Seizure-European Journal of Epilepsy最新文献

{"title":"Application of preoperative MRI lesion identification algorithm in pediatric and young adult focal cortical dysplasia-related epilepsy","authors":"Kara L. Hom ,&nbsp;Venkata Sita Priyanka Illapani ,&nbsp;Hua Xie ,&nbsp;Chima Oluigbo ,&nbsp;L. Gilbert Vezina ,&nbsp;William D. Gaillard ,&nbsp;Taha Gholipour ,&nbsp;Nathan T. Cohen","doi":"10.1016/j.seizure.2024.09.024","DOIUrl":"10.1016/j.seizure.2024.09.024","url":null,"abstract":"<div><h3>Objective</h3><div>The purpose of this study was to evaluate the performance and generalizability of an automated, interpretable surface-based MRI classifier for the detection of focal cortical dysplasia.</div></div><div><h3>Methods</h3><div>This was a retrospective cohort incorporating MRIs from the epilepsy surgery (FCD and MRI-negative) and neuroimaging (healthy controls) databases at Children's National Hospital (CNH), and a publicly-available FCD Type II dataset from Bonn, Germany. Clinical characteristics and outcomes were abstracted from patient records and/or existing databases. Subjects were included if they had 3T epilepsy-protocol MRI. Manually-segmented FCD masks were compared to the automated masks generated by the Multi-centre Epilepsy Lesion Detection (MELD) FCD detection algorithm. Sensitivity/specificity were calculated.</div></div><div><h3>Results</h3><div>From CNH, 39 FCD pharmacoresistant epilepsy (PRE) patients, 19 healthy controls, and 19 MRI-negative patients were included. From Bonn, 85 FCD Type II were included, of which 68 passed preprocessing. MELD had varying performance (sensitivity) in these datasets: CNH FCD-PRE (54 %); Bonn (68 %); MRI-negative (44 %). In multivariate regression, FCD Type IIB pathology predicted higher chance of MELD automated lesion detection. All four patients who underwent resection/ablation of MELD-identified clusters achieved Engel I outcome.</div></div><div><h3>Significance</h3><div>We validate the performance of MELD automated, interpretable FCD classifier in a diverse pediatric cohort with FCD-PRE. We also demonstrate the classifier has relatively good performance in an independent FCD Type II cohort with pediatric-onset epilepsy, as well as simulated real-world value in a pediatric population with MRI-negative PRE.</div></div>","PeriodicalId":49552,"journal":{"name":"Seizure-European Journal of Epilepsy","volume":"122 ","pages":"Pages 64-70"},"PeriodicalIF":2.7,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142378479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRI-quality and morphometric MRI analysis to identify focal cortical dysplasia: An exploratory study","authors":"E.N. Zuidhoek ,&nbsp;J.N.P. Zwemmer ,&nbsp;G.H. Visser ,&nbsp;JW. Dankbaar ,&nbsp;G. Widman","doi":"10.1016/j.seizure.2024.09.025","DOIUrl":"10.1016/j.seizure.2024.09.025","url":null,"abstract":"<div><h3>Background</h3><div>In the pre-surgical evaluation of people with focal epilepsy and a normal MRI, Morphometric Analysis Program v2018 (MAP18) aids in detecting visually inconspicuous focal cortical dysplasia (FCD). We investigated the impact of MRI scans with reduced signal-to-noise ratio (SNR) and spatial resolution (SR) on FCD detection by MAP18, aiming to improve the chances of achieving seizure freedom through epilepsy surgery.</div></div><div><h3>Methods</h3><div>Thirty MRI scans with the identified lesion using MAP18 radiologically confirmed as FCD by a neuroradiologist, were retrospective analysed. SNR and SR were artificially reduced in ten steps, and their impact on MAP18 outcomes was assessed using multilevel analysis.</div></div><div><h3>Results</h3><div>There was a significant effect after reducing SR and SNR for z-score and volume of the FCD cluster, the total number of detected clusters, and volume of these clusters. After SNR reduction, there was also a significant effect for z-score of the total number of detected clusters. FCD became undetectable by MAP18 after six steps of SR reduction (voxel size 2.8 × 2.8 × 2.8 mm³) and after two steps of SNR reduction.</div></div><div><h3>Conclusions</h3><div>This exploratory study suggests that reduced SR and SNR negatively affect FCD detection with MRI post-processing (MAP18). The MAP18 evaluator should screen MRI quality before post-processing, particularly for scans with significant visual noise or voxel sizes of 2.8 × 2.8 × 2.8 mm³ and upwards, as repeating a low-quality MRI scan is less burdensome than the adverse effects of continued seizures due to failure to detect FCD.</div></div>","PeriodicalId":49552,"journal":{"name":"Seizure-European Journal of Epilepsy","volume":"123 ","pages":"Pages 37-42"},"PeriodicalIF":2.7,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142511660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epilepsy trends in Kazakhstan: A retrospective longitudinal study using data from unified national electronic health system 2014–2020","authors":"Ruslan Akhmedullin ,&nbsp;Bermet Kozhobekova ,&nbsp;Arnur Gusmanov ,&nbsp;Temirgali Aimyshev ,&nbsp;Zhasulan Utebekov ,&nbsp;Gaziz Kyrgyzbay ,&nbsp;Azat Shpekov ,&nbsp;Abduzhappar Gaipov","doi":"10.1016/j.seizure.2024.09.022","DOIUrl":"10.1016/j.seizure.2024.09.022","url":null,"abstract":"<div><h3>Objective</h3><div>This study is designed to estimate the epidemiology of epilepsy in Kazakhstan, using a large-scale administrative health database during 2014–2020.</div></div><div><h3>Methods</h3><div>Using the Unified National Electronic Health System of Kazakhstan over a seven-year span, we explored incidence and prevalence rates, disability-adjusted life years (DALY), and all-cause mortality. Regression models using Cox proportional hazards were used to analyze the sociodemographic, mental, behavioral, and neurological factors affecting survival. Overall analyses were performed using STATA (V.16).</div></div><div><h3>Results</h3><div>The total cohort comprised of 82,907 patients, with a significant increase in the incidence of epilepsy from 26.15 in 2014 to 88.80 in 2020 per 100,000 people. Similar trends were observed in the prevalence rates, which tripled from 26.06 in 2014 to 73.10 in 2020. While mortality rates fluctuated, the elderly and children had the greatest rates of 9.97 and 2.98 per 1000 person-years respectively. DALYs revealed a substantial disease burden, with 153,532 DALYs (824.5 per 100,000) being lost during the study period. A few comorbidities, such as cerebral palsy (adjusted hazard ratio (aHR) 2.23) and central nervous system atrophy (aHR, 27.79), markedly elevated all-cause mortality. Furthermore, extrapyramidal and movement disorders (aHR 2.16, <em>p</em> = 0.06) and demyelinating diseases of the central nervous system (aHR 6.36, <em>p</em> = 0.06) showed a trend toward increased mortality risk.</div></div><div><h3>Conclusion</h3><div>To the best of our knowledge, this is the first study from Central Asia exploring a large epilepsy cohort. The findings highlight the need for targeted interventions to address the growing burden of epilepsy, particularly among children, male sex, and those with neurological comorbities.</div></div>","PeriodicalId":49552,"journal":{"name":"Seizure-European Journal of Epilepsy","volume":"122 ","pages":"Pages 58-63"},"PeriodicalIF":2.7,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142378480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep brain stimulation targets in drug-resistant epilepsy: Systematic review and meta-analysis of effectiveness and predictors of response","authors":"Ahmed Yassin ,&nbsp;Leen Al-Kraimeen ,&nbsp;Aref Qarqash ,&nbsp;Hassan AbuShukair ,&nbsp;Obada Ababneh ,&nbsp;Salma Al-Aomar ,&nbsp;Mohammad Abu-Rub ,&nbsp;Khalid Alsherbini","doi":"10.1016/j.seizure.2024.09.017","DOIUrl":"10.1016/j.seizure.2024.09.017","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Purpose&lt;/h3&gt;&lt;div&gt;Anterior nucleus of the thalamus (ANT) is the only deep brain stimulation (DBS) target that is approved by the FDA for treatment of drug-resistant epilepsy (DRE). Hippocampus (HC) and centromedian nucleus (CMN) have been reported as potential DBS targets for DRE. This study aimed to assess the effectiveness and predictors of response among DRE patients treated with DBS in general and among ANT, HC and CMN DBS-targets.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;A systematic search was executed on PubMed, SCOPUS and the Cochrane Central Register of Controlled Trials (CENTRAL) electronic databases between Jan 1, 2000 and June 29, 2020. Patients with DRE who underwent DBS treatment with at least three months of follow-up were included. Individual patient data (IPD) meta-analysis was conducted on DBS studies with available IPD. Response was defined as ≥50 % reduction in seizures frequency. Responders group was compared with non-responders group in terms of demographics, epilepsy/seizure characteristics, MRI findings, and DBS targets and duration of use. Subsequently, predictors of response to different DBS targets were investigated.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Thirty-nine studies with a total of 296 patients (ANT: 69 %, HC: 11 %, CMN: 21 %) were included. The responders group constituted of 209 patients (70.6 %). The response was significantly higher in patients with generalized seizures compared to those with focal seizures (93.2% vs 63.9 %; &lt;em&gt;p&lt;/em&gt; &lt; 0.001). Response was significantly higher with CMN (83.9 %) and HC (77.4 %) compared with ANT (65.5 %) as DBS targets (&lt;em&gt;p&lt;/em&gt; = 0.014). Response was also significantly associated with longer duration of DBS use (&lt;em&gt;p&lt;/em&gt; = 0.008). The responder rate was higher among the patients with lesional MRIs (76.7 %) than those with non-lesional MRIs (66.7 %), but with no statistically significant difference (&lt;em&gt;p&lt;/em&gt; = 0.134). Age, gender, epilepsy etiology, onset zone of focal seizures, and previous use of VNS had no significant differences between the responders and non-responders. A binary logistic regression including the seizure type, MRI findings, DBS targets, and DBS duration showed, after controlling for confounders, that the duration of DBS use was the only significant predictor of response (adjusted OR 1.061; 95 % CI 1.019–1.106; &lt;em&gt;p&lt;/em&gt; = 0.005). Regarding DBS targets, the response rate in patients with symptomatic etiology was significantly higher with HC or CMN targets than the ANT (&lt;em&gt;p&lt;/em&gt; = 0.003). In patients with non-lesional MRI, response rate was significantly higher with the CMN target compared to the other two targets (&lt;em&gt;p&lt;/em&gt; = 0.008).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;DBS proves to be effective in DRE, with progressive success upon longer treatment and possibility of improving quality of life. In addition to focal seizures, DBS has potential for treating generalized seizures as well. While the ANT stands as the most utilized and only","PeriodicalId":49552,"journal":{"name":"Seizure-European Journal of Epilepsy","volume":"122 ","pages":"Pages 144-152"},"PeriodicalIF":2.7,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling the shared genetics of common epilepsies and general cognitive ability","authors":"Naz Karadag ,&nbsp;Espen Hagen ,&nbsp;Alexey A. Shadrin ,&nbsp;Dennis van der Meer ,&nbsp;Kevin S. O'Connell ,&nbsp;Zillur Rahman ,&nbsp;Gleda Kutrolli ,&nbsp;Nadine Parker ,&nbsp;Shahram Bahrami ,&nbsp;Vera Fominykh ,&nbsp;Kjell Heuser ,&nbsp;Erik Taubøll ,&nbsp;Torill Ueland ,&nbsp;Nils Eiel Steen ,&nbsp;Srdjan Djurovic ,&nbsp;Anders M. Dale ,&nbsp;Oleksandr Frei ,&nbsp;Ole A. Andreassen ,&nbsp;Olav B. Smeland","doi":"10.1016/j.seizure.2024.09.016","DOIUrl":"10.1016/j.seizure.2024.09.016","url":null,"abstract":"<div><h3>Purpose</h3><div>Cognitive impairment is prevalent among individuals with epilepsy, and increasing evidence indicates that genetic factors can underlie this relationship. However, the extent to which epilepsy subtypes differ in their genetic relationship with cognitive function, and information about the specific genetic variants involved remain largely unknown.</div></div><div><h3>Methods</h3><div>We investigated the genetic relationship between epilepsies and general cognitive ability (COG) using complementary statistical tools, including linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR). We analyzed genome-wide association study data on COG (<em>n</em> = 269,867) and common epilepsies (<em>n</em> = 27,559 cases, 42,436 controls), including the broad phenotypes ‘all epilepsy’, focal epilepsies and genetic generalized epilepsies (GGE), as well as specific subtypes. We functionally annotated the identified loci using several biological resources and validated the results in independent samples.</div></div><div><h3>Results</h3><div>Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than ‘all epilepsy’, GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k – 2.9k variants). The other epilepsy phenotypes were insufficiently powered for MiXeR analysis. We quantified extensive genetic overlap between COG and epilepsy types, but with varying negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and ‘all epilepsy’, and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), ‘all epilepsy’ (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: <em>p</em> = 3.62 × 10^–7; ‘all epilepsy’: <em>p</em> = 2.58 × 10^–3).</div></div><div><h3>Conclusion</h3><div>Our study further dissects the substantial genetic basis shared between epilepsies and COG and identifies novel shared loci. An improved understanding of the genetic relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.</div></div>","PeriodicalId":49552,"journal":{"name":"Seizure-European Journal of Epilepsy","volume":"122 ","pages":"Pages 105-112"},"PeriodicalIF":2.7,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142401760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional seizure semiology and classification in a public and private hospital","authors":"Gabriele Vilyte ,&nbsp;James Butler ,&nbsp;Victoria Ives-Deliperi ,&nbsp;Chrisma Pretorius","doi":"10.1016/j.seizure.2024.09.020","DOIUrl":"10.1016/j.seizure.2024.09.020","url":null,"abstract":"<div><h3>Purpose</h3><div>Our understanding of potential differences in seizure semiology among patients with functional seizures (FS), also known as psychogenic non-epileptic seizures (PNES), across socioeconomic contexts is currently limited. By examining the differences in seizure manifestations between different socioeconomic groups, we aim to enhance the understanding of how socioeconomic factors may influence FS presentation. This study aimed to describe FS semiology in patients from a private and public epilepsy monitoring units (EMUs) in Cape Town, South Africa.</div></div><div><h3>Methods</h3><div>The study included patients with FS confirmed through video-electroencephalography (video-EEG) and without comorbid epilepsy. For this retrospective case-control study, data on seizure semiology was gathered from digital patient records, beginning with the earliest available record for each hospital.</div></div><div><h3>Results</h3><div>A total of 305 patients from a private hospital and 67 patients from a public hospital were eligible for the study (<em>N</em> = 372). The private hospital tended to report more akinetic and subjective seizure types when compared to the public hospital. Additionally, patients at the public hospital had higher odds of reporting emotional seizure triggers (aOR=2.57, 95% CI [1.03, 6.37]), loss of consciousness or awareness (aOR=2.58, 95% CI [1.07, 6.24]), and rapid post-event recovery (aOR=6.01, 95% CI [2.52, 14.34]). At the same time, they were less likely to report both short (&lt;30 s) (aOR=0.21, 95% CI [0.08, 0.55]) and long (&gt;5 min) seizures (aOR=0.73, 95% CI [0.13, 0.56]), amnesia for the event (aOR=0.19, 95% CI [0.09, 0.43]), ictal aphasia (aOR=0.33, 95% CI [0.14, 0.76]) or falls and drop attacks (aOR=0.43, 95% CI [0.18, 0.996]), when compared to the private hospital patients.</div></div><div><h3>Conclusion</h3><div>While the seizure manifestations were largely consistent across the two socioeconomic cohorts of patients with FS, some subtle differences were observed and warrant further investigation.</div></div>","PeriodicalId":49552,"journal":{"name":"Seizure-European Journal of Epilepsy","volume":"122 ","pages":"Pages 71-79"},"PeriodicalIF":2.7,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing epilepsy diagnosis: A meta-analysis of artificial intelligence approaches for interictal epileptiform discharge detection","authors":"Jordana Borges Camargo Diniz ,&nbsp;Laís Silva Santana ,&nbsp;Marianna Leite ,&nbsp;João Lucas Silva Santana ,&nbsp;Sarah Isabela Magalhães Costa ,&nbsp;Luiz Henrique Martins Castro ,&nbsp;João Paulo Mota Telles","doi":"10.1016/j.seizure.2024.09.019","DOIUrl":"10.1016/j.seizure.2024.09.019","url":null,"abstract":"<div><h3>Introduction</h3><div>Interictal epileptiform discharges (IEDs) in electroencephalograms (EEGs) are an important biomarker for epilepsy. Currently, the gold standard for IED detection is the visual analysis performed by experts. However, this process is expert-biased, and time-consuming. Developing fast, accurate, and robust detection methods for IEDs based on EEG may facilitate epilepsy diagnosis. We aim to assess the performance of deep learning (DL) and classic machine learning (ML) algorithms in classifying EEG segments into IED and non-IED categories, as well as distinguishing whether the entire EEG contains IED or not.</div></div><div><h3>Methods</h3><div>We systematically searched PubMed, Embase, and Web of Science following PRISMA guidelines. We excluded studies that only performed the detection of IEDs instead of binary segment classification. Risk of Bias was evaluated with Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Meta-analysis with the overall area under the Summary Receiver Operating Characteristic (SROC), sensitivity, and specificity as effect measures, was performed with R software.</div></div><div><h3>Results</h3><div>A total of 23 studies, comprising 3,629 patients, were eligible for synthesis. Eighteen models performed discharge-level classification, and 6 whole-EEG classification. For the IED-level classification, 3 models were validated in an external dataset with more than 50 patients and achieved a sensitivity of 84.9 % (95 % CI: 82.3–87.2) and a specificity of 68.7 % (95 % CI: 7.9–98.2). Five studies reported model performance using both internal validation (cross-validation) and external datasets. The meta-analysis revealed higher performance for internal validation, with 90.4 % sensitivity and 99.6 % specificity, compared to external validation, which showed 78.1 % sensitivity and 80.1 % specificity.</div></div><div><h3>Conclusion</h3><div>Meta-analysis showed higher performance for models validated with resampling methods compared to those using external datasets. Only a minority of models use more robust validation techniques, which often leads to overfitting.</div></div>","PeriodicalId":49552,"journal":{"name":"Seizure-European Journal of Epilepsy","volume":"122 ","pages":"Pages 80-86"},"PeriodicalIF":2.7,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142382167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epileptic variant in the spectrum of Alzheimer's disease - practical implications.","authors":"Benjamin Cretin","doi":"10.1016/j.seizure.2024.09.015","DOIUrl":"https://doi.org/10.1016/j.seizure.2024.09.015","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is known to be associated with an increased risk of epilepsy, which is not exclusively related to the late stage of the disease - when a major cognitive impairment is observed, previously known as the dementia stage - but also to its prodromal stage (mild cognitive impairment). Moreover, published case reports and cohorts have shown that epilepsy may occur even earlier, at the preclinical stage of AD: Epileptic seizures may therefore be the sole objective manifestation of the disease. Such a situation is called the epileptic variant of AD (evAD). EvAD is one of the etiologies of late-onset epilepsy, which means that it carries a risk of later progression to dementia and that it can only be diagnosed by assessing amyloid and tau biomarkers. However, evAD is a window of therapeutic opportunity that is probably optimal for preventing, through antiseizure medication treatment, the accelerated cognitive decline associated with AD-related brain hyperexcitability (manifested by seizures or interictal epileptiform activities).</p>","PeriodicalId":49552,"journal":{"name":"Seizure-European Journal of Epilepsy","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142331055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations between epilepsy, respiratory impairment, and minor ECG abnormalities in children","authors":"See Wai Chan ,&nbsp;Angela Chun ,&nbsp;Linh Nguyen ,&nbsp;Beth Bubolz ,&nbsp;Anne E. Anderson ,&nbsp;Yi-Chen Lai","doi":"10.1016/j.seizure.2024.09.011","DOIUrl":"10.1016/j.seizure.2024.09.011","url":null,"abstract":"<div><h3>Objective</h3><div>We sought to examine the effects of acute seizures and respiratory derangement on the cardiac electrical properties reflected on the electrocardiogram (ECG); and to analyze their potential interactions with a diagnosis of epilepsy in children.</div></div><div><h3>Methods</h3><div>Emergency center (EC) visits with seizure or epilepsy diagnostic codes from 1/2011–12/2013 were included if they had ECG within 24 h of EC visit. Patients were excluded if they had pre-existing cardiac conditions, ion channelopathy, or were taking specific cardiac medications. Control subjects were 1:1 age and gender matched. Abnormal ECG was defined as changes in rhythm, PR, QRS, or corrected QT intervals; QRS axis or morphology; ST segment; or T wave morphology from normal standards. We identified independent associations between clinical factors and abnormal ECG findings using multivariable logistic regression modeling.</div></div><div><h3>Results</h3><div>Ninety-five children with epilepsy presented to the EC with seizures, respiratory distress, and other concerns. Three hundred children without epilepsy presented with seizures. There was an increased prevalence of minor ECG abnormalities in children with epilepsy (49 %) compared to the control subjects (29 %) and those without epilepsy (36 %). Epilepsy (OR: 1.61, 95 %CI: 1.01–2.6), need for supplemental oxygen (OR 3.06, 95 % CI: 1.45–6.44) or mechanical ventilation (OR: 2.5, 95 % CI: 1.03–6.05) were independently associated with minor ECG abnormalities. Secondary analyses further demonstrated an independent association between level of respiratory support and ECG abnormalities only in the epilepsy group.</div></div><div><h3>Significance</h3><div>Independent association of increased respiratory support with minor ECG abnormalities suggests a potential respiratory influence on the hearts of children with epilepsy.</div></div>","PeriodicalId":49552,"journal":{"name":"Seizure-European Journal of Epilepsy","volume":"122 ","pages":"Pages 39-44"},"PeriodicalIF":2.7,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction begins with diagnosis: Estimating seizure recurrence risk in the First Seizure Clinic","authors":"Suyi Ooi ,&nbsp;Chris Tailby ,&nbsp;Naoto Nagino ,&nbsp;Patrick W. Carney ,&nbsp;Graeme D. Jackson ,&nbsp;David N. Vaughan","doi":"10.1016/j.seizure.2024.09.013","DOIUrl":"10.1016/j.seizure.2024.09.013","url":null,"abstract":"<div><h3>Objectives</h3><div>To assess the feasibility of using a seizure recurrence prediction tool in a First Seizure Clinic, considering (1) the accuracy of initial clinical diagnoses and (2) performance of automated computational models in predicting seizure recurrence after first unprovoked seizure (FUS).</div></div><div><h3>Methods</h3><div>To assess diagnostic accuracy, we analysed all sustained and revised diagnoses in patients seen at a First Seizure Clinic over 5 years with 6+ months follow-up (‘accuracy cohort’, n = 487).</div><div>To estimate prediction of 12-month seizure recurrence after FUS, we used a logistic regression of clinical factors on a multicentre FUS cohort (‘prediction cohort’, n = 181), and compared performance to a recently published seizure recurrence model.</div></div><div><h3>Results</h3><div>Initial diagnosis was sustained over 6+ months follow-up in 69% of patients in the ‘accuracy cohort’. Misdiagnosis occurred in 5%, and determination of unclassified diagnosis in 9%. Progression to epilepsy occurred in 17%, either following FUS or initial acute symptomatic seizure.</div><div>Within the ‘prediction cohort’ with FUS, 12-month seizure recurrence rate was 41% (95% CI [33.8%, 48.5%]). Nocturnal seizure, focal seizure semiology and developmental disability were predictive factors. Our model yielded an Area under the Receiver Operating Characteristic curve (AUC) of 0.60 (95% CI [0.59, 0.64]).</div></div><div><h3>Conclusions</h3><div>High clinical accuracy can be achieved at the initial visit to a First Seizure Clinic. This shows that diagnosis will not limit the application of seizure recurrence prediction tools in this context. However, based on the modest performance of currently available seizure recurrence prediction tools using clinical factors, we conclude that data beyond clinical factors alone will be needed to improve predictive performance.</div></div>","PeriodicalId":49552,"journal":{"name":"Seizure-European Journal of Epilepsy","volume":"122 ","pages":"Pages 87-95"},"PeriodicalIF":2.7,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142394717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}