Antiseizure Medication Treatment Research Articles

Predicting efficacy of antiseizure medication treatment with machine learning algorithms in North Indian population

PurposeThis study aimed to develop a classifier using supervised machine learning to effectively assess the impact of clinical, demographical, and biochemical factors in accurately predicting the antiseizure medications (ASMs) treatment response in people with epilepsy (PWE). MethodsData was collected from 786 PWE at the Outpatient Department of Neurology, Institute of Human Behavior and Allied Sciences (IHBAS), New Delhi, India from 2005 to 2015. Patients were followed up at the 2nd, 4th, 8th, and 12th month over the span of 1 year for the drugs being administered and their dosage, the serum drug levels, the frequency of seizure control, drug efficacy, the adverse drug reactions (ADRs), and their compliance to ASMs. Several features, including demographic details, medical history, and auxiliary examinations electroencephalogram (EEG) or Computed Tomography (CT) were chosen to discern between patients with distinct remission outcomes. Remission outcomes were categorized into ‘good responder (GR)’ and ‘poor responder (PR)’ based on the number of seizures experienced by the patients over the study duration. Our dataset was utilized to train seven classical machine learning algorithms i.e Extreme Gradient Boost (XGB), K-Nearest Neighbor (KNN), Support Vector Classifier (SVC), Decision Tree (DT), Random Forest (RF), Naïve Bayes (NB) and Logistic Regression (LR) to construct classification models. ResultsOur research findings indicate that 1) among the seven algorithms examined, XGB and SVC demonstrated superior predictive performances of ASM treatment outcomes with an accuracy of 0.66 each and ROC-AUC scores of 0.67 (XGB) and 0.66 (SVC) in distinguishing between PR and GR patients. 2) The most influential factor in discerning PR to GR patients is a family history of seizures (no), education (literate) and multitherapy with Chi-square (χ2) values of 12.1539, 8.7232 and 13.620 respectively and odds ratio (OR) of 2.2671, 0.4467, and 1.9453 each. 3). Furthermore, our surrogate analysis revealed that the null hypothesis for both XGB and SVC was rejected at a 100 % confidence level, underscoring the significance of their predictive performance. These findings underscore the robustness and reliability of XGB and SVC in our predictive modelling framework. SignificanceUtilizing XG Boost and SVC-based machine learning classifier, we successfully forecasted the likelihood of a patient's response to ASM treatment, categorizing them as either PR or GR, post-completion of standard epilepsy examinations. The classifier’s predictions were found to be statistically significant, suggesting their potential utility in improving treatment strategies, particularly in the personalized selection of ASM regimens for individual epilepsy patients.

The assessment of the impact of antiepileptic drugs on cognitive functions via N-200/P-300 potentials and neuropsychological measures.

The effects of antiseizure medications (ASMs) on cognitive functions have not been fully elucidated. The primary aim of this study was to demonstrate potential changes in cognitive functions in patients diagnosed with epilepsy from both neuropsychological and electrophysiological perspectives. Our secondary objective was to assess the effects of administered ASM on cognitive functions by categorizing patients into different monotherapy and polytherapy groups. A single-center, prospective patient registry study was conducted between May 2022 and June 2023. The inclusion criteria included epilepsy patients aged 18 to 50 years who were receiving ASM) treatment, either as inpatients or outpatients, and who did not have any syndromic diagnosis that may lead to cognitive disfunciton (such as primary progressive myoclonic epilepsies, Down syndrome and so on), and did not diagnosed previously or during examination that could affect dementia or cognitive functions. Patients who were scheduled to initiate new ASM treatment were evaluated using the Montreal Cognitive Assessment (MoCA) scale and Event-Related Potentials (ERP) assessment both before commencing treatment and three months thereafter. A total of 320 participants were included in the study; 20 healthy controls and 300 epilepsy patients were included. Statistically significant differences were observed between the healthy control group and the epilepsy group in terms of average Montreal Cognitive Assessment (MoCA) scores and event-related potentials (ERPs) (n200, p300 latencies, n2p3 amplitudes) (p<0.05). Similarly, statistically significant differences were observed between the monotherapy and polytherapy groups in terms of average MoCA and ERP scores (p<0.05). This study demonstrated the detrimental effects of certain ASMs, particularly topiramate and carbamazepine, on cognitive functions. Furthermore, the negative impact on cognitive performance became more pronounced with an increasing number of concurrently used ASMs (polytherapy), with topiramate showing notable effects.

Physical fitness in Indian women with epilepsy on anti-seizure medications and its association with reproductive status, quality of life and stigma: A cross-sectional study

PurposeTo determine the status of physical fitness, reproductive abnormalities, QOL and epilepsy associated stigma in women with epilepsy (WWE) and their association with ASM therapy and seizure frequency. MethodsThis cross-sectional study included WWE of reproductive age (18–50 years) on antiseizure medications (ASMs) for at least three months before enrolment. Physical fitness was assessed using International Physical Activity Questionnaires (IPAQ) and Body composition analysis. Subjects were interviewed for menstrual abnormalities [menstrual disturbance or Polycystic Ovary Syndrome (PCOS)/hirsutism]. Validated questionnaires were used for assessment of, QOL (QOLIE-10) and Stigma in epilepsy (Epilepsy Stigma Scale). Sub-group analysis was done to compare the above parameters on the basis of a) type of therapy (mono or polytherapy), b) type of ASMs treatment (conventional, newer, or conventional + newer ASMs), and c) seizure type and (d) seizure frequency. Correlation and regression analysis were done to find out the association among different variables with physical fitness. ResultsThe overall prevalence of poor physical fitness, reproductive abnormalities, worsened QOL and stigma in the enrolled WWE (n = 203) were 21.18 %, 20.19 %, 52.7 %, and 21.67 %, respectively. Sub-group analysis revealed that WWE on monotherapy (n = 99) had higher median IPAQ score (p = 0.002), comparatively less reproductive abnormalities (24.03 %, p = 0.008), and higher stigma (24.03 %, p = 0.04) than polytherapy group. WWE on conventional ASMs had significantly higher IPAQ scores compared to newer and conventional + newer ASMs groups (p = 0.02). The prevalence of poor physical fitness and stigma was significantly higher in WWE with higher number of seizures (p = 0.007, <0.001, respectively). No significant difference in QOL was observed on the basis of ASM type and therapy; however, WWE with generalized onset seizures had worsened QOL compared to those with focal onset seizures (p = 0.04). A significant negative correlation was found among seizure frequency and IPAQ score in WWE (p = 0.04). ConclusionWWE on polytherapy were physically less active, higher occurrence of reproductive abnormalities, and stigma compared to the monotherapy group. WWE with higher seizure frequency had poor physical fitness, and higher stigma compared to those with lesser number of seizures. These findings may aid value in optimization of ASM treatment in WWE of reproductive age.

A systematic review and meta-analysis of factors related to first line drugs refractoriness in patients with juvenile myoclonic epilepsy (JME).

Juvenile Myoclonic Epilepsy (JME) is a prevalent form of epileptic disorder, specifically categorized within the realm of Genetic Generalized Epilepsy (GGE). Its hallmark features encompass unprovoked bilateral myoclonus and tonic-clonic seizures that manifest during adolescence. While most JME patients respond favorably to anti-seizure medication (ASM), a subset experiences refractory JME, a condition where seizures persist despite rigorous ASM treatment, often termed "Drug-Resistant Epilepsy" (DRE). This systematic review and meta-analysis aims to determine the prevalence of refractory JME, and further to identify socio-demographic, electrophysiological and clinical risk factors associated with its occurrence. Pinpointing these factors is crucial as it offers the potential to predict ASM responsiveness, enabling early interventions and tailored care strategies for patients. The systematic review and meta-analysis followed the Cochrane Handbook and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The study evaluated outcomes post ASM treatment in JME cohorts by searching papers published up to September 2023 in PubMed/MEDLINE, Scopus, and Google Scholar databases. Predefined inclusion criteria were met by 25 eligible studies, forming the basis for analysis. A total of 22 potential risk factors for refractory JME were documented. Notably, robust risk factors for treatment resistance included Psychiatric Disorder (Odds Ratio (OR), 3.42 [2.54, 4.61] (95% Confidence Inverval (Cl)), Febrile Seizures (OR, 1.83 [1.14, 2.96] (95% Cl)), Alcohol Consumption (OR, 16.86 [1.94, 146.88] (95%Cl)), Aura (OR, 2.15 [1.04, 4.47] (95%Cl)), childhood absence epilepsy (CAE) evolving into JME (OR, 4.54 [1.61, 12.78] (95%CI)), occurrence of three seizure types (OR, 2.96 [1.96, 4.46] (95%CI)), and Focal EEG abnormalities (OR, 1.85 [1.13, 3.01] (95%Cl)). In addition, there were some non-significant risk factors for DRE because of noticeable heterogeneity. In aggregate, over 36% of JME patients demonstrated drug resistance, with seven significant risk factors closely linked to this refractoriness. The interplay between these factors and whether they denote treatment non-response or heightened disease burden remains an open question and more studies would be required to fully examine their influence.

Antiseizure Medication Treatment Patterns, Reasons for Disruption, and Side Effects for Patients with Dravet Syndrome or Lennox-Gastaut Syndrome: A Retrospective Analysis of US Physician Notes (P2-1.006)

Antiseizure Medication Treatment Patterns, Reasons for Disruption, and Side Effects for Patients with Dravet Syndrome or Lennox-Gastaut Syndrome: A Retrospective Analysis of US Physician Notes (P2-1.006)

Antiseizure Medications Normalize Electroencephalographic Functional Connectivity and Power in Children With Benign Epilepsy With Centrotemporal Spikes

BackgroundThe decision to treat children with benign epilepsy with centrotemporal spikes (BECTS) using antiseizure medications (ASM) is controversial. Our goal is to compare the effect of ASM treatment on the alteration of electroencephalographic (EEG) functional connectivity and power across four frequency bands in children with BECTS. MethodsChildren with BECTS with two-year follow-up were retrospectively divided into ASM versus non-ASM groups. The network properties of the EEGs as based on network-based statistic and graph theory were evaluated by the following indices: global efficiency, clustering coefficient, betweenness centrality, and nodal strength in four frequency bands (delta, theta, alpha, and beta). EEG power including absolute power (AP) and relative power (RP) was analyzed in four frequency bands. ResultsIn children with BECTS with ASM treatment, there was no significant change in EEG connectivity across all bands before and after two years of ASM. In children with BECTS without ASM treatment, there was a significant increase of global efficiency, clustering coefficient, and nodal strength but not the betweenness centrality in the delta band after two years of follow-up. A decrease in AP in the delta and theta bands and a decrease in RP in the theta band were found in the ASM group after two years of treatment. ConclusionsOur results suggest that ASM may play a role in modulating the development of increasing overall brain connectivity and in downregulating overt synaptic activity, but not intrinsic focal connectivity, in the early years of BECTS. The changes in the EEG power indicate that ASM significantly normalized slow-wave band power.

Epilepsy and pregnancy

Regarding treatment of women of childbearing potential with epilepsy, several aspects of family planning and desire to have children have to be taken into account. Overview of current data on mutual implications of epileptic seizures, antiseizure medication (ASM), pregnancy and child development. Review of the current literature, discussion and presentation of resulting treatment recommendations. Many ASMs bear the potential for clinically relevant interactions with both contraceptives and altered concentrations of sexual hormones and modified pharmacokinetics during pregnancy. All ASMs show an increased risk for congenital malformations; however, due to seizure-related risks for the mother and child effective ASM treatment during pregnancy is crucial. When considering the special aspects of consultation and treatment of women of childbearing potential with epilepsy most pregnancies are uncomplicated.

Greater need for treatment optimization in patients with epilepsy initiating adjunctive therapy: Results of a retrospective claims analysis of antiseizure medication drug load in the United States

BackgroundThis retrospective, observational study used US claims data to assess changes in antiseizure medication (ASM) drug load for a cohort of patients with epilepsy. MethodsAdults (≥18 years) with a diagnosis of epilepsy (ICD-10 code G40.xxx) who started new adjunctive ASM treatment with one of 4 branded (brivaracetam, eslicarbazepine, lacosamide, perampanel) or 4 unbranded (carbamazepine, lamotrigine, levetiracetam, topiramate) ASMs between January 1, 2016 and December 31, 2020 were identified from IBM MarketScan® research databases (primary study population). Patients must have been continuously enrolled 360 days before the start of the new ASM (eligibility period). Follow-up was from the start of new ASM until Day 540 (∼18 months). The primary endpoint was concomitant ASM drug load, which included all ASMs except the new (comparator) ASM. A sensitivity analysis population included adults with epilepsy who were continuously enrolled for ≥ 180 days during at least one calendar year in the study period (2016–2020), whether or not the comparator ASM was new or existing during that period. Total ASM drug load, which included comparator ASM and concomitant ASMs, was assessed in the sensitivity analysis population. ResultsIn total, 21,332 patients were included in the primary study population, of which 5767 initiated branded ASMs and 15,565 initiated unbranded ASMs. A total of 392,426 patients were included in the sensitivity analysis population during at least one calendar year 2016–2020. Concomitant ASM drug load increased in the 360 days prior to new ASM start and slightly declined thereafter. Mean concomitant ASM drug load for the primary population was 1.6 (SD 1.8) at new ASM start. Concomitant drug load was higher among those starting branded ASM comparators compared to those starting unbranded comparators. Mean total ASM drug load for patients increased over time and was approximately double for patients exposed to branded ASMs (mean range 2.1 to 2.7) compared to that of patients exposed to any unbranded ASM (mean range 1.0 to 1.3). ConclusionConcomitant ASM drug load increased prior to addition of new ASM, with higher increases observed among patients starting branded vs unbranded ASMs, followed by slight decreases thereafter. Total drug load increased linearly among all patients. These findings underscore the need for ongoing ASM regimen evaluation and treatment optimization in patients with epilepsy.

Guidelines and epilepsy practice: Antiseizure medication initiation following an unprovoked first seizure in adults

ObjectivesAdherence rate to evidence-based clinical practice guidelines is relatively low and the impact of guidelines on clinical practice in epilepsy is variable. The 2015 practice guideline on the management of an unprovoked first seizure in adults specifies clinical variables associated with increased risk of seizure recurrence and the impact of immediate antiseizure medication (ASM) treatment on seizure outcome.We aimed to evaluate the impact of the evidence-based guideline for the management of an unprovoked first seizure in adults on clinical practice in our adult neurology department. MethodsWe retrospectively reviewed the computerized database of 169 adult patients admitted to the adult neurology department at Shamir-Assaf Harofeh Medical Center following a first unprovoked seizure between October 2011 and October 2018. ResultsASMs were initiated in 86% of patients with a first unprovoked seizure pre- and in all patients admitted post- guideline publication. Monotherapy and use of old generation ASMs were more common in both groups and a combination of old- and new generation ASMs - among the pre-guideline group. The pre-guideline decision to initiate ASM treatment was significantly influenced only by epileptiform discharges in the electroencephalogram (EEG). DiscussionThis is the first study to evaluate the impact of the 2015 practice guideline on the initiation of ASM treatment after a first unprovoked seizure in adults. Further studies are needed to assess the global contribution of the guideline to clinical practice and its impact on patient outcomes.

Variation in seizure risk increases from antiseizure medication withdrawal among patients with well-controlled epilepsy: A pooled analysis.

Guidelines suggest considering antiseizure medication (ASM) discontinuation in seizure-free patients with epilepsy. Past work has poorly explored how discontinuation effects vary between patients. We evaluated (1) what factors modify the influence of discontinuation on seizure risk; and (2) the range of seizure risk increase due to discontinuation across low- versus high-risk patients. We pooled three datasets including seizure-free patients who did and did not discontinue ASMs. We conducted time-to-first-seizure analyses. First, we evaluated what individual patient factors modified the relative effect of ASM discontinuation on seizure risk via interaction terms. Then, we assessed the distribution of 2-year risk increase as predicted by our adjusted logistic regressions. We included 1626 patients, of whom 678 (42%) planned to discontinue all ASMs. The mean predicted 2-year seizure risk was 43% [95% confidence interval (CI) 39%-46%] for discontinuation versus 21% (95% CI 19%-24%) for continuation. The mean 2-year absolute seizure risk increase was 21% (95% CI 18%-26%). No individual interaction term was significant after correcting for multiple comparisons. The median [interquartile range (IQR)] risk increase across patients was 19% (IQR 14%-24%; range 7%-37%). Results were unchanged when restricting analyses to only the two RCTs. No single patient factor significantly modified the influence of discontinuation on seizure risk, although we captured how absolute risk increases change for patients that are at low versus high risk. Patients should likely continue ASMs if even a 7% 2-year increase in the chance of any more seizures would be too much and should likely discontinue ASMs if even a 37% risk increase would be too little. In between these extremes, individualized risk calculation and a careful understanding of patient preferences are critical. Future work will further develop a two-armed individualized seizure risk calculator and contextualize seizure risk thresholds below which to consider discontinuation. Understanding how much antiseizure medications (ASMs) decrease seizure risk is an important part of determining which patients with epilepsy should be treated, especially for patients who have not had a seizure in a while. We found that there was a wide range in the amount that ASM discontinuation increases seizure risk-between 7% and 37%. We found that no single patient factor modified that amount. Understanding what a patient's seizure risk might be if they discontinued versus continued ASM treatment is critical to making informed decisions about whether the benefit of treatment outweighs the downsides.

Predicting Antiseizure Medication Treatment in Children with Rare Tuberous Sclerosis Complex-Related Epilepsy Using Deep Learning.

Tuberous sclerosis complex disease is a rare, multisystem genetic disease, but appropriate drug treatment allows many pediatric patients to have positive outcomes. The purpose of this study was to predict the effectiveness of antiseizure medication treatment in children with tuberous sclerosis complex-related epilepsy. We conducted a retrospective study involving 300 children with tuberous sclerosis complex-related epilepsy. The study included the analysis of clinical data and T2WI and FLAIR images. The clinical data consisted of sex, age of onset, age at imaging, infantile spasms, and antiseizure medication numbers. To forecast antiseizure medication treatment, we developed a multitechnique deep learning method called WAE-Net. This method used multicontrast MR imaging and clinical data. The T2WI and FLAIR images were combined as FLAIR3 to enhance the contrast between tuberous sclerosis complex lesions and normal brain tissues. We trained a clinical data-based model using a fully connected network with the above-mentioned variables. After that, a weighted-average ensemble network built from the ResNet3D architecture was created as the final model. The experiments had shown that age of onset, age at imaging, infantile spasms, and antiseizure medication numbers were significantly different between the 2 drug-treatment outcomes (P < .05). The hybrid technique of FLAIR3 could accurately localize tuberous sclerosis complex lesions, and the proposed method achieved the best performance (area under the curve = 0.908 and accuracy of 0.847) in the testing cohort among the compared methods. The proposed method could predict antiseizure medication treatment of children with rare tuberous sclerosis complex-related epilepsy and could be a strong baseline for future studies.

CNSC-24. NEURONAL ACTIVITY PROMOTES GLIOMA PROGRESSION THROUGH INDUCING RNA M6A DEMETHYLATION AND PRONEURAL-TO-MESENCHYMAL TRANSITION IN GLIOMA STEM CELLS

Abstract High-grade gliomas are lethal brain cancers whose progression is highly driven by neuronal activity. The glioma stem cell (GSC) subpopulation has been identified in glioblastoma and plays a significant role in the resistance of glioma to conventional therapies as well as cancer recurrence. Activity-regulated release of growth factors and electrical synaptic integration promotes glioma growth; however, it is unclear whether neuronal activity plays a role in the mRNA N6-methyladenosine (m6A) level changes in patient glioma tissue. By using chemogenetics techniques, we enhanced and inhibited neuronal activity in vitro and in vivo, and studied how neuronal activity regulates GSC behaviors. Here, we identified that neuronal activity promotes glioma progression and radioresistance through neuronal exosome-induced proneural-to-mesenchymal transition (PMT) of GSCs. We revealed that neuronal activity upregulates critical microRNA expression in NDEs (neuro-derived exosomes) and subsequently induces PMT by activating the STAT3 pathway. Chemogenetically activating cortical neurons increases the growth of GSC xenografts in situ. Conversely, reducing neuronal activity inhibited the GSC xenograft growth. Anti-seizure medication treatment suppresses GSC PMT and sensitizes GSCs to radiotherapy in vitro and in vivo. Together, these findings indicate that exosomes of active neurons can promote glioma progression and radioresistance by inducing GSC PMT via neuro-derived extracellular vesicles

Real-world antiseizure medication treatment outcomes in drug-resistant focal epilepsy patients.

To gather real-world evidence on antiseizure medications (ASMs) treatment patterns and related outcomes in patients with drug-resistant focal epilepsy. Medical insurance claims from the start of 2014 till the end of 2019 were used. Patient selection criteria included International Classification of Diseases (ICD) codes followed by documented ASM use. Baseline patient demographics along with ASM and rescue medication use patterns and related patient outcome were documented for first (index) ASM regimen. Patients who failed the first regimen and then failed the second regimen were considered drug resistant. Multivariate analyses were performed to identify risks and other characteristics for positive or negative treatment outcomes. Study cohort consisted of 46 474 patients with a mean age of 47.23 (SD: 16.94). Levetiracetam was the most first-encountered ASM (37.94%). At baseline, 87.14% were treated with ASMs prior to having study-confirmed diagnoses. Mental comorbidities were present in 37.86% of patients. After first-year ASM treatment, 34.61% of patients persisted on their index regimen and 5.91% were seizure-free. Patients failing first ASM regimen numbered 12 868 (27.69%). Drug-resistant patients who failed first and then second ASM regimens numbered 6335 (49.23%). Percentages of patients who had successful second treatment and seizure-free were 21.32 and 3.65, respectively. Initiating patients on lamotrigine or carbamazepine (relative to levetiracetam), baseline use of index ASM, rescue medications, and older age or male gender all lowered the risk for treatment failure. Having higher comorbidity, comorbid mental illness, headache, or neoplasty increased such a risk. Baseline use of index ASM, depressive episode, or anxiety disorder all entailed higher risk of failing second ASM treatment. Overall, reported findings indicated that patient history at baseline and the early selection of an ASM all influenced treatment outcomes. Findings pointed to the complex nature of ASM treatment in drug-resistant focal epilepsy patients calling for additional research to identify the optimal treatment to achieve beneficial patient outcomes.

P09.01.A IMPACT OF TIMING OF ANTISEIZURE MEDICATION WITHDRAWAL ON SEIZURE RECURRENCE IN GLIOMA PATIENTS: A RETROSPECTIVE OBSERVATIONAL STUDY

Abstract BACKGROUND Withdrawal of antiseizure medication treatment (ASM) can be considered after completion of antitumour treatment in glioma patients who no longer suffer from seizures. We compared the risk of recurrent seizures after ASM withdrawal between patients with short-term, medium-term versus long-term seizure freedom after antitumour treatment. MATERIAL AND METHODS In this retrospective observational study, the primary outcome was time to recurrent seizure, from the starting date of no ASM treatment up to 36 months follow-up. Cox proportional hazards models were used to study the effect of risk factors on time to recurrent seizure. Stratification was done with information known at baseline. Short-term seizure freedom was defined as ≥3 months, but &amp;lt;12 months; medium-term as 12-24 months; and long-term as ≥24 months seizure freedom from the date of last antitumour treatment. RESULTS This study comprised of 109 patients; 31% (34/109) were in the short-term, 29% (32/109) in the medium-term, and 39% (43/109) in the long-term group. A recurrent seizure was experienced by 44% (15/34) of the patients in the short-term, 31% (10/32) in the medium-term, and 44% (19/43) in the long-term group. Seizure recurrence risk was similar between patients in the short-term group as compared to the medium-term (cause-specific adjusted hazard ratio [aHR]=0.65 [95%CI=0.29-1.46]) and long-term group (cause-specific aHR=1.04 [95%CI=0.52-2.09]). CONCLUSION Seizure recurrence risk is relatively similar between patients with short-term, medium-term, and long-term seizure freedom after completion of antitumour treatment.

Functional and structural networks decoupling in generalized tonic-clonic seizures and its reorganization by drugs.

To investigate potential functional and structural large-scale network disturbances in untreated patients with generalized tonic-clonic seizures (GTCS) and the effects of antiseizure drugs. In this study, 41 patients with GTCS, comprising 21 untreated patients and 20 patients who received antiseizure medications (ASMs), and 29 healthy controls were recruited to construct large-scale brain networks based on resting-state functional magnetic resonance imaging and diffusion tensor imaging. Structural and functional connectivity and network-level weighted correlation probability (NWCP) were further investigated to identify network features that corresponded to response to ASMs. Untreated patients showed more extensive enhancement of functional and structural connections than controls. Specifically, we observed abnormally enhanced connections between the default mode network (DMN) and the frontal-parietal network. In addition, treated patients showed similar functional connection strength to that of the control group. However, all patients exhibited similar structural network alterations. Moreover, the NWCP value was lower for connections within the DMN and between the DMN and other networks in the untreated patients; receiving ASMs could reverse this pattern. Our study identified alterations in structural and functional connectivity in patients with GTCS. The influence of ASMs may be more noticeable within the functional network; moreover, abnormalities in both the functional and structural coupling state may be improved by ASM treatment. Therefore, the coupling state of structural and functional connectivity may be used as an indicator of the efficacy of ASMs.

Point-of-care electroencephalography enables rapid evaluation and management of non-convulsive seizures and status epilepticus in the emergency department.

To describe our institutional experience with point-of-care electroencephalography (pocEEG) and its impact on the evaluation/management of suspected non-convulsive seizures in the emergency department (ED). We retrospectively identified 157 adults who underwent pocEEG monitoring in our community hospital ED in 1 year. We calculated the time to obtain pocEEG in the ED (door-to-EEG time) and examined the impact of pocEEG findings (categorized as seizure, highly epileptiform patterns, slowing, or normal activity) on antiseizure medication treatment. PocEEG revealed seizures (14%, n=22), highly epileptiform patterns (22%, n=34), slowing (44%, n=69), and normal activity (20%, n=32). The median door-to-EEG time (from initial ED evaluation to pocEEG monitoring) was only 1.2hours (interquartile range 0.1-2.1) even though 55% of studies were performed after-hours (5 pm-9 am). Most patients were admitted (54% to the intensive care unit, 41% to floor). Antiseizure medication treatment occurred pre-pocEEG in 93 patients (59%) and post-pocEEG in 88 patients (56%). By reviewing the relationship between pocEEG monitoring and antiseizure medication management, we found a significant association between pocEEG findings and changes in management(P<0.001). Treatment escalation occurred more frequently in patients with epileptiform activity (seizures or highly epileptiform patterns, 52%) than patients with non-epileptiform activity (normal or slow, 25%, P<0.001), and avoidance of treatment escalation occurred more frequently in patients with normal or slow activity (27%) than patients with seizures or highly epileptiform patterns (2%, P<0.001). Our study, the largest to date describing the real-world use of pocEEG in emergency medicine, found that rapid EEG acquisition in the ED was feasible in a community hospital and significantly affected the management of suspected non-convulsive seizures.

Idiopathic generalized epilepsies: Which seizure type is more difficult to control?

ObjectivesThe purpose of the current study was to investigate that which seizure type is more difficult to be brought under control with antiseizure medication treatment in patients with idiopathic generalized epilepsy (IGE). MethodsThis was a retrospective study of a large database of patients with epilepsy, which was built over more than a decade. All patients with a diagnosis of IGE, with at least 12 months of follow-up at our center, were studied at the epilepsy center at Shiraz University of Medical Sciences, Shiraz, Iran, from 2008 until 2022. Results358 patients were included. The seizure types were generalized tonic-clonic seizures (GTCSs) (in 87.2%), myoclonic seizures (in 57.5%), and absence seizures (in 51.7%). Among patients who had GTCSs (N = 312), 160 patients (51.3%) became free of this seizure type. Among patients who had myoclonic seizures (N = 206), 122 patients (59.2%) became seizure-free. Among patients who had absences (N = 185), 127 patients (68.6%) became seizure-free. The difference between the groups was significant (p = 0.0007). Receiving valproate was significantly associated with a myoclonus-free status (compared with other drugs). SignificanceThe likelihood of achieving seizure control is different for various seizure types in patients with IGE (achievement of seizure control is less likely for GTCSs and more likely for absences). Antiseizure drug efficacy should be considered along with other variables (e.g., sex) when selecting an ASM for a patient with IGE. Specifically designed clinical trials are needed to develop more efficacious and safe drugs to treat various syndromes of IGE.

Risk of Recurrence in Patients with an Unprovoked Tonic-Clonic Seizure and Generalized Epileptiform Discharges on EEG.

The decision to initiate treatment in patients with a first unprovoked seizure remains controversial. Studies have reported a recurrence rate ranging from 21-50%, but most have included patients with different etiologies, EEG findings, and seizure types. This study aimed to determine the risk of recurrence in patients with a first unprovoked generalized tonic-clonic (GTC) seizure with evidence of generalized spike-wave discharges (GSWD) on EEG and compare the efficacy of antiseizure medications (ASM) in preventing recurrence. This prospective study included consecutive patients who presented with a single GTC seizure, evidence of GSWD on EEG, and a follow-up period of at least one year. All patients underwent extensive evaluation, including a 3-hour sleep-deprived video-EEG recording and an epilepsy protocol brain MRI. Treatment with ASM was recommended for all patients. The decision regarding the specific ASM to be used was left to the treating physician's discretion. A total of 57 patients with a median age of 19 years were included. A total of 41 patients agreed to be started on an ASM while 16 declined. Seizure recurred in 6/41 (14.6%) patients in the treated group compared to 11/16 (68.8%) in the untreated group (P = 0.00006). Valproate was significantly more efficacious than levetiracetam or lamotrigine (P = 0.04). Of the 15 patients who discontinued ASM treatment after remaining seizure free for an average of 30 months, 6 (40%) experienced a seizure recurrence. Patients with a first unprovoked GTC seizure and evidence of GSWD on EEG have a high risk of recurrence if left untreated. Valproate is the most efficacious ASD for preventing recurrence in this population. A sizeable proportion of patients can be successfully tapered off medication after a period of seizure freedom. This study provides valuable information for guiding treatment decisions in this patient population.

Changes in seizure frequency and anti-seizure medication therapy during pregnancy and one year postpregnancy

Seizure control in women with epilepsy (WWE) during pregnancy is a vital concern. The aim of this study was to compare changes in seizure frequency and anti-seizure medication (ASM ) therapy in WWE in a real-world setting over three epochs (prepregnancy, pregnancy, and postpregnancy). We screened WWE who were pregnant between 1 January 2010 and 31 December 2020 from the epilepsy follow-up registry database of a tertiary hospital in China. We reviewed and collected follow-up data for the following time periods: 12 months before pregnancy (epoch 1), throughout pregnancy and the first 6 weeks postpartum (epoch 2), and from 6 weeks to 12 months postpartum (epoch 3). Seizures were classified into two categories: tonic‒clonic/focal to bilateral tonic‒clonic seizures and non-tonic‒clonic seizures. The main indicator was the seizure-free rate over the three epochs. Using epoch 1 as a reference, we also compared the percentage of women with an increased seizure frequency, as well as changes in ASM treatment, in epochs 2 and 3. Ultimately, 271 eligible pregnancies in 249 women were included. The seizure-free rates in epoch 1, epoch 2, and epoch 3 were 38.4%, 34.7%, and 43.9%, respectively (P = 0.09). The top three ASMs used in the three epochs were lamotrigine, levetiracetam, and oxcarbazepine. Using epoch 1 as a reference, the percentages of women with increased frequencies of tonic‒clonic/focal to bilateral tonic‒clonic seizures in epoch 2 and epoch 3 were 17.0% and 14.8%, respectively, while the percentages of women with an increased frequency of non-tonic‒clonic seizures in epoch 2 and epoch 3 were 31.0% and 21.8% (P = 0.02). The percentage of women whose ASM dosages were increased in epoch 2 was higher than that in epoch 3 (35.8% vs. 27.3%, P = 0.03). The seizure frequency during pregnancy may not differ significantly from that during prepregnancy and postpregnancy if WWE are treated according to the guidelines.

Video-EEG-monitoring to guide antiseizure medication withdrawal

BackgroundDiscontinuing anti-seizure medication (ASM) should be considered in persons with epilepsy with long-term seizure freedom. Clinicians should also pursue ASM withdrawal in persons with one-time seizures without increased recurrence risk and those with suspected non-epileptic events. However, ASM withdrawal is associated with the risk of recurring seizures. Monitored ASM withdrawal in an epilepsy monitoring unit (EMU) could help better evaluate the risk of seizure recurrence. Here, we investigate the practice of EMU-guided ASM withdrawal, assess its indications, and aim to determine positive and negative predictors for successful withdrawal.MethodsWe screened the medical records of all patients admitted to our EMU between November 1, 2019, and October 31, 2021, and included patients of at least 18 years admitted with the aim of permanent ASM withdrawal. We defined four groups of withdrawal indications: (1) long-term seizure freedom; (2) suspected non-epileptic events; (3) history of epileptic seizures but not fulfilling diagnostic criteria of epilepsy; and (4) seizure-freedom after epilepsy surgery. Successful withdrawal was defined according to the following criteria: no recoding of (sub)clinical seizure activity during VEM (groups 1, 2, and 3), patients did not meet the International League Against Epilepsy (ILAE) definition of epilepsy (groups 2 and 3) [14], and patients were discharged without ongoing ASM treatment (all groups). We also evaluated the prediction model by Lamberink et al. (LPM) for the risk of seizure recurrence in groups 1 and 3.Results55/651 (8.6%) patients fulfilled the inclusion criteria. Withdrawal indications were distributed as follows; group 1: 2/55 (3.6%); group 2: 44/55 (80%); group 3: 9/55 (16,4%); group 4: 0/55. Overall, ASM withdrawal was successful in 90.9%. The sensitivity of the LPM for a 2-year 50% relapse risk threshold was 75%, the specificity 33.3%; for a 5-year relapse risk respectively 12.5% and 33.3%, suggesting that the model is not suitable for risk assessment in patients with one-time seizures or acute-symptomatic seizures, who constituted most of the evaluated patients.ConclusionsOur study suggests that EMU-guided ASM withdrawal could be a helpful tool to support clinical decision-making and improve patient safety. Prospective, randomized trials should further evaluate this method in the future.