Anticonvulsant effects of Paeonia daurica subsp. macrophylla root extracts in pentylenetetrazol-induced seizure models in mice.

INTRODUCTION: In the present study, anticonvulsant effects of aqueous extract (AE), hydro-alcoholic crude extract (HE), and its fractions (F-CHCl3, F-EtOAc, F-MeOH) of Paeonia daurica subsp. macrophylla (P. daurica ssp. macrophylla) root examined by using a pentylenetetrazol-induced model (PTZ) on mice. METHODS: HE and its fractions as well as AE, in concentrations of (100, 200 and 400mg/kg), valproate (Val) (100 and 200mg/kg), and saline (negative control) (10mg/kg) were injected intraperitoneally (i.p.) 30min before PTZ (80mg/kg, i.p.). The time taken before the onset of myoclonic convulsions (MC), MC duration, time taken before the onset of generalized tonic-clonic seizures (GTCS), the duration of GTCS, and the percentage of GTCS and mortality protection recorded. The plant's anticonvulsant mechanisms were assessed using flumazenil (5mg/kg, i.p.) before AE (100, 200, and 400mg/kg, i.p.) injection. GraphPad Prism software was used to compare the differences between various treatment groups with one-way analysis of variance (ANOVA) followed by Tukey-Krammer multiple comparison tests. RESULTS: All the plant samples except F-EtOAc significantly delayed the onset and decreased the duration of PTZ-induced MCS and GTCS, and significantly reduced the GTCS and mortality rate. Pretreatment with flumazenil diminished the significant anticonvulsant effects of AE against PTZ-induced seizures. CONCLUSIONS: It can report that extract of P. daurica ssp. macrophylla might be a helpful guide for future studies in the treatment of epilepsy.

[The importance of adherence to treatment in control of epilepsy]. / Relevancia de la adhesión al tratamiento en el control de la epilepsia.

TITLE: Relevancia de la adhesión al tratamiento en el control de la epilepsia.

Association of Localizing 18F-FDG-PET Hypometabolism and Outcome Following Epilepsy Surgery: Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Although commonly used in the evaluation of patients for epilepsy surgery, the association between the detection of localizing 18fluorine fluorodeoxyglucose PET (18F-FDG-PET) hypometabolism and epilepsy surgery outcome is uncertain. We conducted a systematic review and meta-analysis to determine whether localizing 18F-FDG-PET hypometabolism is associated with favorable outcome after epilepsy surgery. METHODS: A systematic literature search was undertaken. Eligible publications included evaluation with 18F-FDG-PET before epilepsy surgery, with ≥10 participants, and those that reported surgical outcome at ≥12 months. Random-effects meta-analysis was used to calculate the odds of achieving a favorable outcome, defined as Engel class I, International League Against Epilepsy class 1-2, or seizure-free, with localizing 18F-FDG-PET hypometabolism, defined as concordant with the epilepsy surgery resection zone. Meta-regression was used to characterize sources of heterogeneity. RESULTS: The database search identified 8,916 studies, of which 98 were included (total patients n = 4,104). Localizing 18F-FDG-PET hypometabolism was associated with favorable outcome after epilepsy surgery for all patients with odds ratio (OR) 2.68 (95% CI 2.08-3.45). Subgroup analysis yielded similar findings for those with (OR 2.64, 95% CI 1.54-4.52) and without epileptogenic lesion detected on MRI (OR 2.49, 95% CI 1.80-3.44). Concordance with EEG (OR 2.34, 95% CI 1.43-3.83), MRI (OR 1.69, 95% CI 1.19-2.40), and triple concordance with both (OR 2.20, 95% CI 1.32-3.64) was associated with higher odds of favorable outcome. By contrast, diffuse 18F-FDG-PET hypometabolism was associated with worse outcomes compared with focal hypometabolism (OR 0.34, 95% CI 0.22-0.54). DISCUSSION: Localizing 18F-FDG-PET hypometabolism is associated with favorable outcome after epilepsy surgery, irrespective of the presence of an epileptogenic lesion on MRI. The extent of 18F-FDG-PET hypometabolism provides additional information, with diffuse hypometabolism associated with worse surgical outcome than focal 18F-FDG-PET hypometabolism. These findings support the incorporation of 18F-FDG-PET into routine noninvasive investigations for patients being evaluated for epilepsy surgery to improve epileptogenic zone localization and to aid patient selection for surgery.

Machine learning applied to epilepsy: bibliometric and visual analysis from 2004 to 2023.

Background: Epilepsy is one of the most common serious chronic neurological disorders, which can have a serious negative impact on individuals, families and society, and even death. With the increasing application of machine learning techniques in medicine in recent years, the integration of machine learning with epilepsy has received close attention, and machine learning has the potential to provide reliable and optimal performance for clinical diagnosis, prediction, and precision medicine in epilepsy through the use of various types of mathematical algorithms, and promises to make better parallel advances. However, no bibliometric assessment has been conducted to evaluate the scientific progress in this area. Therefore, this study aims to visually analyze the trend of the current state of research related to the application of machine learning in epilepsy through bibliometrics and visualization. Methods: Relevant articles and reviews were searched for 2004-2023 using Web of Science Core Collection database, and bibliometric analyses and visualizations were performed in VOSviewer, CiteSpace, and Bibliometrix (R-Tool of R-Studio). Results: A total of 1,284 papers related to machine learning in epilepsy were retrieved from the Wo SCC database. The number of papers shows an increasing trend year by year. These papers were mainly from 1,957 organizations in 87 countries/regions, with the majority from the United States and China. The journal with the highest number of published papers is EPILEPSIA. Acharya, U. Rajendra (Ngee Ann Polytechnic, Singapore) is the authoritative author in the field and his paper "Deep Convolutional Neural Networks for Automated Detection and Diagnosis of Epileptic Seizures Using EEG Signals" was the most cited. Literature and keyword analysis shows that seizure prediction, epilepsy management and epilepsy neuroimaging are current research hotspots and developments. Conclusions: This study is the first to use bibliometric methods to visualize and analyze research in areas related to the application of machine learning in epilepsy, revealing research trends and frontiers in the field. This information will provide a useful reference for epilepsy researchers focusing on machine learning.

Mapping combinatorial expression of non-clustered protocadherins in the developing brain identifies novel PCDH19-mediated cell adhesion properties.

Non-clustered protocadherins (ncPcdhs) are adhesive molecules with spatio-temporally regulated overlapping expression in the developing nervous system. Although their unique role in neurogenesis has been widely studied, their combinatorial role in brain physiology and pathology is poorly understood. Using probabilistic cell typing by in situ sequencing, we demonstrate combinatorial inter- and intra-familial expression of ncPcdhs in the developing mouse cortex and hippocampus, at single-cell resolution. We discovered the combinatorial expression of Protocadherin-19 (Pcdh19), a protein involved in PCDH19-clustering epilepsy, with Pcdh1, Pcdh9 or Cadherin 13 (Cdh13) in excitatory neurons. Using aggregation assays, we demonstrate a code-specific adhesion function of PCDH19; mosaic PCDH19 absence in PCDH19+9 and PCDH19 + CDH13, but not in PCDH19+1 codes, alters cell-cell interaction. Interestingly, we found that PCDH19 as a dominant protein in two heterophilic adhesion codes could promote trans-interaction between them. In addition, we discovered increased CDH13-mediated cell adhesion in the presence of PCDH19, suggesting a potential role of PCDH19 as an adhesion mediator of CDH13. Finally, we demonstrated novel cis-interactions between PCDH19 and PCDH1, PCDH9 and CDH13. These observations suggest that there is a unique combinatorial code with a cell- and region-specific characteristic where a single molecule defines the heterophilic cell-cell adhesion properties of each code.

Seizure as the main presenting manifestation of three patients with acute glufosinate-ammonium poisoning.

Glufosinate-ammonium herbicides are the most widely used broad-spectrum, non-selective herbicides in the world. Glufosinate-ammonium is a structural analogue of glutamate (Glu) which can irreversibly inhibit the activity of glutamine synthetase (GS) and Glu decarboxylase in plants, thereby blocking the synthesis of glutamine (Gln) from Glu and ammonia (Hoerlein, 1994). This causes the plants to die because of the nitrogen metabolism disorder and subsequent intracellular accumulation of ammonia. In humans, the characteristic features of glufosinate-ammonium herbicide poisoning include gastrointestinal symptoms and neurotoxicity (Watanabe and Sano, 1998). Currently, there are no antidotes for glufosinate-ammonium herbicide poisoning, and thus supportive care is the key treatment.

Virus-Induced Epilepsy vs. Epilepsy Patients Acquiring Viral Infection: Unravelling the Complex Relationship for Precision Treatment.

The intricate relationship between viruses and epilepsy involves a bidirectional interaction. Certain viruses can induce epilepsy by infecting the brain, leading to inflammation, damage, or abnormal electrical activity. Conversely, epilepsy patients may be more susceptible to viral infections due to factors, such as compromised immune systems, anticonvulsant drugs, or surgical interventions. Neuroinflammation, a common factor in both scenarios, exhibits onset, duration, intensity, and consequence variations. It can modulate epileptogenesis, increase seizure susceptibility, and impact anticonvulsant drug pharmacokinetics, immune system function, and brain physiology. Viral infections significantly impact the clinical management of epilepsy patients, necessitating a multidisciplinary approach encompassing diagnosis, prevention, and treatment of both conditions. We delved into the dual dynamics of viruses inducing epilepsy and epilepsy patients acquiring viruses, examining the unique features of each case. For virus-induced epilepsy, we specify virus types, elucidate mechanisms of epilepsy induction, emphasize neuroinflammation's impact, and analyze its effects on anticonvulsant drug pharmacokinetics. Conversely, in epilepsy patients acquiring viruses, we detail the acquired virus, its interaction with existing epilepsy, neuroinflammation effects, and changes in anticonvulsant drug pharmacokinetics. Understanding this interplay advances precision therapies for epilepsy during viral infections, providing mechanistic insights, identifying biomarkers and therapeutic targets, and supporting optimized dosing regimens. However, further studies are crucial to validate tools, discover new biomarkers and therapeutic targets, and evaluate targeted therapy safety and efficacy in diverse epilepsy and viral infection scenarios.

X-Linked Epilepsies: A Narrative Review.

X-linked epilepsies are a heterogeneous group of epileptic conditions, which often overlap with X-linked intellectual disability. To date, various X-linked genes responsible for epilepsy syndromes and/or developmental and epileptic encephalopathies have been recognized. The electro-clinical phenotype is well described for some genes in which epilepsy represents the core symptom, while less phenotypic details have been reported for other recently identified genes. In this review, we comprehensively describe the main features of both X-linked epileptic syndromes thoroughly characterized to date (PCDH19-related DEE, CDKL5-related DEE, MECP2-related disorders), forms of epilepsy related to X-linked neuronal migration disorders (e.g., ARX, DCX, FLNA) and DEEs associated with recently recognized genes (e.g., SLC9A6, SLC35A2, SYN1, ARHGEF9, ATP6AP2, IQSEC2, NEXMIF, PIGA, ALG13, FGF13, GRIA3, SMC1A). It is often difficult to suspect an X-linked mode of transmission in an epilepsy syndrome. Indeed, different models of X-linked inheritance and modifying factors, including epigenetic regulation and X-chromosome inactivation in females, may further complicate genotype-phenotype correlations. The purpose of this work is to provide an extensive and updated narrative review of X-linked epilepsies. This review could support clinicians in the genetic diagnosis and treatment of patients with epilepsy featuring X-linked inheritance.

Potential of focal cortical dysplasia in migraine pathogenesis.

Focal cortical dysplasias are abnormalities of the cerebral cortex associated with an elevated risk of neurological disturbances. Cortical spreading depolarization/depression is a correlate of migraine aura/headache and a trigger of migraine pain mechanisms. However, cortical spreading depolarization/depression is associated with cortical structural changes, which can be classified as transient focal cortical dysplasias. Migraine is reported to be associated with changes in various brain structures, including malformations and lesions in the cortex. Such malformations may be related to focal cortical dysplasias, which may play a role in migraine pathogenesis. Results obtained so far suggest that focal cortical dysplasias may belong to the causes and consequences of migraine. Certain focal cortical dysplasias may lower the threshold of cortical excitability and facilitate the action of migraine triggers. Migraine prevalence in epileptic patients is higher than in the general population, and focal cortical dysplasias are an established element of epilepsy pathogenesis. In this narrative/hypothesis review, we present mainly information on cortical structural changes in migraine, but studies on structural alterations in deep white matter and other brain regions are also presented. We develop the hypothesis that focal cortical dysplasias may be causally associated with migraine and link pathogeneses of migraine and epilepsy.

Systematic review of rodent studies of deep brain stimulation for the treatment of neurological, developmental and neuropsychiatric disorders.

Deep brain stimulation (DBS) modulates local and widespread connectivity in dysfunctional networks. Positive results are observed in several patient populations; however, the precise mechanisms underlying treatment remain unknown. Translational DBS studies aim to answer these questions and provide knowledge for advancing the field. Here, we systematically review the literature on DBS studies involving models of neurological, developmental and neuropsychiatric disorders to provide a synthesis of the current scientific landscape surrounding this topic. A systematic analysis of the literature was performed following PRISMA guidelines. 407 original articles were included. Data extraction focused on study characteristics, including stimulation protocol, behavioural outcomes, and mechanisms of action. The number of articles published increased over the years, including 16 rat models and 13 mouse models of transgenic or healthy animals exposed to external factors to induce symptoms. Most studies targeted telencephalic structures with varying stimulation settings. Positive behavioural outcomes were reported in 85.8% of the included studies. In models of psychiatric and neurodevelopmental disorders, DBS-induced effects were associated with changes in monoamines and neuronal activity along the mesocorticolimbic circuit. For movement disorders, DBS improves symptoms via modulation of the striatal dopaminergic system. In dementia and epilepsy models, changes to cellular and molecular aspects of the hippocampus were shown to underlie symptom improvement. Despite limitations in translating findings from preclinical to clinical settings, rodent studies have contributed substantially to our current knowledge of the pathophysiology of disease and DBS mechanisms. Direct inhibition/excitation of neural activity, whereby DBS modulates pathological oscillatory activity within brain networks, is among the major theories of its mechanism. However, there remain fundamental questions on mechanisms, optimal targets and parameters that need to be better understood to improve this therapy and provide more individualized treatment according to the patient's predominant symptoms.

Disparities in Teleneurology Use in Medicaid Beneficiaries With Epilepsy by Practice Setting: Promoting Health Equity in Academic Centers.

BACKGROUND AND OBJECTIVES: Medicaid beneficiaries in many American academic medical centers can receive care in a separate facility than those not covered by Medicaid. We aimed to identify possible disparities in care by evaluating the association between facility type (integrated faculty practice or Medicaid-only outpatient clinic) and telehealth utilization in people with epilepsy. METHODS: We performed retrospective analyses using structured data from the Mount Sinai Health System electronic medical record data from January 2003 to August 2021. We identified people of all ages with epilepsy who were followed by an epileptologist after January 3, 2018, using a validated ICD-9-CM/10-CM coded case definition. We evaluated associations between practice setting and telehealth utilization, an outcome measure that captures the evolving delivery of neurologic care in a post-coronavirus disease 2019 era, using multivariable logistic regression. RESULTS: We identified 4,586 people with epilepsy seen by an epileptologist, including Medicaid beneficiaries in the Medicaid outpatient clinic (N = 387), Medicaid beneficiaries in the faculty practice after integration (N = 723), and non-Medicaid beneficiaries (N = 3,476). Patients not insured by Medicaid were significantly older (average age 40 years vs 29 in persons seen in Medicaid-only outpatient clinic and 28.5 in persons insured with Medicaid seen in faculty practice [p < 0.0001]). Medicaid beneficiaries were more likely to have drug-resistant epilepsy (DRE), with 51.94% of people seen in Medicaid-only outpatient clinic, 41.63% of Medicaid beneficiaries seen in faculty practice, and 37.2% of non-Medicaid beneficiaries having DRE (p < 0.0001). Medicaid outpatient clinic patients were less likely to have telehealth visits (phone or video); 81.65% of patients in the Medicaid outpatient clinic having no telehealth visits vs 71.78% of Medicaid beneficiaries in the faculty practice and 70.89% of non-Medicaid beneficiaries (p < 0.0001). In an adjusted logistic regression analysis, Medicaid beneficiaries had lower odds (0.61; 95% CI 0.46-0.81) of using teleneurology compared with all patients seen in faculty practice (p = 0.0005). DISCUSSION: Compared with the Medicaid-only outpatient clinic, we found higher telehealth utilization in the integrated faculty practice with no difference by insurance status (Medicaid vs other). Integrated care may be associated with better health care delivery in people with epilepsy; thus, future research should examine its impact on other epilepsy-related outcomes.

Target and suspect screening of psychoactive substances in seizures and oral fluid exploiting retention time prediction and LC-MS/MS analysis.

BACKGROUND: Novel psychoactive substances (NPS) are a group of substances, mainly of synthetic origin, characterized by toxicological properties extremely dangerous. The main difficulty in recognizing NPS in seizures and biological samples lies in their dynamic nature, related to the continuous synthesis and introduction on the market of new drugs, often with very similar structures to existing ones. The aim of this study was the creation of a robust and versatile method for the analysis of traditional drugs and NPS in different matrices. RESULTS: Both target analysis and suspect screening methodologies were developed. The strategy used for suspect screening allowed to collect data through a scheduled multi reaction monitoring (sMRM) survey which triggered the collection of enhanced product ion (EPI) spectra when a compound met information dependent acquisition (IDA) criteria. The retention time of the different drugs, which was crucial to define the sMRM survey scan parameters, was predicted with a Quantitative Structure Retention (Chromatographic) Relationship (QSRR) model by Multiple Linear Regression. The model was validated through the evaluation of training set predictions, an external validation set and a leave-one out strategy; the results showed that the method fit for its purpose. The target method was validated in oral fluid as a testing matrix, with excellent results in term of recovery, accuracy, precision and matrix effect. Finally, the performances of the suspect method were evaluated by analysing a mixture containing 8 reference standards not included in the initial dataset, as well as seizures and real oral fluid samples. Four NPS were putatively identified in the analysed samples. SIGNIFICANCE: The advantage of the proposed approach is the possibility of quantifying 65 classical drugs of abuse and NPS and, at the same time, detect and putatively identify 146 additional drugs in one single LC-MS/MS run. This is an innovative strategy for multi analyte detection and enables detection of low concentrations of drugs in complex biological matrices such as oral fluid. Considering the highly dynamic drug market, a strength of this strategy is that the analytical method can be kept up to date through the addition of new compounds based on the last drug monitoring bodies alerts without the need of authentic standards.

Efficacy and Safety of Levetiracetam for Childhood Epilepsies.

Background: Levetiracetam (LEV) is a broad spectrum second-generation antiepileptic drug (AED). Objective: The objective of the study was to investigate the efficacy and safety of levetiracetam for childhood epilepsies. Methods: This is single, tertiary centre observational, prospective study, that included paediatric patients who were treated with levetiracetam at Paediatric hospital University Clinical Centre Sarajevo, during the period of 15 years (2008-2022). Inclusion criteria were: paediatric patients age > 1 month, diagnosed with epilepsy according to International League Against Epilepsy. After the introduction of levetiracetam, each patient has been followed up at least 12 months. According to the outcome the patients were divided into 5 groups: seizure reduction >50%, seizure reduction <50%, complete seizure freedom, the same number of seizures and increased number of seizures. From these groups two intergroups have been formed: responders (seizure reduction >50% and complete seizure freedom) and non-responders (seizure reduction <50%, the same number of seizures and increased number of seizures). Results: The study enrolled 259 patients (141 female and 118 male), with mean age 7 years (3,0-12.0). Comorbidities were present at 129/259 (49.8%) patients. After 12 months of treatment, 25/259 (9.7%) patients had seizure reduction >50%, 30/259 (11.6%) patients had seizure reduction <50%, 154/259 (56.5%) patients had achieved seizure freedom, 31/259 (12%) patients had same number of seizures, while 19/259 (7.3%) patients had increased number of seizures. Seizure frequency between responders and non-responders, before treatment and after 12 months of treatment was statistically significant (p<0.001). Discussion: Non responders had the best outcome with ditherapy (30/79; 38%), while responders had the best outcome with monotherapy (161/180;89.4%). Conclusion: Levetiracetam is efficient antiepileptic drug for different types of epilepsies in childhood, used as mono, di or polytherapy.

Very Long-Term Functional Outcomes and Dependency in Children With Anti-NMDA Receptor Encephalitis.

OBJECTIVES: To assess the daily function of children with anti-N-methyl-d-aspartate receptor encephalitis (NMDARe) after a minimal follow-up of 5 years. METHODS: Patients 18 years and younger by the time of disease onset, whose serum and CSF were studied in our center between 2013 and 2017, were included in the study. Patients' daily life function was assessed by their physicians using a 15-domain question format (Liverpool Outcome Score). RESULTS: Of 76 patients, 8 (11%) died and 68 were followed for a mean of 7.1 years (SD 1.5 years, range: 5.0-10.1). Three outcome patterns were identified: full recovery (50; 73%); behavioral and school/working deficits (12; 18%); and multidomain deficits (6; 9%) involving self-care ability, behavioral-cognitive impairment, and seizures. Younger age of disease onset was significantly associated with multidomain deficits (OR 1.6, 95% CI 1.02-2.4, p = 0.04), particularly in children younger than 6 years, among whom 8 of 23 (35%) remained sociofamiliar dependent. DISCUSSION: After a minimal follow-up of 5 years, most children with NMDARe had substantial or full functional recovery, but approximately one-fifth remained with behavioral and school/working deficits. The younger the patient at disease onset, the more probable it was to remain with multidomain deficits and dependent on sociofamiliar support.

Clinically significant changes in genes and variants associated with epilepsy over time: implications for re-analysis.

Despite the significant advances in understanding the genetic architecture of epilepsy, many patients do not receive a molecular diagnosis after genomic testing. Re-analysing existing genomic data has emerged as a potent method to increase diagnostic yields-providing the benefits of genomic-enabled medicine to more individuals afflicted with a range of different conditions. The primary drivers for these new diagnoses are the discovery of novel gene-disease and variants-disease relationships; however, most decisions to trigger re-analysis are based on the passage of time rather than the accumulation of new knowledge. To explore how our understanding of a specific condition changes and how this impacts re-analysis of genomic data from epilepsy patients, we developed Vigelint. This approach combines the information from PanelApp and ClinVar to characterise how the clinically relevant genes and causative variants available to laboratories change over time, and this approach to five clinical-grade epilepsy panels. Applying the Vigelint pipeline to these panels revealed highly variable patterns in new, clinically relevant knowledge becoming publicly available. This variability indicates that a more dynamic approach to re-analysis may benefit the diagnosis and treatment of epilepsy patients. Moreover, this work suggests that Vigelint can provide empirical data to guide more nuanced, condition-specific approaches to re-analysis.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

Predictors of Seizure Recurrence in Women With Idiopathic Generalized Epilepsy Who Switch From Valproate to Another Medication.

BACKGROUND AND OBJECTIVES: To investigate the predictors of seizure recurrence in women of childbearing age with idiopathic generalized epilepsy (IGE) who switched from valproate (VPA) to alternative antiseizure medications (ASMs) and compare the effectiveness of levetiracetam (LEV) and lamotrigine (LTG) as VPA alternatives after switch. METHODS: This multicenter retrospective study included women of childbearing age diagnosed with IGE from 16 epilepsy centers. Study outcomes included worsening or recurrence of generalized tonic-clonic seizure (GTCS) at 12 months and 24 months after the switch from VPA to an alternative ASM. The comparative effectiveness of LEV and LTG as alternative ASM following VPA discontinuation was assessed through inverse probability treatment-weighted (IPTW) Cox regression analysis. RESULTS: We included 426 women with IGE, with a median (interquartile range) age at VPA switch of 24 (19-30) years and a median VPA dosage of 750 (500-1,000) mg/d. The most common reason for VPA switch was teratogenicity concern in 249 women (58.6%), and the most common ASM used in place of VPA was LEV in 197 (46.2%) cases, followed by LTG in 140 (32.9%). GTCS worsening/recurrence occurred in 105 (24.6%) and 139 (32.6%) women at 12 and 24 months, respectively. Catamenial worsening of seizures, higher VPA dosage during switch, multiple seizure types, and shorter duration of GTCS freedom before switch were independent predictors of GTCS recurrence or worsening at 12 months according to mixed multivariable logistic regression analysis. After internal-external validation through 16 independent cohorts, the model showed an area under the curve of 0.71 (95% CI 0.64-0.77). In the subgroup of 337 women who switched to LEV or LTG, IPTW Cox regression analysis showed that LEV was associated with a reduced risk of GTCS worsening or recurrence compared with LTG (adjusted hazard ratio 0.59, 95% CI 0.40-0.87, p = 0.008) during the 24-month follow-up. DISCUSSION: Our findings can have practical implications for optimizing counselling and treatment choices in women of childbearing age with IGE and may help clinicians in making informed treatment decisions in this special population of patients. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that for women with IGE switching from VPA, LEV was associated with a reduced risk of GTCS worsening or recurrence compared with LTG.

Short-stay urgent hospital admissions of children with convulsions: A mixed methods exploratory study to inform out of hospital care pathways.

OBJECTIVE: To inform interventions focused on safely reducing urgent paediatric short stay admissions (SSAs) for convulsions. METHODS: Routinely acquired administrative data from hospital admissions in Scotland between 2015-2017 investigated characteristics of unscheduled SSAs (an urgent admission where admission and discharge occur on the same day) for a diagnosis of febrile and/or afebrile convulsions. Semi-structured interviews to explore perspectives of health professionals (n = 19) making referral or admission decisions about convulsions were undertaken. Interpretation of mixed methods findings was complemented by interviews with four parents with experience of unscheduled SSAs of children with convulsion. RESULTS: Most SSAs for convulsions present initially at hospital emergency departments (ED). In a subset of 10,588 (11%) of all cause SSAs with linked general practice data available, 72 (37%) children with a convulsion contacted both the GP and ED pre-admission. Within 30 days of discharge, 10% (n = 141) of children admitted with afebrile convulsions had been readmitted to hospital with a further convulsion. Interview data suggest that panic and anxiety, through fear that the situation is life threatening, was a primary factor driving hospital attendance and admission. Lengthy waits to speak to appropriate professionals exacerbate parental anxiety and can trigger direct attendance at ED, whereas some children with complex needs had direct access to convulsion professionals. CONCLUSIONS: SSAs for convulsions are different to SSAs for other conditions and our findings could inform new efficient convulsion-specific pre and post hospital pathways designed to improve family experiences and reduce admissions and readmissions.

Dynamical modulation of hypersynchronous seizure onset with transcranial magneto-acoustic stimulation in a hippocampal computational model.

Hypersynchronous (HYP) seizure onset is one of the frequently observed seizure-onset patterns in temporal lobe epileptic animals and patients, often accompanied by hippocampal sclerosis. However, the exact mechanisms and ion dynamics of the transition to HYP seizures remain unclear. Transcranial magneto-acoustic stimulation (TMAS) has recently been proposed as a novel non-invasive brain therapy method to modulate neurological disorders. Therefore, we propose a biophysical computational hippocampal network model to explore the evolution of HYP seizure caused by changes in crucial physiological parameters and design an effective TMAS strategy to modulate HYP seizure onset. We find that the cooperative effects of abnormal glial uptake strength of potassium and excessive bath potassium concentration could produce multiple discharge patterns and result in transitions from the normal state to the HYP seizure state and ultimately to the depolarization block state. Moreover, we find that the pyramidal neuron and the PV+ interneuron in HYP seizure-onset state exhibit saddle-node-on-invariant-circle/saddle homoclinic (SH) and saddle-node/SH at onset/offset bifurcation pairs, respectively. Furthermore, the response of neuronal activities to TMAS of different ultrasonic waveforms revealed that lower sine wave stimulation can increase the latency of HYP seizures and even completely suppress seizures. More importantly, we propose an ultrasonic parameter area that not only effectively regulates epileptic rhythms but also is within the safety limits of ultrasound neuromodulation therapy. Our results may offer a more comprehensive understanding of the mechanisms of HYP seizure and provide a theoretical basis for the application of TMAS in treating specific types of seizures.