individual mutations in people affected by genetic epilepsies are identified, and genetic therapies are being developed. In addition, drugs are being screened to directly target specific mutations, and personalised medicine is possible. However, people with epilepsy do not yet benefit from these advances, and many types of epilepsies are medication‐resistant, including Dravet syndrome. Thus, in the meantime, alternative and effective treatment options are needed. There is increasing evidence that metabolic deficits contribute to epileptic seizures and that such metabolic impairments may be amenable to treatment, with metabolic treatment options like the ketogenic diet being employed with some success. However, the brain metabolic alterations that occur in ion channel epilepsies are not well‐understood, nor how these may differ from epilepsies that are of acquired and unknown origins. Here, we provide an overview of studies investigating metabolic alterations in epilepsies caused by mutations in the SCN1A and KCNA1 genes, which are currently the most studied ion channel epilepsies in animal models. The metabolic changes found in these models are likely to contribute to seizures. A metabolic basis of these ion channel epilepsies is supported by human and/or animal studies that show beneficial effects of the ketogenic diet, which may be mediated by the provision of auxiliary brain fuel in the form of ketone bodies. Other potentially more preferred dietary therapies including medium‐chain triglycerides and triheptanoin have also been tested in a limited number of studies, but their efficacies remain to be clearly established. The extent to which brain metabolism is affected in people with Dravet syndrome, KCNA1 epilepsy and the models thereof still requires clarification. This requires more experiments that yield functional insight into metabolism. [ABSTRACT FROM AUTHOR]

Epilepsy, a clinical diagnosis characterised by paroxysmal episodes known as seizures, affects 1% of people worldwide. Safe and patient‐specific treatment is vital and can be achieved by the development of rapid pre‐clinical models of for identified epilepsy genes. Epilepsy can result from either brain injury or gene mutations, and can also be induced chemically. Xenopus laevis tadpoles could be a useful model for confirmation of variants of unknown significance found in epilepsy patients, and for drug re‐purposing screens that could eventually lead to benefits for patients. Here, we characterise and quantify seizure‐related behaviours in X. laevis tadpoles arrayed in 24‐well plates. To provoke acute seizure behaviours, tadpoles were chemically induced with either pentylenetetrazole (PTZ) or 4‐aminopyridine (4‐AP). To test the capacity to adapt this method for drug testing, we also exposed induced tadpoles to the anti‐seizure drug valproate (VPA). Four induced seizure‐like behaviours were described and manually quantified, and two of these (darting, circling) could be accurately detected automatically, using the video analysis software TopScan. Additionally, we recorded swimming trajectories and mean swimming velocity. Automatic detection showed that either PTZ or 4‐AP induced darting behaviour and increased mean swimming velocity compared to untreated controls. Both parameters were significantly reduced in the presence of VPA. In particular, darting behaviour was a shown to be a sensitive measure of epileptic seizure activity. While we could not automatically detect the full range of seizure behaviours, this method shows promise for future studies since X. laevis is a well‐characterised and genetically tractable model organism. [ABSTRACT FROM AUTHOR]

Background and Purpose: Adenosine, through the A1 receptor (A1R), is an endogenous anticonvulsant. The development of adenosine receptor agonists as antiseizure medications has been hampered by their cardiac side effects. A moderately A1R‐selective agonist, MRS5474, has been reported to suppress seizures without considerable cardiac action. Hypothesizing that this drug could act through other than A1R and/or through a disease‐specific mechanism, we assessed the effect of MRS5474 on the hippocampus. Experimental Approach: Excitatory synaptic currents, field potentials, spontaneous activity, [3H]GABA uptake and GABAergic currents were recorded from rodent or human hippocampal tissue. Alterations in adenosine A3 receptor (A3R) density in human tissue were assessed by Western blot. Key Results: MRS5474 (50–500 nM) was devoid of effect upon rodent excitatory synaptic signals in hippocampal slices, except when hyperexcitability was previously induced in vivo or ex vivo. MRS5474 inhibited GABA transporter type 1 (GAT‐1)‐mediated γ‐aminobutyric acid (GABA) uptake, an action not blocked by an A1R antagonist but blocked by an A3R antagonist and mimicked by an A3R agonist. A3R was overexpressed in human hippocampal tissue samples from patients with epilepsy that had focal resection from surgery. MRS5474 induced a concentration‐dependent potentiation of GABA‐evoked currents in oocytes micro‐transplanted with human hippocampal membranes prepared from epileptic hippocampal tissue but not from non‐epileptic tissue, an action blocked by an A3R antagonist. Conclusion and Implications: We identified a drug that activates A3R and has selective actions on epileptic hippocampal tissue. This underscores A3R as a promising target for the development of antiseizure medications. [ABSTRACT FROM AUTHOR]

Objective: The study aims to assess the relationship between epilepsy and circadian rhythms. Method: This study included a cohort of 7,410 participants sourced from the 2013–2014 National Health and Nutrition Examination Survey (NHANES) database. The investigation focused on the comparative analysis of seven nonparametric indices associated with circadian rhythms (Interdaily Stability (IS), Intradaily Variability (IV), Relative Amplitude (RA), L5, M10, L5 start time, and M10 start time) between the overall population and patients with epilepsy. Logistic regression analysis was utilized to assess the potential correlation between the rest-activity circadian rhythm patterns and the presence of epilepsy within the cohort. Results: Compared to the general population, individuals with epilepsy exhibited lower values of IS and M10. Multivariable logistic regression analysis, when IS, RA, and M10 were categorized into four groups based on quartiles, revealed that the odds ratio (IS: OR = 0.36, 95% CI: 0.13, 0.89; RA: OR = 0.25, 95% CI: 0.06, 0.77; M10: OR = 0.24, 95% CI: 0.06, 0.73) for the highest quartile was lower than that for the lowest quartile. Furthermore, after adjustment for confounding factors, participants in the highest quartile compared to those in the lowest quartile of IV and M10 start time demonstrated a higher prevalence of epilepsy. Conclusion: Individuals with epilepsy demonstrate significant alterations in circadian rhythms. [ABSTRACT FROM AUTHOR]

Dipeptides (DPs), composed of two amino acids (AAs), hold significant therapeutic potential but remain underexplored. Given the crucial role of AAs in central nervous system (CNS) function, this study investigated the presence of DPs in cerebrospinal fluid (CSF) and their correlation with corresponding AAs, potentially indicating their role as AA donors. Plasma and CSF samples were collected from 43 children with neurological or metabolic conditions of unknown origin, including 23 with epilepsy. A panel of 33 DPs was quantified using UPLC-MS/MS. Out of 33 DPs, 18 were detectable in CSF and 20 in plasma, displaying high inter-individual variance. Gly-Asp, Gly-Pro, and Ala-Glu were consistently found in all CSF samples, while only Gly-Asp was universally detectable in plasma. Anserine and carnosine were prominent in CSF and plasma, respectively, with no other histidine-containing DPs observed. Generally, DP concentrations were higher in plasma than in CSF; however, anserine and Gly-Pro had similar concentrations in both fluids. Significant correlations were observed between specific DPs and their corresponding AAs in CSF (Gly-Glu, Gly-Pro and Ser-Gln) and plasma (Glu-Glu and Glu-Ser). Notably, patients with epilepsy had elevated medium anserine concentrations in CSF. This study is the first to demonstrate the presence of numerous DPs in CSF and plasma. Further research is needed to determine if DP patterns can support the diagnosis of neurological diseases and whether DP administration can modulate amino acid availability in the brain, potentially offering new therapeutic options, such as for defects in the amino acid transporter. [ABSTRACT FROM AUTHOR]

Introduction: Understanding the lived experience of mental health and illness in people with epilepsy has been little investigated in Africa and yet is essential to inform person-centered care. The aim of this study was to explore the experiences mental ill-health in the contexts of the lives of people with epilepsy in rural Ethiopia. Methods: A phenomenological approach was employed using in-depth individual interviews with PWE. Participants were selected purposely. The setting was Gurage Zone in south-central Ethiopia, where efforts had been made to expand access to mental health and epilepsy care through integration in primary health care. Thematic analysis was used. Result: Twenty-two participant were interviewed (8 women, 14 men). The following themes were identified: expression of ill-health; the essence of emotions; the emotional burden of epilepsy and aspirations and mitigating impacts. Participants reported multiple bodily (e.g., fatigue) and emotional (e.g., irritability, sadness) experiences that were tied up with their experience of epilepsy and not separable into physical vs. mental health. Occupation and social life difficulties were interconnected with emotional and bodily sickness. Emotions were considered inherently concerning, with emotional imbalance spoken of as a cause or trigger for seizures. These emotional burdens resulted in difficulties fulfilling occupational and social life obligations, in turn exacerbating the epilepsy-related stigma experienced by others. Participants sought to mitigate these interconnected psychosocial impacts through finding spiritual meaning in, or acceptance of, their experiences, drawing on family care and, for some, emotional support from health professionals. Conclusions: People living with epilepsy in this rural Ethiopian setting experience various emotional, financial, occupational and interpersonal problems that are crucially interwoven with one another and with the experience of epilepsy. A people-centered approach to support the recovery of people with epilepsy requires consideration of mental health alongside physical health, as well as interventions outside the health system to address poverty and stigma. [ABSTRACT FROM AUTHOR]

Recent discoveries have revealed that genetic variants in γ-aminobutyric acid type A (GABAA) receptor subunits can lead to both gain-of-function (GOF) and loss-of-function (LOF) receptors. GABAA receptors, however, have a pseudosymmetrical pentameric assembly, and curiously diverse functional outcomes have been reported for certain homologous variants in paralogous genes (paralogous variants). To investigate this, we assembled a cohort of 11 individuals harboring paralogous M1 proline missense variants in GABRA1, GABRB2, GABRB3, and GABRG2. Seven mutations (α1P260L, α1P260S, β2P252L, β3P253L, β3P253S, γ2P282A, and γ2P282S) in α1β2/3γ2 receptors were analyzed using electrophysiological examinations and molecular dynamics simulations. All individuals in the cohort were diagnosed with developmental and epileptic encephalopathy, with a median seizure onset age of 3.5 mo, and all exhibited global developmental delay. The clinical data for this cohort aligned with established GABAA receptor GOF but not LOF cohorts. Electrophysiological assessments revealed that all variants caused GOF by increasing GABA sensitivity by 3- to 23-fold. In some cases, this was accompanied by LOF traits such as reduced maximal current amplitude and enhanced receptor desensitization. The specific subunit mutated and whether the mutation occurred in one or two subunits within the pentamer influenced the overall effects. Molecular dynamics simulations confirmed similar structural changes from all mutations, but with position-dependent asymmetry. These findings establish that paralogous variants affecting the 100% conserved proline residue in the M1 transmembrane helix of GABAAR subunits all lead to overall GOF traits. The unexpected asymmetric and mixed effects on receptor function have broader implications for interpreting functional analyses for multimeric ion-channel proteins. [ABSTRACT FROM AUTHOR]

Background: The risk of seizure aggravation following coronavirus disease 2019 (COVID-19) vaccines is a major cause behind vaccine hesitancy among patients with epilepsy (PWE), resulting in lower immunization rates. This work aimed to investigate the impact of COVID-19 different vaccines on seizure control in PWE. Results: This study was conducted on 110 PWE who received at least the first dose of any COVID-19 vaccine. Sixty-one (55.5%) patients did not develop any side effects from vaccination. There was no statistically significant change in seizure frequency following receiving COVID-19 vaccines, either adenoviral vector vaccines, inactivated vaccines, or mRNA vaccines (P = 0.733, 0.778, respectively). Twelve patients (10.9%) experienced seizure exacerbation following COVID-19 vaccination; seizure occurrence in the first 24 h immediately after the vaccine was reported in only one patient. There were no statistically significant differences between patients who developed seizure exacerbation following COVID-19 vaccination and those who did not develop regarding age, age at onset, seizure etiology, type of vaccine, or seizure exacerbation following COVID-19 infection. Conclusions: There is a low likelihood of COVID-19 vaccine-related seizure exacerbations in PWE. This data can be utilized to counsel PWE regarding the safety of COVID-19 vaccination. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance To date, the identification of objective biomarkers of neural epileptic activity (EA) remains challenging. We therefore investigated whether neuronal complexity could serve as an interictal electroencephalographic measure of EA, independent of interictal epileptiform discharges (IEDs). By tapering anti‐seizure medication (ASM) during video‐EEG (electroencephalography) monitoring (VEM), we studied whether changes in neuronal complexity could reliably indicate the increase in EA and identify patients with epilepsy.The study included 27 patients with unilateral mesial temporal lobe epilepsy (TLE) and 24 control patients with non‐epileptic episodes (NEEs) only, each undergoing ASM reduction during VEM. Thirteen additional patients undergoing intracranial recordings during VEM were included to study the relation of surface EEG complexity to intracranial IED. Neuronal complexity was quantified using sample entropy. Delta power served as a control parameter. Receiver‐operating characteristic (ROC) analysis was used to evaluate diagnostic performance.As ASM was reduced, patients with epilepsy showed a significant decrease in neuronal complexity over consecutive days (p = .0008). In contrast, patients with NEE showed no significant change in neuronal complexity (p = .78). Delta power in contrast increased and did not differ significantly between patients with TLE and patients with NEE (p = 1). ROC analysis demonstrated that neuronal complexity effectively distinguished between patients with epilepsy and patients with NEE (area under the curve [AUC] = .76), whereas delta power performed at chance level (AUC = .5). Analysis of simultaneously recorded surface and intracranial EEG showed that hippocampal IEDs are followed by an increase in surface EEG delta power (p = 1.8 × 10−18) without any significant change in complexity (p = .39).An increase in EA caused by ASM reduction resulted in a loss of neuronal complexity in surface EEG recordings of patients with epilepsy, independent of IEDs. These findings suggest that neuronal complexity could serve as a potential biomarker to differentiate between epilepsy patients and those with NEEs only. This holds promise for improving the clinical evaluation of EA in epilepsy, addressing the limitations of seizure frequency and IED identification. [ABSTRACT FROM AUTHOR]

Objective: Although seizures are the cardinal feature, epilepsy is associated with other forms of brain dysfunction including impaired cognition, abnormal sleep, and increased risk of developing dementia. We hypothesized that, given the widespread neurologic dysfunction caused by epilepsy, accelerated brain aging would be seen. We measured the sleep-based brain age index (BAI) in a diverse group of patients with epilepsy. The BAI is a machine learning-based biomarker that measures how much the brain activity of a person during overnight sleep deviates from chronological age-based norms. Methods: This case–control study drew information of age-matched controls without epilepsy from home sleep monitoring volunteers and from non-epilepsy patients with Sleep Lab testing. Patients with epilepsy underwent in-patient monitoring and were classified by epilepsy type and seizure burden. The primary outcomes measured were BAI, processed from electroencephalograms, and epilepsy severity metrics (years with epilepsy, seizure frequency standardized by year, and seizure burden [number of seizures in life]). Subanalyses were conducted on a subset with NIH Toolbox cognitive testing for total, fluid, and crystallized composite cognition. Results: 138 patients with epilepsy (32 exclusively focal and 106 generalizable [focal seizures with secondary generalization]) underwent in-patient monitoring, and age-matched, non-epilepsy controls were analyzed. The mean BAI was higher in epilepsy patients vs controls and differed by epilepsy type: −0.05 years (controls) versus 5.02 years (all epilepsy, p < 0.001), 5.53 years (generalizable, p < 0.001), and 3.34 years (focal, p = 0.03). Sleep architecture was disrupted in epilepsy, especially in generalizable epilepsy. A higher BAI was positively associated with increased lifetime seizure burden in focal and generalizable epilepsies and associated with lower crystallized cognition. Lifetime seizure burden was inversely correlated with fluid, crystallized, and composite cognition. Significance: Epilepsy is associated with accelerated brain aging. Higher brain age indices are associated with poorer cognition and more severe epilepsy, specifically generalizability and higher seizure burden. These findings strengthen the use of the sleep-derived, electroencephalography-based BAI as a biomarker for cognitive dysfunction in epilepsy. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance Previous retrospective studies have reported vigabatrin‐associated brain abnormalities on magnetic resonance imaging (VABAM), although clinical impact is unknown. We evaluated the association between vigabatrin and predefined brain magnetic resonance imaging (MRI) changes in a large homogenous tuberous sclerosis complex (TSC) cohort and assessed to what extent VABAM‐related symptoms were reported in TSC infants.The Dutch TSC Registry and the EPISTOP cohort provided retrospective and prospective data from 80 TSC patients treated with vigabatrin (VGB) before the age of 2 years and 23 TSC patients without VGB. Twenty‐nine age‐matched non‐TSC epilepsy patients not receiving VGB were included as controls. VABAM, specified as T2/fluid‐attenuated inversion recovery hyperintensity or diffusion restriction in predefined brain areas, were examined on brain MRI before, during, and after VGB, and once in the controls (at approximately age 2 years). Additionally, the presence of VABAM accompanying symptoms was evaluated.Prevalence of VABAM in VGB‐treated TSC patients was 35.5%. VABAM‐like abnormalities were observed in 13.5% of all patients without VGB. VGB was significantly associated with VABAM (risk ratio [RR] = 3.57, 95% confidence interval [CI] = 1.43–6.39), whereas TSC and refractory epilepsy were not. In all 13 VGB‐treated patients with VABAM for whom posttreatment MRIs were available, VABAM entirely resolved after VGB discontinuation. The prevalence of symptoms was 11.7% in patients with VABAM or VABAM‐like MRI abnormalities and 4.3% in those without, implicating no significant association (RR = 2.76, 95% CI = .68–8.77).VABAM are common in VGB‐treated TSC infants; however, VABAM‐like abnormalities also occurred in children without either VGB or TSC. The cause of these MRI changes is unknown. Possible contributing factors are abnormal myelination, underlying etiology, recurrent seizures, and other antiseizure medication. Furthermore, the presence of VABAM (or VABAM‐like abnormalities) did not appear to be associated with clinical symptoms. This study confirms that the well‐known antiseizure effects of VGB outweigh the risk of VABAM and related symptoms. [ABSTRACT FROM AUTHOR]

Despite some evidence of a possible link between epileptogenesis and tumorigenesis in glioblastoma, the prognostic value of epilepsy at presentation has been debated over the years. We performed a systematic review and meta-analysis to summarize all published data evaluating the prognostic significance of seizures as a presenting manifestation of glioblastoma. A comprehensive search of five databases from inception to December 2023 was conducted. Included studies underwent meta-analysis, with subgroup analyses performed to identify sources of heterogeneity. Fifteen studies were included in the analysis. Seizures were considered a favorable prognostic factor in seven studies, while eight studies found no differences in overall survival between patients with seizures and those with other presenting symptoms. Eleven studies were included in the meta-analysis. The overall pooled analysis indicated a potentially favorable prognostic impact of seizures at the clinical onset of glioblastoma (HR 0.73; 95% CI 0.61–0.87). However, subgroup analysis within studies focusing on IDH-wild type cases showed no discernible impact from preoperative seizures. Retrospective design, poor quality in reporting results, and heterogeneity in tumor characteristics and therapies are the main limitations of included studies. Future prospective studies on large, homogeneous cohorts of patients with IDH-wild type glioblastoma are warranted. Overall, these findings suggest that while seizures may hold some prognostic value, further research is essential to clarify their role. Understanding the true prognostic role of seizures at clinical onset may enhance our ability to predict patient outcomes and guide clinical decision-making. [ABSTRACT FROM AUTHOR]

Neuroplasticity refers to functional and structural changes in brain regions in response to healthy and pathological activity. Activity dependent plasticity induced by epileptic activity can involve healthy brain regions into the epileptogenic network by perturbing their excitation/inhibition balance. In this article, we present a new neural mass model, which accounts for neuroplasticity, for investigating the possible mechanisms underlying the epileptogenic network expansion. Our multiple-timescale model is inspired by physiological calcium-mediated synaptic plasticity and pathological extrasynaptic N-methyl-D-aspartate (NMDA) dependent plasticity dynamics. The model highlights that synaptic plasticity at excitatory connections and structural changes in the inhibitory system can transform a healthy region into a secondary epileptic focus under recurrent seizures and interictal activity occurring in the primary focus. Our results suggest that the latent period of this transformation can provide a window of opportunity to prevent the expansion of epileptogenic networks, formation of an epileptic focus, or other comorbidities associated with epileptic activity. Author summary: Repetitive epileptic activity leads to a large variety of plastic changes in brain. Understanding the mechanism and its time course can indicate windows of opportunity for preventing the devastating impact of focal epileptic activity on brain networks. Animal models of focal epilepsy have underlined the role of NMDA receptors and deregulations in the GABAergic system in the expansion of epileptic activity. Here we develop a plastic neural mass model integrating physiological and pathologic plasticity. Our results show that neuroplasticity mediated by epileptic activity increases synaptic efficacy between epileptic and healthy regions, and causes irreversible changes in the GABAergic system in the healthy region. The model gives mechanistic insights into the physio-pathological impact of focal epileptic activity on large-scale networks and suggests that seizures may beget seizures. [ABSTRACT FROM AUTHOR]

Background & Objective: Takotsubo cardiomyopathy (TCM), manifests as left ventricular dysfunction triggered by physical or emotional stress. It leads to higher morbidity in epileptic patients and can progress to complications. To find out the correlation between Takotsubo cardiomyopathy and epilepsy and to investigate pathophysiology and associated types of epilepsy. Methodology: This systematic review adhered to PRISMA guidelines and was sourced from the PubMed Central database. Search terms were pertinent to cardiomyopathy and epilepsy. Sixteen studies, comprising case reports and a case series were selected from 2000 to 2023 for data extraction. The quality evaluation was executed via the Joanna Briggs Institute Critical Appraisal checklist. Results: The review included 18 female patients with a mean age of 57.22 years. Predominant symptoms included tonic-clonic seizures (66.66%). Seizure-induced TCM pathophysiology implicates catecholamine surge, precipitating myocardial stunting and characteristic apical ballooning. Most patients had a history of epilepsy (38.88%). ECG findings showed tachycardia (38.88%) and ST-segment elevation (38.88%). Elevated troponin levels were noted in 83.33% of patients. Echocardiography showed reduced ejection fraction (72.22%), hypokinesia (38.88%) and akinesis (27.77%). Treatment involved Benzodiazepines (50%), Beta-blockers (61.11%) and Phenytoin (38.88%). The majority of patients showed improvement in echocardiography findings (55.55%) and ECG findings (11.11%). Conclusion: TCM in epilepsy patients evinces significant female predominance, with pathophysiology rooted in seizureinduced catecholamine surge. Early recognition in high-risk patients is essential in preventing complications. [ABSTRACT FROM AUTHOR]

The swift updates of public databases and advancements in next-generation sequencing (NGS) technologies have enhanced the genetic identification capacities of epilepsy clinics. This study aimed to evaluate the diagnostic efficacy of NGS in pediatric epilepsy patients as a whole and to present the data obtained in the whole exome sequence analysis. We enrolled 40 children with suspected childhood epilepsy in this study. All patients underwent evaluation by a clinical geneticist or pediatric neurologist and the molecular genetic analysis of those children was performed by whole-exome sequencing (WES). Out of the 40 patients, 12 (30%) received a genetic diagnosis, involving 14 mutations across 13 genes. The cumulative positive diagnostic yield was 30%. Twelve of these patients were identified to have 5 variants previously documented as pathogenic, 9 variants classified as likely pathogenic, and 5 novel variants that have not been reported before. The outcomes indicate that whole-exome sequencing offers great benefits in clinical patient diagnosis, particularly in terms of detecting diagnostic variants. This study underscored the significance of whole exome sequencing (WES) studies, where only a broad gene set is examined in epilepsy patients. This approach has the potential to establish gene-specific phenotypic profiles, particularly by uncovering novel candidate genes in epilepsy patients with well-defined phenotypes. Additionally, conducting validation studies on variants of uncertain clinical significance could enhance the outcome yield. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the demographic data and resolved-relapse rates in clinical follow-up of patients whose antiseizure medications (ASM) were discontinued after a minimum of 2 years of seizure freedom. Methods: The files of 1985 patients followed in the epilepsy outpatient clinic were evaluated retrospectively. The inclusion criteria for patients were between 18 and 65 years old, followed up at an epilepsy outpatient clinic, and having discontinued ASM after at least 2 years of seizure freedom under the supervision of a neurologist. Results: A total of 56 patients were included in the study. The age of onset of seizures was 13.9±10.04 years, the age of onset of ASM was 15.87±9.69 years, and the age of quitting ASM was 24.58±11.54 years. The patients had a mean seizure-free period of 64.46±32.27 months before drug discontinuation and 43.73±38.87 months after drug discontinuation. The EEGs of 49 patients were normal in the EEGs performed after drug discontinuation, and seven patients had epileptiform discharges. Relapse was observed in 23.2% of patients after drug discontinuation. It was observed that 69% of the recurrences in 13 patients occurred within the first 2 months. Conclusion: Although seizure recurrence probability is highest during the first 2 months after ASM discontinuation, it is still possible 6 years later in adults with inactive epilepsy. The time window without seizures before ASM discontinuation and follow-up EEGs afterwards may help in the prediction of seizure recurrence. [ABSTRACT FROM AUTHOR]

Background: Transcranial Magnetic Stimulation–Electroencephalography (TMS-EEG) is a non-operative technique that allows for magnetic cortical stimulation (TMS) and analysis of the electrical currents generated in the brain (EEG). Despite the regular utilization of both techniques independently, little is known about the potential impact of their combination in neurosurgical practice. Methods: This scoping review, conducted following PRISMA guidelines, focused on TMS-EEG in epilepsy, neuro-oncology, and general neurosurgery. A literature search in Embase and Ovid MEDLINE returned 3596 records, which were screened based on predefined inclusion and exclusion criteria. After full-text review, three studies met the inclusion criteria. Two independent investigators conducted study selection and data extraction, with mediators resolving disagreements. The NHLBI tool was used to assess risk of bias in the included studies. Results: A total of 3596 articles were screened following the above-mentioned criteria: two articles and one abstract met the inclusion criteria. TMS-EEG is mentioned as a promising tool to evaluate tumor–brain interaction, improve preoperative speech mapping, and for lateralization epileptic focus in patients undergoing epilepsy surgery. Lack of detailed patient and outcome information preclude further considerations about TMS-EEG use beyond the potential applications of this technique. Conclusions: TMS-EEG research in neurosurgery is required to establish the role of this non-invasive brain stimulation-recording technique. Tumor–brain interaction, preoperative mapping, and seizure lateralization are in the front row for its future applications. [ABSTRACT FROM AUTHOR]

For centuries, epileptic seizures have been noticed to recur with temporal regularity, suggesting that an underlying biological rhythm may play a crucial role in their timing. In this review, we propose to adopt the framework of chronobiology to study the circadian timing of seizures. We first review observations made on seizure timing in patients with epilepsy and animal models of the disorder. We then present the existing chronobiology paradigm to disentangle intertwined circadian and sleep–wake timing mechanisms. In the light of this framework, we review the existing evidence for specific timing mechanisms in specific epilepsy syndromes and highlight that current knowledge is far from sufficient. We propose that individual seizure chronotypes may result from an interplay between independent timing mechanisms. We conclude with a research agenda to help solve the urgency of ticking seizures. [ABSTRACT FROM AUTHOR]

Objective: This retrospective cohort study assessed dementia risk in epilepsy patients associated with the compliance to epileptic treatment visits. Methods: We used Taiwanese insurance claims data to establish an epilepsy cohort (N = 39,216) diagnosed in 2000–2015 and a matched control cohort without epilepsy (N = 156,864), evaluating the incident dementia by the end of 2016. Results: The dementia incidence was 2.9-fold higher in the epilepsy cohort than in comparisons (4.68 vs. 1.59 per 1000 person-years). Only 9.3% of epilepsy patients were compliant to ≥80% of scheduled treatment visits, but they exhibited a 7.2-fold higher dementia incidence than those without treatment. The contrast was greater in younger patients than in the elderly (20-fold versus 5.5-fold). Dementia incidence increased with the frequency of neurological consultations, peaking in the first year after epilepsy diagnosis. Conclusions: Epileptic patients with more clinical visits for active treatment had a higher chance of dementia diagnosis, highlighting the importance of close neurological monitoring post-epilepsy diagnosis to address potential dementia complications. [ABSTRACT FROM AUTHOR]

Objective: EEG patterns and quantitative EEG (qEEG) features have been poorly explored in monogenic epilepsies. Herein, we investigate regional differences in EEG frequency composition in patients with STXBP1 developmental and epileptic encephalopathy (STXBP1‐DEE). Methods: We conducted a retrospective study collecting electroclinical data of patients with STXBP1‐DEE and two control groups of patients with DEEs of different etiologies and typically developing individuals matched for age and sex. We performed a (1) visual EEG assessment, (b) qEEG analysis, and (c) electrical source imaging (ESI). We quantified the relative power (RP) of four frequency bands (α β, θ, δ), in two electrode groups (anterior/posterior), and compared their averages and dynamics (standard deviation [SD] over time). The ESI was performed by applying the standard Distributed Source Modeling algorithm. Results: We analyzed 42 EEG studies in 19 patients with STXBP1‐DEE (10 female), with a median age at recordings of 9.6 years (range 9 months to 29 years). The δRP was higher in recordings of STXBP1‐DEE (p <.001) compared to both control groups, suggesting the pathogenicity and STXBP1‐specificity of these findings. In STXBP1‐DEE, the δRP was significantly higher in the anterior electrode group compared to the posterior one (p =.003). There was no correlation between the anterior δRP and the epilepsy focus, age at recordings, and concomitant medications The ESI modeling of this activity showed a widespread involvement of the dorsomesial frontal cortex, suggesting a large corticosubcortical pathologic network. Finally, we identified two groups of recordings: cluster.1 with higher anterior δRP and low dynamics and cluster.2 with lower δRP and higher dynamics. Patients in cluster.1 had a more severe epilepsy and neurological phenotype compared to patients in cluster 2. Significance: The qEEG analysis showed a predominant frontal slow activity as a specific STXBP1 feature that correlates with the severity of the phenotype and may represent a biomarker for prospective longitudinal studies of STXBP1‐DEE. [ABSTRACT FROM AUTHOR]

We studied the distribution of germline and somatic variants in epilepsy surgery patients with (suspected) malformations of cortical development (MCD) who underwent surgery between 2015 and 2020 at University Medical Center Utrecht (the Netherlands) and pooled our data with four previously published cohort studies. Tissue analysis yielded a pathogenic variant in 203 of 663 (31%) combined cases. In 126 of 379 (33%) focal cortical dysplasia (FCD) type II cases and 23 of 37 (62%) hemimegalencephaly cases, a pathogenic variant was identified, mostly involving the mTOR signaling pathway. Pathogenic variants in 10 focal epilepsy genes were found in 48 of 178 (27%) FCDI/mild MCD/mMCD with oligodendroglial hyperplasia and epilepsy cases; 36 of these (75%) were SLC35A2 variants. Six of 69 (9%) patients without a histopathological lesion had a pathogenic variant in SLC35A2 (n = 5) or DEPDC5 (n = 1). A germline variant in blood DNA was confirmed in all cases with a pathogenic variant in tissue, with a variant allele frequency (VAF) of ~50%. In seven of 114 patients (6%) with a somatic variant in tissue, mosaicism in blood was detected. More than half of pathogenic somatic variants had a VAF < 5%. Further analysis of the correlation between genetic variants and surgical outcomes will improve patient counseling and may guide postoperative treatment decisions. [ABSTRACT FROM AUTHOR]

Objective: To determine the optimal duration of electroencephalography (EEG) recording to detect epileptic spasms (ES) based on inpatient overnight video‐EEG monitoring in patients with infantile epileptic spasms syndrome (IESS) at the 2‐week follow‐up. Methods: Patients with IESS and overnight EEG monitoring between January 2020 and June 2022 were retrospectively reviewed. Time‐to‐ES, time‐to‐sleep and time‐to‐epileptic encephalopathy (EE) per the Burden of Amplitudes and Epileptiform Discharges (BASED 2021) score. BASED 2021 score were reported. ES and sleep detection sensitivity were calculated with respect to monitoring time. Etiology, treatment, and EEG features were assessed for strength of association with continued ES. Time‐to‐event analysis was performed with the first ES as the event of interest. Results: Of 90 patients, 39 (43%) continued to have ES; 78.6% with EE continued to have ES, whereas only 27.4% without EE had ES (odds ratio [OR] 12.05). Structural etiologies were also associated with continued ES (OR 5.24). ES detection was 35.9%, 76.9%, and 84.6% at 1, 4, and 6 h, respectively, with corresponding negative likelihood ratios (NLRs) of.64,.23, and.15. ES detection reached >90% and >95% at 14 and 19 h, respectively. Sleep detection was 52.2%, 84.4%, and 95.6% at 1, 4, and 6 h, respectively, and captured in all patients by 11 h. EE was observed by 6 h for all associated patients. Significance: Typical routine EEG durations (<1 h) were not sufficient to detect ES, EE, or sleep in patients with IESS at the 2‐week follow‐up. Four hour outpatient EEG will capture ES in 77% and sleep in 84% of the patients. EE, if present, was shortly after sleep onset. Additional monitoring of up to 19 h was needed to capture >95% of patients with ES. Although EE was strongly associated with continued ES, 27.4% of patients without EE demonstrated ES. This study will help guide adequate duration of EEG monitoring at the 2‐week follow‐up for patients with IESS. [ABSTRACT FROM AUTHOR]