Pediatric epilepsy: Five new things

Predictors of drug-resistant epilepsy in childhood epilepsy syndromes: A subgroup analysis from a prospective cohort study

OBJECTIVE

Previous studies assessing factors associated with drug-resistant epilepsy (DRE) were constrained by their amalgamation of all epilepsy syndromes in their analyses and the absence of uniform criteria for defining DRE. Our objective was to identify predictors of DRE among the four primary childhood epilepsy syndrome groups within a cohort of children with new onset seizures, using the International League Against Epilepsy (ILAE) definition of DRE and the recent classification of epilepsies.

METHODS

This is a prospective study of 676 children with new onset seizures initiated on antiseizure medication. Patients were monitored for the occurrence of DRE according to the ILAE criteria and were categorized into one of four epilepsy groups: self-limited focal epilepsies (SeLFEs), genetic generalized epilepsies (GGEs), developmental epileptic encephalopathies (DEEs), and focal epilepsies. Cox regression analysis was performed to identify predictors of DRE within each epilepsy group.

RESULTS

Overall, 29.3% of children were classified as having DRE, with the highest incidence observed among children diagnosed with DEEs (77.7%), followed by focal epilepsies (31.5%). Across the entire cohort, predictors of DRE included the presence of an epileptogenic lesion, a higher pretreatment number of seizures, experiencing multiple seizure types, presence and severity of intellectual and developmental delay, myoclonus, and younger age at epilepsy onset. Within the GGEs, only a younger age at seizure onset and experiencing multiple seizure types predicted DRE. Among focal epilepsies, predictors of DRE included the presence of an epileptogenic lesion, experiencing multiple seizure types, and having a greater number of pretreatment seizures. Within the DEEs, predictors of DRE were the occurrence of tonic seizures. Predictors of DRE within SeLFEs could not be identified.

SIGNIFICANCE

This study indicates that different epilepsy syndromes are associated with distinct predictors of drug resistance. Anticipation of drug resistance within various groups is feasible using accessible clinical variables throughout the disease course.

Stigma perception and health fatalism in parents of children with epilepsy: A cross-sectional study

Aim

The aim of this study was to examine the factors that affect stigma perceptions and health fatalism of parents of children with epilepsy in eastern Turkey, the relationship between these and the impact of these on their social lives.

Method

This descriptive and cross-sectional study was conducted between August 2022 and January 2023 with the parents of children under the age of 18 who had been diagnosed with epilepsy for at least 1 year and who were followed up in the only hospital with a paediatric neurology outpatient clinic in Van province of Turkey. No sample selection was made in the study. Healthy parents (n = 123) who presented to the outpatient clinic within the specified time period and who agreed to participate in the study after being explained the purpose of the study participated in the study.

Results

In this study, parental age was found to have a statistically weak positive correlation with Health Fatalism Scale (HFS) (r = 0.251; p = 0.005). A weak positive correlation was also found between the years patients had epilepsy and Parent Stigma Scale (PSS) (r = 0.275; p = 0.002). In addition, a statistically positive and weak relationship was found between Parent Stigma Scale scores and Health Fatalism Scale scores (r = 0.212; p = 0.018). This study found significant relationships between stigma perception and health fatalism in parents of epileptic children. Stigma perception increased with disease duration and lower parental education levels.

Conclusion

While providing an important basis for understanding the difficulties experienced by parents and developing support mechanisms, the present study can contribute to more informed support for parents of patients with epilepsy in the community. Nurses can contribute to ending stigma and discrimination by identifying patients' and parents' perceptions of epilepsy, focusing on addressing gaps in knowledge and raising awareness in the community.

Assessment of knowledge, attitude and practice (KAP) of parents/caregivers towards epilepsy in children - A cross- sectional observational study

Objectives

The study aimed to assess the knowledge, attitude, and practice (KAP) of parents/caregivers toward epilepsy in paediatric patients at a tertiary care centre of North India.

Methods

A cross sectional study was carried out among 418 parents or caregivers using convenience sampling technique with 16-item questionnaire in English language and also translated to local language that is Hindi. Children with epilepsy who visited the paediatric outpatient department within a year were included in the study (January 2021-22). A total of 450 children visited the clinic, 32 of whom were excluded for various reasons, and the final analysis was conducted among the 418 parents or caregivers who completed the questionnaire.

Results

The male and female patients were 56.7% (n = 237) and 43.3% (n = 181) respectively. The age distribution of patients with less than 5 years, 6-10 years and more than 10 years were 35.6% (n = 149), 54.5% (n = 228), 9.8% (n = 41) respectively. Only one third of parents and caregivers did not consider epilepsy as psychiatric illness. Most of the parents and caregivers think that epilepsy affects school performance (77.2%) and hinders family life (71.0%). More than half of the parents or caregivers believes that the society discriminates against person with epilepsy and around 46.6% consider that alternative medicine can cure epilepsy. The parents or caregivers felt financial burden due to epilepsy was in 72.5% and approximately 78.5% perceived that their work is affected because of their child's epilepsy. Perception of epilepsy as a psychiatric illness was found to be significantly higher in parents with primary and secondary level education, when compared to parents who were graduates. The practice of the parents or caregivers towards administration of drugs to their child was good, however around 36.6% (n = 153) missed the dose of anti-seizure medications.

Conclusion

The study highlights the substantial knowledge, attitude and practice gap amongst parents and caregivers for children with epilepsy which indirectly has huge impact on the management of epilepsy. Thus it becomes utmost important to educate the family as well as the community regarding epilepsy which will help in improving the therapeutic outcomes, overall quality of life and interpersonal and social relationships of these children.

Focal drug-resistant temporal lobe epilepsy associated with an ipsilateral anterior choroidal artery aneurysm: illustrative case

BACKGROUND

The occurrence of both an intracranial aneurysm and epilepsy, especially drug-resistant epilepsy (DRE), is rare. Although the overall incidence of aneurysms associated with DRE is unclear, it is thought to be particularly infrequent in the pediatric population. Surgical ligation of the offending aneurysm has been reported in conjunction with resolving seizure activity, although few cases have cited a combined approach of aneurysm ligation and resection of an epileptogenic focus.

OBSERVATIONS

We present the case of a 14-year-old female patient with drug-resistant temporal lobe epilepsy and an ipsilateral supraclinoid internal carotid artery aneurysm. Seizure semiology, electroencephalography monitoring, and magnetic resonance imaging all indicated a left temporal epileptogenic focus, in addition to an incidental aneurysm. The authors recommended a combined surgery involving resection of the temporal lesion and surgical clip ligation of the aneurysm. Near-total resection and successful ligation were achieved, and the patient has remained seizure free since surgery at 1 year postoperatively.

LESSONS

In patients with focal DRE and an adjacent intracranial aneurysm, a combined surgical approach involving both resection and surgical ligation can be used. Several surgical timing and neuroanesthetic considerations should be made to ensure the overall safety and efficacy of this procedure.

Epileptic seizure detection by using interpretable machine learning models

Objective.Accurate detection of epileptic seizures using electroencephalogram (EEG) data is essential for epilepsy diagnosis, but the visual diagnostic process for clinical experts is a time-consuming task. To improve efficiency, some seizure detection methods have been proposed. Regardless of traditional or machine learning methods, the results identify only seizures and non-seizures. Our goal is not only to detect seizures but also to explain the basis for detection and provide reference information to clinical experts.Approach.In this study, we follow the visual diagnosis mechanism used by clinical experts that directly processes plotted EEG image data and apply some commonly used models of LeNet, VGG, deep residual network (ResNet), and vision transformer (ViT) to the EEG image classification task. Before using these models, we propose a data augmentation method using random channel ordering (RCO), which adjusts the channel order to generate new images. The Gradient-weighted class activation mapping (Grad-CAM) and attention layer methods are used to interpret the models.Main results.The RCO method can balance the dataset in seizure and non-seizure classes. The models achieved good performance in the seizure detection task. Moreover, the Grad-CAM and attention layer methods explained the detection basis of the model very well and calculate a value that measures the seizure degree.Significance.Processing EEG data in the form of images can flexibility to use a variety of machine learning models. The imbalance problem that exists widely in clinical practice is well solved by the RCO method. Since the method follows the visual diagnosis mechanism of clinical experts, the model interpretation results can be presented to clinical experts intuitively, and the quantitative information provided by the model is also a good diagnostic reference.

Anti-inflammatory effects of vagus nerve stimulation in pediatric patients with epilepsy

Introduction

The neural control of the immune system by the nervous system is critical to maintaining immune homeostasis, whose disruption may be an underlying cause of several diseases, including cancer, multiple sclerosis, rheumatoid arthritis, and Alzheimer's disease.

Methods

Here we studied the role of vagus nerve stimulation (VNS) on gene expression in peripheral blood mononuclear cells (PBMCs). Vagus nerve stimulation is widely used as an alternative treatment for drug-resistant epilepsy. Thus, we studied the impact that VNS treatment has on PBMCs isolated from a cohort of existing patients with medically refractory epilepsy. A comparison of genome-wide changes in gene expression was made between the epilepsy patients treated and non-treated with vagus nerve stimulation.

Results

The analysis showed downregulation of genes related to stress, inflammatory response, and immunity, suggesting an anti-inflammatory effect of VNS in epilepsy patients. VNS also resulted in the downregulation of the insulin catabolic process, which may reduce circulating blood glucose.

Discussion

These results provide a potential molecular explanation for the beneficial role of the ketogenic diet, which also controls blood glucose, in treating refractory epilepsy. The findings indicate that direct VNS might be a useful therapeutic alternative to treat chronic inflammatory conditions.

Seizure onset zone classification based on imbalanced iEEG with data augmentation

Objective. Identifying the seizure onset zone (SOZ) in patients with focal epilepsy is the critical information required for surgery. However, collecting this information is challenging, time-consuming, and subjective. Some machine learning methods reduce the workload of clinical experts in intracranial electroencephalogram (iEEG) visual diagnosis but face significant challenges because interictal iEEG clinical data often suffer from a significant class imbalance. We aim to generate synthetic data for the minority class.Approach. To make the clinically imbalanced data suitable for machine learning, we introduce an EEG augmentation method (EEGAug). The EEGAug method randomly selects several samples from the minority class and transforms them into the frequency domain. Then, different frequency bands from different samples are used to compose new data. Finally, a synthetic sample is generated after converting the new data back to the time domain.Main results. The imbalanced clinical iEEG data can be balanced and applied to machine learning models using the method. A one-dimensional convolutional neural network model is used to classify the SOZ and non-SOZ data. We compare the EEGAug method with other data augmentation methods and another method of class-balanced focal loss function, which is also used for solving the data imbalance problem by adjusting the weights between the minority and majority classes. The results show that the EEGAug method performs best in most data.Significance. Data imbalance is a widespread clinical problem. The EEGAug method can flexibly generate synthetic data for the minority class, yielding synthetic and raw data with a high distribution similarity. By using the EEGAug method, clinical data can be used in machine learning models.

Over 10-Year Outcomes of Infantile-Onset Epilepsies

Seizures in infancy have highly variable courses and underlying etiologies. However, there are only a few long-term follow-up studies regarding infantile-onset epilepsy. Therefore, we aimed to describe the clinical courses, seizure outcomes, and risk factors of infantile-onset epilepsy followed up for more than 10 years in a tertiary center. Methods: Data of the patients with epilepsy, diagnosed under the age of 12 months and followed up for more than 10 years, were retrieved from the electronic medical records of Asan Medical Center Children’s Hospital. The patients’ medical records were retrospectively reviewed, and clinical outcomes were assessed based on the duration of seizure freedom at the last follow-up. Results: Of the 146 patients, 103 (70.5%) entered at least one remission, of whom epilepsy was resolved in 46 (31.5%). Forty-nine (33.6%) were found to be intractable at last contact. Delayed development, neurological deficits, and later onset (>3 months) were significantly associated with intractable epilepsies (p < 0.01). Conclusions: This study demonstrated that many patients with infantile-onset epilepsy can experience seizure remission. However, in some cases, early onset epilepsy was highly associated with various comorbidities and intractable seizures. Therefore, appropriate diagnosis and treatment are necessary to prevent further neuropsychiatric complications.

An Overview of Digital Health in the Transition of Pediatric to Adult Epilepsy Care

Children with epilepsy often have impairments in cognitive and behavioral functioning which may hinder socio-occupational well-being as they reach adulthood. Adolescents with epilepsy have the added worry of health problems while starting the transition from family-centered pediatric care into largely autonomous adult care. If this transition is not appropriately planned and resourced, it may result in medical mistrust, nonadherence, and worsening biopsychosocial health as an adult. In recent years, there has been increased availability of digital health solutions that may be used during this stark change in care and treating teams. The digital health landscape includes a wide variety of technologies meant to address challenges faced by patients, caregivers, medical professionals, and health care systems. These technologies include mobile health products and wearable devices (e.g., seizure monitors and trackers, smartphone passive data collection), digital therapeutics (e.g., cognitive/behavioral health management; digital speech–language therapy), telehealth services (e.g., teleneurology visits), and health information technology (e.g., electronic medical records with patient portals). Such digital health solutions may empower patients in their journey toward optimal brain health during the vulnerable period of pediatric to adult care transition. Further research is needed to validate and measure their impact on clinical outcomes, health economics, and quality of life.

TRPM2 ion channel is involved in the aggravation of cognitive impairment and down regulation of epilepsy threshold in pentylenetetrazole-induced kindling mice

Epilepsy is one of the most common neurological conditions. Recent findings suggest that one of the mechanisms promoting its existence is calcium influx. The transient receptor potential melastatin type 2 channel (TRPM2) is a Ca²⁺-permeable cation channel that contributes to cell apoptosis; its possible signaling pathway is the PARP1/BNIP3/AIF/Endo G pathway that may be related to epilepsy. The aim of this study was to investigate the TRPM2 channel's involvement in epilepsy and how it works. We also explored the possible role of the TRPM2 channel on cognitive ability and emotion in epilepsy. To accomplish our goals, we used different animal epilepsy models to study the effect of the TRPM2 channel on epilepsy. The results showed that the knockout (KO) of the TRPM2 gene might play a protective role in epilepsy. Considering the advantages attributed to pentylenetetrazole (PTZ)-induced kindling mouse model, we used the model for the following assessments: 1. to observe changes in cognition and anxiety between wild type (WT) mice and TRPM2-KO mice with the recognition of new things trial and elevated plus-maze; 2. to determine the expression of apoptosis-associated proteins (PARP1, BNIP3, AIF, and Endo G) using Reverse transcription-polymerase chain reaction (RT-PCR) and Western blot; 3. to observe neurons pathologic damages and astrocyte activation in each group. The main findings of our study were: (a) TRPM2-KO had a protective effect on epilepsy; (b) TRPM2-KO improved spatial memory deficits overtime during epilepsy, but it did not improve anxiety; (c) the protective effect probably occurred via the PARP1 downstream signaling pathway; (d) TRPM2-KO could ameliorate epilepsy-induced hippocampal pathological damages and weaken astrocyte activation. These findings may provide a new approach for the treatment of epilepsy and early intervention.