Uncommon cause of chest pain: Case report of esophageal foreign body diagnosed by chest computed tomography scan.

A 44-year-old man with a history of epilepsy presented with mild, persistent chest pain lasting 3 days, despite normal cardiac evaluations. A chest computed tomography scan revealed 3 artificial dental prostheses lodged in his esophagus, which the patient had inadvertently swallowed during a recent seizure. Endoscopic removal of the foreign bodies resolved his chest pain without complications. This case emphasizes the importance of considering esophageal foreign bodies as a differential diagnosis for persistent chest pain, particularly in patients with neurological conditions, and highlights the role of early imaging for accurate diagnosis and timely intervention.

Novel ML-Based Algorithm for Detecting Seizures from Single-Channel EEG.

There is a need for seizure classification based on EEG signals that can be implemented with a portable device for in-home continuous minoring of epilepsy. In this study, we developed a novel machine learning algorithm for seizure detection suitable for wearable systems. Extreme gradient boosting (XGBoost) was implemented to classify seizures from single-channel EEG obtained from an open-source CHB-MIT database. The results of classifying 1-s EEG segments are shown to be sufficient to obtain the information needed for seizure detection and achieve a high seizure sensitivity of up to 89% with low computational cost. This algorithm can be impeded in single-channel EEG systems that use in- or around-the-ear electrodes for continuous seizure monitoring at home.

Diphenhydramine Overdose: A Case Report and Topic Review of Prehospital Diagnosis and Treatment.

Diphenhydramine (DPH), a readily available first-generation H1 receptor antihistamine, can have severe consequences when taken in excessive amounts and can lead to grave outcomes such as seizures, dysrhythmias, coma, and death. Recognizing the early signs and symptoms of DPH toxicity is crucial. Fortunately, fatal adult cases of DPH overdose are rare. This report describes a near-fatal overdose of a young adult female who experienced recurrent seizures, respiratory failure, and cardiac arrest with the return of spontaneous circulation (ROSC) in the prehospital setting and complete functional recovery. This case underscores the urgency of addressing DPH toxicity and the utility of reversal agents, such as sodium bicarbonate, in sodium channel blockade.

Interprofessional Team Training With Virtual Reality: Acceptance, Learning Outcome, and Feasibility Evaluation Study.

Background: Effective interprofessional teamwork is vital for ensuring high-quality patient care, especially in emergency medicine. However, interprofessional education often fails to facilitate meaningful interaction among health care disciplines. It is therefore imperative to afford early opportunities for cultivating interprofessional teamwork skills. While in-person simulation-based training has been shown to improve performance, this is resource-intensive, especially if it involves multiple professions. Virtual reality (VR)-based training is an innovative instructional approach that demands fewer resources and offers the flexibility of location-independent learning. Objective: This study aimed to develop and evaluate the acceptance, learning outcome, and feasibility of an interprofessional team (INTEAM) training course that included a VR simulation of a neurological emergency case. Methods: This 1-group study used a pre- and posttest design to evaluate the 2-hour INTEAM training course for nursing and medical students. The course included an e-learning part, VR simulation, and debriefing. The main learning objectives were derived from the entrustable professional activity 6, namely to handle a common problem in emergency medicine (headache due to subarachnoid hemorrhage and epileptic seizure) that requires interprofessional collaboration, including a structured handover. We used validated and self-constructed questionnaires, pre- and posttests, and open questions to assess the acceptance, learning outcome, and feasibility of the course. Results: The data of 42 students (21 nursing and 21 medical students) were analyzed and showed good usability in the System Usability Scale (median 72.5, IQR 65-80). The perception of usefulness (median 6, IQR 5.8-6.9) and ease of use (median 5.9, IQR 5.1-6.3) was good among all students. There was a significant increase in the handover performance from pre- (median 8, IQR 6-9) to posttraining (median 8, IQR 7-9; z=-2.01; P=.045; r=0.33) and of the confidence in caring for patients with seizures (median 3, IQR 2-3 and median 3.5, IQR 3-4, respectively; z=-3.8; P<.001; r=0.60). In 67% (14/21) of the simulations, technical issues occurred, but all simulations could be carried out completely. Conclusions: The new INTEAM training course was well received by nursing and medical students. The handover skills and confidence in caring for patients with seizures were improved after the course. Despite technical challenges with the VR simulations, none required termination, and this demonstrates that our approach is feasible. These promising results encourage the use of VR simulations for team training in the education of nursing and medical students.

TATPat based explainable EEG model for neonatal seizure detection.

The most cost-effective data collection method is electroencephalography (EEG) to obtain meaningful information about the brain. Therefore, EEG signal processing is very important for neuroscience and machine learning (ML). The primary objective of this research is to detect neonatal seizures and explain these seizures using the new version of Directed Lobish. This research uses a publicly available neonatal EEG signal dataset to get comparative results. In order to classify these EEG signals, an explainable feature engineering (EFE) model has been proposed. In this EFE model, there are four essential phases and these phases: (i) automaton and transformer-based feature extraction, (ii) feature selection deploying cumulative weight-based neighborhood component analysis (CWNCA), (iii) the Directed Lobish (DLob) and Causal Connectome Theory (CCT)-based explainable result generation and (iv) classification deploying t algorithm-based support vector machine (tSVM). In the first phase, we have used a channel transformer to get channel numbers and these values have been divided into three levels and these levels are named (1) high, (2) medium and (3) low. By utilizing these levels, we have created an automaton and this automaton has three nodes (each node defines each level). In the feature extraction phase, transition tables of these nodes has been extracted. Therefore, the proposed feature extraction function is termed Triple Nodes Automaton-based Transition table Pattern (TATPat). The used EEG signal dataset contains 19 channels and there are 9 (= 32) connection in the defined automaton. Thus, the presented TATPat extracts 3249 (= 19 × 19 × 9) features from each EEG segment. To choose the most informative features of these 3249 features, a new feature selector which is CWNCA has been applied. By cooperating findings of this feature selector and the presented DLob, the explainable results have been obtained. The last phase is the classification phase and to get high classification performance from this phase, an ensemble classifier (tSVM) has been presented and the classification results have been obtained using two validation techniques which are 10-fold cross-validation (CV) and leave-one subject-out (LOSO) CV. The proposed EFE model generates a DLob string and by using this string, the explainable results have been obtained. Moreover, the presented EFE model attained 99.15% and 76.37% classification accuracy deploying 10-fold and LOSO CVs respectively. According to the classification performances, the recommended TATPat-based EFE is a good model at EEG signal classification. Also, the presented TATPat-based EFE model is a good model for explainable artificial intelligence (XAI) since TTPat-based EFE is cooperating by the DLob.

Sudden unexpected atraumatic arterial dissection-related death after seizures.

BACKGROUND: To date, it has been assumed that acute seizures which arise in the context of sudden, spontaneous, atraumatic, acute, arterial dissections (SAAADs) are downstream consequences of the dissections driven by syncope or focal brain lesions (FBLs). As this subject has not been formally investigated, likely due to its rarity, we reviewed published case reports (CRs) to examine the veracity of this assumption. METHODS: We included CR describing patients diagnosed with both acute seizures and arterial dissections in order to ascertain the temporal sequence between acute seizures and typical SAAAD symptoms. In addition, we quantified the frequency with which hypotension, bradycardia, and FBLs are associated with acute seizures in such cases. RESULTS: We found 45 published CRs, six (13.3%) of which involved traumatic arterial dissections and 39 (86.7%) which involved SAAADs. Of the latter, twenty-one (53.8%) described seizures that followed typical SAAAD symptoms (SAFO), and 18 (46.2%) that preceded all such symptoms (SATO). On average, blood pressure and heart rate for both groups exceeded the normal range. Of the CRs that included magnetic resonance imaging (MRI) scans, 8 (100%) SAFO but only 6 (54.5%) SATO patients demonstrated FBLs (p<0.03). A conspicuously large fraction of SATO patients had known epilepsy compared with SAFO patients, (33.3% vs 4.8%; p<0.02). In addition, SATO epilepsy patients' seizure semiologies frequently resembled their breakthrough seizures (BTS). The most common SAAAD associated with acute seizures was aortic dissection (AoD; 17/45; 37.8%). Nine CRs (20%) described patients who died soon after presentation, seven of which were associated with AoDs, including one epilepsy patient. Six of these seven AoDs occurred in patients who suffered from chronic hypertension (CHTN). All five deaths in the SATO group followed first ever seizures (FES) [four AoDs and one coronary artery dissection (CoAD)]. CONCLUSION: Acute seizures arising in the context of SAAADs are not necessarily associated with hypotension or FBLs, and frequently appear to precede the associated dissections. These results suggest that seizures could act as triggers for SAAADs. In addition, sudden unexpected atraumatic acute arterial dissection-related death after seizure (SUADAS) might be a distinct cause of sudden death in epilepsy patients.

An advocacy based cross sectional study of healthcare professionals of factors impacting on medication adherence across nine Sub-Saharan African countries.

BACKGROUND: Adherence to anti-seizure medication (ASM) by people diagnosed with epilepsy in sub-Saharan Africa remains low. The factors for low adherence are not well understood. To improve adherence, it is important to understand the perceptions and views of healthcare professionals delivering epilepsy care to this population. The aim was to investigate the factors influencing ASM adherence. METHODS: This study uses a brief online questionnaire which asked healthcare professionals (both from nursing and medical backgrounds) who work in sub-Saharan African countries to rate a set of pre-established options designed with the feedback of a local focus group of epilepsy experts from countries targeted. The questionnaire consisted of six questions and was a mix of multiple choice and Likert scale questions. RESULTS: There were 217 healthcare professionals who replied to the questionnaire. The most important factors believed to be influencing adherence from a healthcare professional perspective are; lack of availability of medication for epilepsy (71 %), affordability of medication (60 %), the patient, family, carer lacking in understanding of medication (43 %), cultural misconceptions about epilepsy (40 %) and side effects of the medication (32 %). The survey was answered by many different healthcare professionals; 65 participants were doctors and 152 were other healthcare professionals such as nurses (59 %) pharmacists (10 %) and when comparing them, the three most important categories were consistent across groups. CONCLUSION: Healthcare workers in Sub-Saharan Africa identify that the primary factors impacting adherence to ASMs, in their view, is affordability and availability of ASMs.Addressing this issue may reduce the treatment gap.

Machine learning for forecasting initial seizure onset in neonatal hypoxic-ischemic encephalopathy.

OBJECTIVE: This study was undertaken to develop a machine learning (ML) model to forecast initial seizure onset in neonatal hypoxic-ischemic encephalopathy (HIE) utilizing clinical and quantitative electroencephalogram (QEEG) features. METHODS: We developed a gradient boosting ML model (Neo-GB) that utilizes clinical features and QEEG to forecast time-dependent seizure risk. Clinical variables included cord blood gas values, Apgar scores, gestational age at birth, postmenstrual age (PMA), postnatal age, and birth weight. QEEG features included statistical moments, spectral power, and recurrence quantification analysis (RQA) features. We trained and evaluated Neo-GB on a University of California, San Francisco (UCSF) neonatal HIE dataset, augmenting training with publicly available neonatal electroencephalogram (EEG) datasets from Cork University and Helsinki University Hospitals. We assessed the performance of Neo-GB at providing dynamic and static forecasts with diagnostic performance metrics and incident/dynamic area under the receiver operating characteristic curve (iAUC) analyses. Model explanations were performed to assess contributions of QEEG features and channels to model predictions. RESULTS: The UCSF dataset included 60 neonates with HIE (30 with seizures). In subject-level static forecasting at 30 min after EEG initiation, baseline Neo-GB without time-dependent features had an area under the receiver operating characteristic curve (AUROC) of .76 and Neo-GB with time-dependent features had an AUROC of .89. In time-dependent evaluation of the initial seizure onset within a 24-h seizure occurrence period, dynamic forecast with Neo-GB demonstrated median iAUC = .79 (interquartile range [IQR] .75-.82) and concordance index (C-index) = .82, whereas baseline static forecast at 30 min demonstrated median iAUC = .75 (IQR .72-.76) and C-index = .69. Model explanation analysis revealed that spectral power, PMA, RQA, and cord blood gas values made the strongest contributions in driving Neo-GB predictions. Within the most influential EEG channels, as the preictal period advanced toward eventual seizure, there was an upward trend in broadband spectral power. SIGNIFICANCE: This study demonstrates an ML model that combines QEEG with clinical features to forecast time-dependent risk of initial seizure onset in neonatal HIE. Spectral power evolution is an early EEG marker of seizure risk in neonatal HIE.

Epilepsy in CHAD: Realities, constraints, and prospects.

Epilepsy is a significant public health problem. More than 50 million people worldwide live with epilepsy, and over three-quarters of them are in low- and middle-income countries. The situation in Chad regarding people with epilepsy is challenging to assess, starting from the shortage of scientific data, the inadequacy of technical facilities, the lack of human resources, and the inadequacy of government action. The Ministry of Health and Chadian Society of Neurology are looking forward to prioritizing epilepsy as well as improving the living conditions of persons with this disease. The epilepsy treatment issue is also problematic. Most of the patients are either off treatment or under-medicated. Few antiseizure medications (ASMs) are available, notably carbamazepine, phenobarbital, and valproic acid. Epilepsy remains little-known and does not seem to be a priority for decision-makers. We describe the current situation in Chad, to improve the conditions under which epilepsy is treated. PLAIN LANGUAGE SUMMARY: Epilepsies is a chronic brain problem that is common in poorer settings. The daily lives of people with epilepsy are chaotic in Chad. The challenges are numerous, particularly those related to health infrastructures, due to the lack of adequate diagnostic means and the lack of neurologists. The cultural and language challenges, especially since epilepsy is still considered the devil's disease and the name differs according to the dialects. Stigmatization is also frequent and is often responsible for school dropout, refusal, or dismissal from work. Care and prevention are daily challenges that require government action. Social coverage is insufficient and almost absent in rural areas. It is urgent to prioritize epilepsy in future action plans and also to increase awareness of the conditions to overcome these challenges.

Use of Stiripentol in Patients with Dravet Syndrome: Common Practice Among Experts in Spain.

BACKGROUND: Despite considerable evidence for the efficacy and safety of stiripentol in Dravet syndrome (DS), some aspects of stiripentol use remain challenging in clinical practice, such as dose titration and the adjustment of concomitant antiseizure medications (ASMs) to prevent potential adverse effects. AIM: To (1) provide practical recommendations on the initiation of stiripentol treatment in patients with DS, (2) evaluate its effectiveness in the patient, and (3) guide the management of drug interactions and other aspects of treatment monitoring. METHODS: Six Spanish neurologists (the authors) with expertise in the management of pediatric and adult patients with DS held a meeting in early 2024 to develop expert recommendations regarding the use of stiripentol in DS, based on a review of the literature and their common clinical experience. RESULTS: According to these recommendations, stiripentol can be administered to patients with DS of any age, although its initiation and titration vary according to age group. Individualized adjustment of concomitant ASMs, such as valproic acid and clobazam or drugs specifically for DS (i.e., fenfluramine), at initiation and during stiripentol treatment, can mitigate drug interactions, thereby increasing the long-term tolerability of stiripentol treatment. In specific cases, stiripentol doses of > 50 mg/kg/day may be contemplated, and acute stiripentol administration may be considered to control refractory status epilepticus. Blood tests should be performed before starting stiripentol, at 3, 6, and 12 months after starting treatment, and then annually, except in the event of adverse effects, when additional testing may be necessary. Most adverse effects can be adequately managed by adjusting concomitant medications. CONCLUSION: These practical recommendations may be easily adapted for use in different countries, and should increase physicians' confidence in the initiation and monitoring of stiripentol treatment, thus facilitating effective management of patients with DS and improving clinical outcomes.

In this article, six Spanish neurologists with expertise in the treatment of individuals with Dravet syndrome (DS) developed recommendations based on a review of the academic literature and their common clinical experience on the use of stiripentol in the treatment of this syndrome. DS is a rare and severe form of lifelong genetic epilepsy that first develops in infancy, impairs neurologic and psychomotor development, and increases the risk of premature death. Stiripentol is an antiseizure medication for which there is considerable evidence of its efficacy and safety as a treatment for DS, but dose titration and its use in combination with other antiseizure medications to minimize potential adverse effects remain challenging in clinical practice. The expert recommendations presented here provide neurologists with practical guidance on the effective initiation of stiripentol treatment, assessment of its effectiveness in patients with DS, and guidance on the management and monitoring of its potential interaction with other medications. It is hoped that these recommendations will facilitate the effective management of patients with DS and improve their clinical outcomes.

CNN-Informer: A hybrid deep learning model for seizure detection on long-term EEG.

Timely detecting epileptic seizures can significantly reduce accidental injuries of epilepsy patients and offer a novel intervention approach to improve their quality of life. Investigation on seizure detection based on deep learning models has achieved great success. However, there still remain challenging issues, such as the high computational complexity of the models and overfitting caused by the scarce availability of ictal electroencephalogram (EEG) signals for training. Therefore, we propose a novel end-to-end automatic seizure detection model named CNN-Informer, which leverages the capability of Convolutional Neural Network (CNN) to extract EEG local features of multi-channel EEGs, and the low computational complexity and memory usage ability of the Informer to capture the long-range dependencies. In view of the existence of various artifacts in long-term EEGs, we filter those raw EEGs using Discrete Wavelet Transform (DWT) before feeding them into the proposed CNN-Informer model for feature extraction and classification. Post-processing operations are further employed to achieve the final detection results. Our method is extensively evaluated on the CHB-MIT dataset and SH-SDU dataset with both segment-based and event-based criteria. The experimental outcomes demonstrate the superiority of the proposed CNN-Informer model and its strong generalization ability across two EEG datasets. In addition, the lightweight architecture of CNN-Informer makes it suitable for real-time implementation.

Emotional comorbidities in epilepsy result from seizure-induced corticosterone activity.

People with epilepsy often have psychiatric comorbidities that can significantly impair their quality of life. We previously reported that repeated seizure activity persistently alters endocannabinoid (eCB) signaling in the amygdala which accounts for comorbid emotional dysregulation in rats, however, the mechanism by which these alterations in eCB signaling within the epileptic brain occur is unclear. Endocannabinoid signaling is influenced by corticosterone (CORT) to modulate cognitive and emotional processes and a hyperactive hypothalamic-pituitary-adrenal (HPA) axis occurs in both people with epilepsy and nonhuman animal models of epilepsy. We employed selective pharmacological tools and a variety of approaches including whole-cell patch-clamp electrophysiology, behavioural paradigms and biochemical assays in amygdala kindled adult male Long-Evans rats. We aimed to determine whether seizures induce hypersecretion of CORT and the role this plays in eCB system dysregulation, impaired fear memory, and anxiety-like behaviours associated with seizure activity. Plasma CORT levels were significantly and consistently elevated following seizures over the course of kindling. Pre-seizure administration with the CORT synthesis inhibitor metyrapone prevented this seizure-induced CORT increase, prevented amygdala anandamide downregulation, and synaptic alteration induced by seizure activity. Moreover, treatment with metyrapone or combined glucocorticoid receptor (GR)/mineralocorticoid receptor (MR) antagonists prior to each elicited seizure were equally effective in preventing chronically altered anxiety-like behaviour and fear memory responses. Inhibiting seizure-induced corticosterone synthesis, or directly blocking the effects of CORT at GR/MR prevents deleterious changes in emotional processing and could be a treatment option for emotional comorbidities in epilepsy.

Beyond seizure freedom: Reduction in anti-seizure medication after epilepsy surgery.

INTRODUCTION: Patients considering therapeutic epilepsy surgery often seek to decrease the number of anti-seizure medications (ASMs) they need. Predicting such reductions remains challenging. Although predictors of seizure freedom after epilepsy surgery are well-established, long-term outcomes remain modest and factors associated with ASM reduction, even in the absence of seizure freedom, may improve surgical planning to align with patient goals. METHODS: We studied a large multi-institutional cohort of patients who underwent epilepsy surgery between 2001 and 2022, with a minimum of two years follow-up. Preoperative features, including duration of epilepsy, epilepsy etiology, non-invasive investigation data, and total number of ASMs prescribed immediately prior to surgery were extracted for each patient. Primary endpoints included likelihood of ASM reduction and ASM freedom at multiple post-operative time points up to 15 years and stratified by seizure control. RESULTS: A total of 250 patients were followed for a median of 6.0 (range 2, 22) years after intracranial EEG (iEEG) surgery. Significant ASM reduction was only observed in those who underwent subsequent resection, whereas those undergoing neuromodulation saw their ASM usage maintained. Engel I outcomes were the strongest driver of ASM reduction. In patients with persistent seizures, patients with lateralized seizure onset zones (SOZs) also achieved sustained ASM reduction over time. Similarly, an increased number of preoperative ASMs also corresponded to a higher likelihood of ASM reduction across all follow-up periods. Other preoperative factors, including seizure etiology, did not independently influence ASM reduction. CONCLUSIONS: Even patients with persistent seizures after epilepsy surgery can observe meaningful ASM reduction during long-term follow-up. ASM reduction may be a relevant secondary outcome measure for epilepsy surgery.

Coexistence of epilepsy or seizure and multiple sclerosis; review of the literature with a single center experience.

OBJECTIVES: There is evidence that the inflammatory demyelinating disorder in Multiple Sclerosis (MS) is associated with acute seizures and epilepsy. Additionally, the likelihood of developing epilepsy increases with neurodegeneration. This study aims to reveal the clinical and radiological features of MS-epilepsy/seizure coexistence. METHODS: Among all patients diagnosed with MS that we followed in our center between April 2002 and July 2023, patients with a single seizure history or diagnosed with epilepsy (MS-seizure/epilepsy) were randomized 1:1 in terms of age and gender with MS patients without a diagnosis of epilepsy or seizures. Clinical (comorbidities, annualized relapse rate, disability, seizures during attacks, initial diagnosis, disease duration, disease-modifying therapies (DMTs), refractory epilepsy, anti-seizure drugs), electroencephalography (EEG) and MRI (lesion localization and new lesion(s)) data were retrospectively evaluated. RESULTS: The mean EDSS was 4.07±2.81. 29.4 % of patients had progressive MS (n = 10). Refractory epilepsy was 52.9 % (n = 18), and SE history was 14.7 % (n = 5). Pathology was detected in 69.7 % (n = 23) of patients in the EEG. The most common slow wave activation was detected in 51.5 % (n = 17). Refractory epilepsy was more common in cases under 45 and patients with lesions in thalamic localization. Lesions in the temporal and thalamic regions and cerebral atrophy were more common in the MS-seizure/epilepsy group. CONCLUSION: Patients with demyelinating lesions in the temporal and thalamic regions should be questioned more carefully for epilepsy, and an EEG should be performed in case of clinical suspicion. Since thalamus lesions are more common in patients with refractory epilepsy, anti-seizure treatment strategies should be applied more carefully. The presence of atrophy on MRI confirms the link between neurodegeneration processes and the development of epilepsy.

Anti-seizure effects of norepinephrine-induced free fatty acid release.

The brain's ability to rapidly transition between sleep, quiet wakefulness, and states of high vigilance is remarkable. Cerebral norepinephrine (NE) plays a key role in promoting wakefulness, but how does the brain avoid neuronal hyperexcitability upon arousal? Here, we show that NE exposure results in the generation of free fatty acids (FFAs) within the plasma membrane from both astrocytes and neurons. In turn, FFAs dampen excitability by differentially modulating the activity of astrocytic and neuronal Na+, K+, ATPase. Direct application of FFA to the occipital cortex in awake, behaving mice dampened visual-evoked potential (VEP). Conversely, blocking FFA production via local application of a lipase inhibitor heightened VEP and triggered seizure-like activity. These results suggest that FFA release is a crucial step in NE signaling that safeguards against hyperexcitability. Targeting lipid-signaling pathways may offer a novel therapeutic approach for seizure prevention.

Voltage-gated potassium channels and genetic epilepsy.

Recent advances in exome and targeted sequencing have significantly improved the aetiological diagnosis of epilepsy, revealing an increasing number of epilepsy-related pathogenic genes. As a result, the diagnosis and treatment of epilepsy have become more accessible and more traceable. Voltage-gated potassium channels (Kv) regulate electrical excitability in neuron systems. Mutate Kv channels have been implicated in epilepsy as demonstrated in case reports and researches using gene-knockout mouse models. Both gain and loss-of-function of Kv channels lead to epilepsy with similar phenotypes through different mechanisms, bringing new challenges to the diagnosis and treatment of epilepsy. Research on genetic epilepsy is progressing rapidly, with several drug candidates targeting mutated genes or channels emerging. This article provides a brief overview of the symptoms and pathogenesis of epilepsy associated with voltage-gated potassium ion channels dysfunction and highlights recent progress in treatments. Here, we reviewed case reports of gene mutations related to epilepsy in recent years and summarized the proportion of Kv genes. Our focus is on the progress in precise treatments for specific voltage-gated potassium channel genes linked to epilepsy, including KCNA1, KCNA2, KCNB1, KCNC1, KCND2, KCNQ2, KCNQ3, KCNH1, and KCNH5.

[Possibilities of stimulating epileptic seizures using deep stereo-EEG electrodes in presurgical diagnosis in patients with drug-resistant epilepsy]. / Vozmozhnosti stimulyatsii epilepticheskikh pristupov posredstvom glubinnykh stereo-EEG-elektrodov v predkhirurgicheskoi diagnostike u patsientov s farmakorezistentnoi epilepsiei.

Electrical stimulation mapping using depth stereo-EEG electrodes is an important method in the structure of presurgical diagnostics in patients with drug-resistant forms of epilepsy. Electrical stimulation mapping was first used in the 1960s and has been actively developed since then, but despite such a long history, a unified protocol for the use of this technique has not been developed and different approaches to stimulation mapping are used in different countries. Based on publications on the topic in PubMed and other available resources, we tried to briefly outline the current opinion on the significance of this technique, paying special attention to the methodological approaches of different schools to stimulation parameters when mapping epileptogenic zones, highlighting in a separate section approaches to stimulation of functionally significant zones Finally, we summarize data on the effectiveness of this method in the presurgical diagnostics of epilepsy.

New-Onset Focal to Bilateral Tonic-Clonic Seizure Following COVID-19 Vaccination.

An 18-year-old male presented with new-onset focal to bilateral tonic-clonic seizures 5 days after receiving the first dose of COVID-19 vaccine. 3 days later, an identical seizure occurred lasting 1 min, leading to an acute presentation to the hospital. In hospital, the patient was loaded with intravenous phenytoin and started on levetiracetam with no further seizure recurrence. CT venogram and scalp EEG were unremarkable. MRI brain revealed generalised atrophy with mild bilateral hippocampal atrophy. The patient was maintained on 500 mg levetiracetam twice daily and advised to proceed with subsequent doses of vaccination. Vaccinations have been associated with breakthrough seizures. In this case, COVID-19 vaccination possibly unmasked an underlying predisposition for epilepsy.

A systematic catalog of studies on fetal heart rate pattern and neonatal outcome variables.

OBJECTIVES: To study the methodology and results of studies assessing the relationship between fetal heart rate and specified neonatal outcomes including, heart rate, infection, necrotizing enterocolitis, intraventricular hemorrhage, hypoxic-ischemic encephalopathy, and seizure. METHODS: Embase, Medline ALL, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and CINAHL were searched from inception to October 5, 2023. RESULTS: Forty-two studies were included, encompassing 57,232 cases that underwent fetal monitoring and were evaluated for neonatal outcome. Heterogeneity was observed in the timing and duration of fetal heart rate assessment, classification guidelines used, number of assessors, and definition and timing of neonatal outcome assessment. Nonreassuring fetal heart rate was linked to lower neonatal heart rate variability. A significant increase in abnormal fetal heart rate patterns were reported in neonates with hypoxic-ischemic encephalopathy, but the predictive ability was found to be limited. Conflicting results were reported regarding sepsis, seizure and intraventricular hemorrhage. No association was found between necrotizing enterocolitis rate and fetal heart rate. CONCLUSIONS: There is great heterogeneity in the methodology used in studies evaluating the association between fetal heart rate and aforementioned neonatal outcomes. Hypoxic-ischemic encephalopathy was associated with increased abnormal fetal heart rate patterns, although the predictive ability was low. Further research on developing and evaluating an automated early warning system that integrates computerized cardiotocography with a perinatal health parameter database to provide objective alerts for patients at-risk is recommended.

Brain network changes after the first seizure: an insight into medication response?

After a first epileptic seizure, anti-seizure medications (ASMs) can change the likelihood of having a further event. This prospective study aimed to quantify brain network changes associated with taking ASM monotherapy. We applied graph theoretical network analysis to longitudinal resting-state functional MRI (fMRI) data from 28 participants who had recently experienced their first seizure. Participants were imaged before and during long-term ASM therapy, with a mean inter-scan interval of 6.9 months. After commencing ASM, we observed an increase in the clustering coefficient and a decrease in network path length. Brain changes after ASM treatment were most prominent in the superior frontoparietal and inferior fronto-temporal regions. Participants with recurrent seizures display the most pronounced network changes after ASM treatment. This study shows changes in brain network function after ASM administration, particularly in participants with recurrent seizures. Larger studies that ideally include control cohorts are required to understand further the connection between ASM-related brain network changes and longer-term seizure status.