Journal of epilepsy research最新文献

Background and purpose: In recent years, brain-derived neurotrophic factor (BDNF) and matrix metalloproteinase-9 (MMP-9) have garnered interest for their involvement in epilepsy. This study evaluated the serum levels of BDNF and MMP-9 in pediatric patients with epilepsy compared to healthy controls and assessed the effect of valproate on serum BDNF and MMP-9.

Methods: Children aged 1 year to 12 years, diagnosed with epilepsy (n=30), and age-matched healthy controls (n=30) were included. All participants were followed up for 16 weeks and assessed for changes in serum BDNF and MMP-9 levels.

Results: Children with epilepsy had significantly lower BDNF and higher MMP-9 levels compared to healthy controls at baseline. Following 16 weeks of treatment with valproate, BDNF levels were increased significantly (p<0.001), and MMP-9 levels decreased significantly (p<0.001).

Conclusions: The findings suggest the involvement of BDNF and MMP-9 in the pathogenesis of epilepsy. Serum BDNF and MMP-9 levels were increased and decreased, respectively, following valproate treatment in children with epilepsy. Hence, BDNF and MMP-9 could be potential biomarkers in pediatric epilepsy. Large sample sizes and long-term studies are warranted to confirm the findings.

Magnetoencephalography (MEG) is a non-invasive neurophysiological technique offering high spatial resolution for localizing epileptogenic zones in epilepsy, especially when traditional electroencephalography or magnetic resonance imaging (MRI) is inconclusive. A systematic evaluation of MEG's diagnostic and prognostic utility within combination strategies is crucial, particularly in countries like South Korea with limited MEG access. We conducted a qualitative systematic review of nine studies (n=354 focal epilepsy patients) to evaluate MEG's clinical performance in presurgical workup. Databases (MEDLINE, EMBASE, Cochrane, KoreaMed, KMbase, RISS) were searched. Data extraction focused on localization accuracy and surgical outcomes (Engel class I); risk of bias was assessed using quality assessment of diagnostic accuracy studies-2. MEG alone achieved up to the mid-70% range; however, integration with other modalities (e.g., with positron emission tomography/high-density electroencephalography) significantly improved both localization and surgical outcomes. Pediatric focal cortical dysplasia patients showed Engel class I outcomes of 67-87%. Most studies had low-to-moderate bias. Only one MEG system is operational in South Korea (introduced 2023), limiting accessibility. Canadian economic evaluations, despite higher initial costs, suggest MEG is long-term cost-effective, improving quality-adjusted life years. MEG offers complementary diagnostic value in epilepsy evaluation and surgical planning, enhancing localization and outcome prediction, especially for pediatric and MRI-negative patients. Considering this clinical utility, national support for MEG equipment and its regional expansion in South Korea is crucial to ensure equitable access and optimal patient care.

Psoas syndrome is a rare form of muscle irritation that causes pain and weakness in the lower extremities. A 52-year-old male presented to the emergency department with complaints of having had a seizure and weakness in the left lower extremity. A computerized tomography scan of the abdomen and pelvis revealed reversible thickening of the left psoas muscle, consistent with psoas syndrome. We report a case of psoas syndrome following a generalized seizure and discuss its clinical characteristics and differential diagnoses.

Background and purpose: S100B is a cytokine produced by astrocytes following glial and neuronal damage. This study aims to evaluate the impact of anti-epileptic drugs (AEDs) on serum S100B levels and health-related quality of life (HRQoL) indices.

Methods: In this prospective observational study, serum S100B levels were compared between persons with epilepsy (PWE) and healthy controls. In the PWE group, serum S100B levels and HRQoL using patient weighted quality of life in epilepsy (QOLIE-10-P), pittsburgh sleep quality index (PSQI), and liverpool adverse event profile (LAEP) scores were assessed at baseline and after 12 weeks of AEDs treatment.

Results: The mean baseline serum S100B level in the PWE group was 0.093±0.031 μg/L, significantly higher than in the control group, 0.050±0.020 μg/L. In PWE, after 12 weeks of treatment, this level decreased by 17.20% (p<0.001). QOLIE-10-P scores showed improvement (32.1%; p<0.001) across both conventional and newer AED types. PSQI scores improved by 6.9% with conventional AEDs (p=0.19) and 35.7% with newer AEDs (p<0.001). LAEP scores increased by 5.06% with conventional AEDs (p=0.06) and decreased by 5.63% with newer AEDs (p=0.10). Seizures were significantly reduced in both groups (overall 86.09%). Treatment costs were higher for newer AEDs ($39.10) than for conventional AEDs ($16.73).

Conclusions: Over 12 weeks of AED therapy, PWE demonstrated significant reductions in both serum S100B levels and seizure frequency. While conventional and newer AEDs yielded comparable improvements in HRQoL, newer AEDs conferred an advantage in sleep quality.

[This retracts the article on p. 45 in vol. 4, PMID: 25625088.].

Drug-resistant epilepsy (DRE) remains a formidable clinical challenge, affecting nearly 30-40% of patients despite optimized pharmacotherapy. In patients for whom resective surgery is contraindicated or poses unacceptable risks, neuromodulatory therapies-most notably deep brain stimulation (DBS)-have emerged as viable and reversible treatment options. This narrative review critically examines the current applications of DBS for DRE, with a focus on major targets including the anterior thalamic nucleus, centromedian nucleus, hippocampus, and emerging targets such as the pulvinar. We provide an in-depth discussion of the therapeutic mechanisms underlying DBS-from local cellular inhibition and desynchronization to widespread network modulation and neuroplasticity induction-and review the latest advances in sensing technologies, patient-specific connectivity mapping, and closed loop stimulation paradigms. In addition to integrating data from randomized controlled trials, long-term observational studies, and advanced imaging investigations, we discuss limitations, persistent challenges, and future research directions that will guide clinical decision-making and optimize therapeutic outcomes.

Recent research has disclosed significant associations between stigma suffered by people living with epilepsy (PWE) and psychiatric conditions, especially major depression. These results have practical implication when coupled with the precise regional-and-local prevalences of stigma in its heterogeneous manifestations among PWE. Here we review current research involving stigma in PWE to assess its prevalence and explore psychopathological associations. A systematic review was conducted in PubMed and Scopus to identify clinical trials objectively evaluating prevalence of any type of stigma, enacted and perceived, in PWE, published from database inception to 31 May 2024. A random effects meta-analysis was undertaken, with 6,072 participants, to obtain the meta-prevalence of stigma among PWE. Subgroup analysis moderated by major continent was delineated. A report was obtained from clinical documentation review and adjoined to the evidence generated. From the 105 records identified, 22 studies were eligible for inclusion. The meta-analysis revealed an overall stigma prevalence of 35% (29%; 41%), and subgroups, Africa or Asia (mostly); arbitrarily defined after analysis of geographical study distributions; indicated a prevalence of 40% (34%; 46%) and 28% (21%; 37%), respectively. Significant difference was identified (p=0.03). The case reported exemplifies how stigma may impair development, especially in children and adolescents. Stigmas among PWE are prevalent. More than one in three PWE has already experienced some form of stigma and there is potential to undermine quality of life and associate with psychiatric disorders. PWE may benefit from tailored screening and management approaches to decrease stigma burden.

Diagnosing and managing epilepsy is difficult for doctors. Surgery can help some patients, but it often takes a long time to get there. This research looks at scientific studies to see if artificial intelligence and machine learning (ML) can be used to improve epilepsy treatment. In-depth research was conducted across PubMed, Google Scholar, Scopus, Wiley, Web of Science, and Microsoft Academia. This search focused on studies exploring the use of ML for diagnosing epilepsy, predicting treatment response, and predicting outcomes of epilepsy surgery. The search was limited to original English-language articles published between 2015 and 2022. This review examined 36 studies on using ML to predict epilepsy. The studies fell into four categories: general diagnosis (27), treatment outcome (3), identifying surgical candidates (2), and predicting surgical results (4). Researchers employed a diverse set of data, including symptoms and brain scans, alongside machine learning algorithms like support vector machines and convolutional neural networks, to construct their models. Some models achieved impressive results with areas under the curve reaching up to 0.99, but most studies were limited by small sample sizes and a lack of independent validation. ML shows potential for epilepsy treatment based on initial studies, but real-world use is restricted due to small sample sizes and the need for more validation from other studies. Large collaborative research efforts and data on long-term outcomes are essential before ML can be widely adopted by doctors and make a positive difference for epilepsy patients.