Displaying publications 1 - 20 of 203 in total

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  1. Lee EL
    Family Practitioner, 1983;6:39-40.
    Matched MeSH terms: Seizures, Febrile
  2. Kumara Deva M
    Family Practitioner, 1977;2(7):11-13.
    Matched MeSH terms: Seizures*
  3. Audrey C, Lim KS, Ahmad Zaki R, Fong SL, Chan CY, Sathis Kumar T, et al.
    Epilepsy Res, 2022 Nov;187:107033.
    PMID: 36274423 DOI: 10.1016/j.eplepsyres.2022.107033
    OBJECTIVES: Prevalence of seizures in brain tumors vary substantially between studies even with similar histopathological types. We aimed to identify the seizure prevalence of the commonest types of brain tumors.

    METHODS: Systematic computerized search of PubMed, Embase, and Web of Science were performed. The meta-analysis of pooled prevalence and 95 % confidence interval (CI) for tumor-related seizures were calculated by using a random effect model. Based on the 2014 epilepsy definition, a mean seizure prevalence of 60 % is used to indicate high seizure prevalence in this study.

    RESULTS: 74 studies that reported seizure prevalence with 23,116 patients were included in this meta-analysis. These tumors has higher seizure incidence rate (at least 60 %) with pooled prevalence of 63 % for adult with low-grade astrocytoma (95 % CI: 57-68 %), 65 % for oligodendroglioma (95% CI: 57-72 %), 72 % for oligoastrocytoma (95 % CI: 67-77 %), 81 % for ganglioglioma (95 % CI: 66-97 %) and 94 % for DNET (94 % CI: 83-100 %).

    CONCLUSION: This study highlights the type of brain tumors that carry a high seizure prevalence. Screening for subtle seizures and early management of seizures may be beneficial in patients with low-grade astrocytoma (adult), oligodendroglioma, oligoastrocytoma, ganglioglioma or DNET brain tumor.

    Matched MeSH terms: Seizures/etiology
  4. Arulsamy A, Shaikh MF
    ACS Chem Neurosci, 2020 07 01;11(13):1900-1908.
    PMID: 32479057 DOI: 10.1021/acschemneuro.0c00301
    Post-traumatic epilepsy (PTE) is one of the detrimental outcomes of traumatic brain injury (TBI), resulting in recurrent seizures that impact daily life. However, the pathological relationship between PTE and TBI remains unclear, and commonly prescribed antiepileptic drugs (AED) are ineffective against PTE. Fortunately, emerging research implicates neuroinflammation, particularly, tumor necrosis factor-α (TNF-α), as the key mediator for PTE development. Thus, this review aims to examine the available literature regarding the role of TNF-α in PTE pathology and, subsequently, evaluate TNF-α as a possible target for its treatment. A comprehensive literature search was conducted on four databases including PubMed, CINAHL, Embase, and Scopus. Articles with relevance in investigating TNF-α expression in PTE were considered in this review. Critical evaluation of four articles that met the inclusion criteria suggests a proportional relationship between TNF-α expression and seizure susceptibilit and that neutralization or suppression of TNF-α release results in reduced susceptibility to seizures. In conclusion, this review elucidates the importance of TNF-α expression in epileptogenesis postinjury and urges future research to focus more on clinical studies involving TNF-α, which may provide clearer insight into PTE prevention, therefore improving the lives of PTE patients.
    Matched MeSH terms: Seizures/drug therapy; Seizures/etiology
  5. Anuar MA, Zainal Abidin M', Tan SH, Yeap CF, Yahaya NA
    Pediatr Neurol, 2024 Jan;150:10-14.
    PMID: 37931500 DOI: 10.1016/j.pediatrneurol.2023.10.004
    BACKGROUND: Epilepsy has a high incidence among infants during their first year of life, yet the prognosis can vary significantly. Although considerable research has been conducted on infantile spasms, studies examining infantile-onset epilepsy, excluding infantile spasms, remain limited, particularly concerning the factors influencing outcomes. Therefore, our study aims to elucidate seizure control, developmental outcomes, and prognostic factors in infants with epilepsy during their first year of life, within a single-center study in Malaysia.

    METHODS: We retrieved data from patients who experienced seizures before age 12 months and were followed for over two years, using electronic patient records at Hospital Raja Perempuan Zainab II in Kelantan, a state in Malaysia's east coast. We retrospectively reviewed these records and assessed clinical outcomes based on the last follow-up.

    RESULTS: Of 75 patients, 61 (81.3%) achieved good seizure control or remission. At the last follow-up, 24 (32%) exhibited developmental delay, whereas 19 (25.3%) displayed abnormal neuroimaging. Patients with abnormal background electroencephalographic (EEG) activity, as well as abnormal radiological findings, were more likely to experience poor seizure control and unfavorable developmental outcomes (P 

    Matched MeSH terms: Seizures/complications; Seizures/etiology
  6. Aithala, Gururaj
    Medical Health Reviews, 2008;2008(1):5-16.
    MyJurnal
    Epilepsy is a common neurological disorder in childhood. In a majority, the cause of epilepsy remains a mystery in spite of extensive investigations. The aim of drug treatment is to effectively stop the seizures with minimum of side effects, causing no impairment of long term learning abilities of the child. Up to 30% of children with epilepsy may continue to have seizures in spite of adequate drug therapy. In this review, an overview of the recent advances that affect the diagnosis, prognosis and therapy of childhood epilepsy including the dilemmas of everyday practice is presented.
    Matched MeSH terms: Seizures
  7. Habib MA, Ibrahim F, Mohktar MS, Kamaruzzaman SB, Lim KS
    Clin Neurophysiol, 2020 03;131(3):642-654.
    PMID: 31978849 DOI: 10.1016/j.clinph.2019.11.058
    OBJECTIVE: This study aimed to present a new ictal component selection technique, named as recursive ICA-decomposition for ictal component selection (RIDICS), for potential application in epileptogenic zone localization.

    METHODS: The proposed technique decomposes ictal EEG recursively, eliminates a few unwanted components in every recursive cycle, and finally selects the most significant ictal component. Back-projected EEG, regenerated from that component, was used for source estimation. Fifty sets of simulated EEGs and 24 seizures in 8 patients were analyzed. Dipole sources of simulated-EEGs were compared with a known dipole location whereas epileptogenic zones of the seizures were compared with their corresponding sites of successful surgery. The RIDICS technique was compared with a conventional technique.

    RESULTS: The RIDICS technique estimated the dipole sources at an average distance of 12.86 mm from the original dipole location, shorter than the distances obtained using the conventional technique. Epileptogenic zones of the patients, determined by the RIDICS technique, were highly concordant with the sites of surgery with a concordance rate of 83.33%.

    CONCLUSIONS: Results show that the RIDICS technique can be a promising quantitative technique for ictal component selection.

    SIGNIFICANCE: Properly selected ictal component gives good approximation of epileptogenic zone, which eventually leads to successful epilepsy surgery.

    Matched MeSH terms: Seizures
  8. Ong JS, Wong SN, Arulsamy A, Watterson JL, Shaikh MF
    Curr Neuropharmacol, 2022;20(5):950-964.
    PMID: 34749622 DOI: 10.2174/1570159X19666211108153001
    BACKGROUND: Epilepsy is a devastating neurological disorder that affects nearly 70 million people worldwide. Epilepsy causes uncontrollable, unprovoked and unpredictable seizures that reduce the quality of life of those afflicted, with 1-9 epileptic patient deaths per 1000 patients occurring annually due to sudden unexpected death in epilepsy (SUDEP). Predicting the onset of seizures and managing them may help patients from harming themselves and may improve their well-being. For a long time, electroencephalography (EEG) devices have been the mainstay for seizure detection and monitoring. This systematic review aimed to elucidate and critically evaluate the latest advancements in medical devices, besides EEG, that have been proposed for the management and prediction of epileptic seizures. A literature search was performed on three databases, PubMed, Scopus and EMBASE.

    METHODS: Following title/abstract screening by two independent reviewers, 27 articles were selected for critical analysis in this review.

    RESULTS: These articles revealed ambulatory, non-invasive and wearable medical devices, such as the in-ear EEG devices; the accelerometer-based devices and the subcutaneous implanted EEG devices might be more acceptable than traditional EEG systems. In addition, extracerebral signalbased devices may be more efficient than EEG-based systems, especially when combined with an intervention trigger. Although further studies may still be required to improve and validate these proposed systems before commercialization, these findings may give hope to epileptic patients, particularly those with refractory epilepsy, to predict and manage their seizures.

    CONCLUSION: The use of medical devices for epilepsy may improve patients' independence and quality of life and possibly prevent sudden unexpected death in epilepsy (SUDEP).

    Matched MeSH terms: Seizures
  9. Akyuz E, Arulsamy A, Hasanli S, Yilmaz EB, Shaikh MF
    Epilepsy Res, 2023 Feb;190:107093.
    PMID: 36652852 DOI: 10.1016/j.eplepsyres.2023.107093
    Epilepsy is one of the most recognizable neurological diseases, globally. Epilepsy may be accompanied by various complications, including vision impairments, which may severely impact one's quality of life. These visual phenomena may occur in the preictal, ictal and/or postictal periods of seizures. Examples of epilepsy associated visual phenomena include visual aura, visual hallucinations, transient visual loss and amaurosis (blindness). These ophthalmologic signs/symptoms of epilepsy may be temporary or permanent and may vary depending of the type of epilepsy and location of the seizure foci (occipital or temporal lobe). Some visual phenomena may even be utilized to diagnose the epilepsy type, although solely depending on visual symptoms for diagnosis may lead to mistreatment. Some antiseizure medications (ASMs) may also contribute to certain visual disturbances, thereby impacting its therapeutic efficiency for patients with epilepsy (PWE). Although the development of visual comorbidities has been observed diversely among PWE, there may still be a lack of understanding on their relevance and manifestation in epilepsy, which may contribute to the rate of misdiagnosis and the current scarcity in therapeutic relieve. Therefore, this mini narrative review aimed to discuss the common epilepsy associated visual phenomena, based on the available literature. This review also showcased the relationship between the type of visual complications and the site of seizure onset, as well as compared the visual phenomena between occipital lobe epilepsy and temporal lobe epilepsy. Evaluation of these findings may be crucial in reducing the risk of permanent seizure/epilepsy related vision deficits among PWE.
    Matched MeSH terms: Seizures/complications
  10. Seth EA, Watterson J, Xie J, Arulsamy A, Md Yusof HH, Ngadimon IW, et al.
    Epilepsia Open, 2024 Feb;9(1):41-59.
    PMID: 37881157 DOI: 10.1002/epi4.12854
    A reliable seizure detection or prediction device can potentially reduce the morbidity and mortality associated with epileptic seizures. Previous findings indicating alterations in cardiac activity during seizures suggest the usefulness of cardiac parameters for seizure detection or prediction. This study aims to examine available studies on seizure detection and prediction based on cardiac parameters using non-invasive wearable devices. The Embase, PubMed, and Scopus databases were used to systematically search according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Human studies that evaluated seizure detection or prediction based on cardiac parameters collected using wearable devices were included. The QUADAS-2 tool and proposed standards for validation for seizure detection devices were used for quality assessment. Twenty-four articles were identified and included in the analysis. Twenty studies evaluated seizure detection algorithms, and four studies focused on seizure prediction. Most studies used either a wrist-worn or chest-worn device for data acquisition. Among the seizure detection studies, cardiac parameters utilized for the algorithms mainly included heart rate (HR) (n = 11) or a combination of HR and heart rate variability (HRV) (n = 6). HR-based seizure detection studies collectively reported a sensitivity range of 56%-100% and a false alarm rate (FAR) of 0.02-8/h, with most studies performing retrospective validation of the algorithms. Three of the seizure prediction studies retrospectively validated multimodal algorithms, combining cardiac features with other physiological signals. Only one study prospectively validated their seizure prediction algorithm using HRV extracted from ECG data collected from a custom wearable device. These studies have demonstrated the feasibility of using cardiac parameters for seizure detection and prediction with wearable devices, with varying algorithmic performance. Many studies are in the proof-of-principle stage, and evidence for real-time detection or prediction is currently limited. Future studies should prioritize further refinement of the algorithm performance with prospective validation using large-scale longitudinal data. PLAIN LANGUAGE SUMMARY: This systematic review highlights the potential use of wearable devices, like wristbands, for detecting and predicting seizures via the measurement of heart activity. By reviewing 24 articles, it was found that most studies focused on using heart rate and changes in heart rate for seizure detection. There was a lack of studies looking at seizure prediction. The results were promising but most studies were not conducted in real-time. Therefore, more real-time studies are needed to verify the usage of heart activity-related wearable devices to detect seizures and even predict them, which will be beneficial to people with epilepsy.
    Matched MeSH terms: Seizures/diagnosis
  11. Dang J, Paudel YN, Yang X, Ren Q, Zhang S, Ji X, et al.
    ACS Chem Neurosci, 2021 07 07;12(13):2542-2552.
    PMID: 34128378 DOI: 10.1021/acschemneuro.1c00314
    The lack of disease-modifying therapeutic strategies against epileptic seizures has caused a surge in preclinical research focused on exploring and developing novel therapeutic candidates for epilepsy. Compounds from traditional Chinese medicines (TCMs) have gained much attention for a plethora of neurological diseases, including epilepsy. Herein, for the first time, we evaluated the anticonvulsive effects of schaftoside (SS), a TCM, on pentylenetetrazol (PTZ)-induced epileptic seizures in zebrafish and examined the underlying mechanisms. We observed that SS pretreatments significantly suppressed seizure-like behavior and prolonged the onset of seizures. Zebrafish larvae pretreated with SS demonstrated downregulation of c-fos expression during seizures. PTZ-induced upregulation of apoptotic cells was decreased upon pretreatment with SS. Inflammatory phenomena during seizure progression including the upregulation of interleukin 6 (IL-6), interleukin 1 beta (IL-1β), and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) were downregulated upon pretreatment with SS. The PTZ-induced recruitment of immunocytes was in turn reduced upon SS pretreatment. Moreover, SS pretreatment modulated oxidative stress, as demonstrated by decreased levels of catalase (CAT) and increased levels of glutathione peroxidase-1a (GPx1a) and manganese superoxide dismutase (Mn-SOD). However, pretreatment with SS modulated the PTZ-induced downregulation of the relative enzyme activity of CAT, GPx, and SOD. Hence, our findings suggest that SS pretreatment ameliorates PTZ-induced seizures, suppresses apoptosis, and downregulates the inflammatory response and oxidative stress, which potentially protect against further seizures in zebrafish.
    Matched MeSH terms: Seizures/chemically induced; Seizures/drug therapy
  12. Paudel YN, Khan SU, Othman I, Shaikh MF
    ACS Chem Neurosci, 2021 09 15;12(18):3288-3302.
    PMID: 34463468 DOI: 10.1021/acschemneuro.0c00825
    Glycyrrhizin (GL) is a well-known pharmacological inhibitor of high mobility group box 1 (HMGB1) and is abundantly present in the licorice root (Glycyrrhiza radix). HMGB1 protein, a key mediator of neuroinflammation, has been implicated in several neurological disorders, including epilepsy. Epilepsy is a devastating neurological disorder with no effective disease-modifying treatment strategies yet, suggesting a pressing need for exploring novel therapeutic options. In the current investigation, using a second hit pentylenetetrazol (PTZ) induced chronic seizure model in adult zebrafish, regulated mRNA expression of HMGB1 was inhibited by pretreatment with GL (25, 50, and 100 mg/kg, ip). A molecular docking study suggests that GL establishes different binding interactions with the various amino acid chains of HMGB1 and Toll-like receptor-4 (TLR4). Our finding suggests that GL pretreatment reduces/suppresses second hit PTZ induced seizure, as shown by the reduction in the seizure score. GL also regulates the second hit PTZ induced behavioral impairment and rescued second hit PTZ related memory impairment as demonstrated by an increase in the inflection ratio (IR) at the 3 h and 24 h T-maze trial. GL inhibited seizure-induced neuronal activity as demonstrated by reduced C-fos mRNA expression. GL also modulated mRNA expression of BDNF, CREB-1, and NPY. The possible mechanism underlying the anticonvulsive effect of GL could be attributed to its anti-inflammatory activity, as demonstrated by the downregulated mRNA expression level of HMGB1, TLR4, NF-kB, and TNF-α. Overall, our finding suggests that GL exerts an anticonvulsive effect and ameliorates seizure-related memory disruption plausibly through regulating of the HMGB1-TLR4-NF-kB axis.
    Matched MeSH terms: Seizures/chemically induced; Seizures/drug therapy
  13. Sahu R, Dash SR, Cacha LA, Poznanski RR, Parida S
    J Integr Neurosci, 2020 Mar 30;19(1):1-9.
    PMID: 32259881 DOI: 10.31083/j.jin.2020.01.24
    Electroencephalography is the recording of brain electrical activities that can be used to diagnose brain seizure disorders. By identifying brain activity patterns and their correspondence between symptoms and diseases, it is possible to give an accurate diagnosis and appropriate drug therapy to patients. This work aims to categorize electroencephalography signals on different channels' recordings for classifying and predicting epileptic seizures. The collection of the electroencephalography recordings contained in the dataset attributes 179 information and 11,500 instances. Instances are of five categories, where one is the symptoms of epilepsy seizure. We have used traditional, ensemble methods and deep machine learning techniques highlighting their performance for the epilepsy seizure detection task. One dimensional convolutional neural network, ensemble machine learning techniques like bagging, boosting (AdaBoost, gradient boosting, and XG boosting), and stacking is implemented. Traditional machine learning techniques such as decision tree, random forest, extra tree, ridge classifier, logistic regression, K-Nearest Neighbor, Naive Bayes (gaussian), and Kernel Support Vector Machine (polynomial, gaussian) are used for classifying and predicting epilepsy seizure. Before using ensemble and traditional techniques, we have preprocessed the data set using the Karl Pearson coefficient of correlation to eliminate irrelevant attributes. Further accuracy of classification and prediction of the classifiers are manipulated using k-fold cross-validation methods and represent the Receiver Operating Characteristic Area Under the Curve for each classifier. After sorting and comparing algorithms, we have found the convolutional neural network and extra tree bagging classifiers to have better performance than all other ensemble and traditional classifiers.
    Matched MeSH terms: Seizures/diagnosis*; Seizures/physiopathology
  14. Siang LH, Arulsamy A, Yoon YK, Shaikh MF
    Curr Neuropharmacol, 2022;20(10):1925-1940.
    PMID: 34517803 DOI: 10.2174/1570159X19666210913120637
    Epilepsy is a devastating neurological disorder. Current anti-convulsant drugs are only effective in about 70% of patients, while the rest remain drug-resistant. Thus, alternative methods have been explored to control seizures in these drug-resistant patients. One such method may be through the utilization of fruit phytochemicals. These phytochemicals have been reported to have beneficial properties such as anti-convulsant, anti-oxidant, and anti-inflammatory activities. However, some fruits may also elicit harmful effects. This review aims to summarize and elucidate the anti- or pro-convulsant effects of fruits used in relation to seizures in hopes of providing a good therapeutic reference to epileptic patients and their carers. Three databases, SCOPUS, ScienceDirect, and PubMed, were utilized for the literature search. Based on the PRISMA guidelines, a total of 40 articles were selected for critical appraisal in this review. Overall, the extracts and phytochemicals of fruits managed to effectively reduce seizure activities in various preclinical seizure models, acting mainly through the activation of the inhibitory neurotransmission and blocking the excitatory neurotransmission. Only star fruit has been identified as a pro-convulsant fruit due to its caramboxin and oxalate compounds. Future studies should focus more on utilizing these fruits as possible treatment strategies for epilepsy.
    Matched MeSH terms: Seizures/chemically induced; Seizures/drug therapy
  15. Anuar MA, Lee JX, Musa H, Abd Hadi D, Majawit E, Anandakrishnan P, et al.
    Brain Dev, 2023 Nov;45(10):547-553.
    PMID: 37661525 DOI: 10.1016/j.braindev.2023.06.004
    INTRODUCTION: Since the emergence of COVID-19, we have experienced potent variants and sub-variants of the virus with non-specific neurological manifestations. We observed a surge of the Omicron variant of COVID-19 patients with neurological manifestations where less cases of multisystem inflammatory syndrome in children (MIS-C) were reported. This article describes our experience of children with severe and rare neurological manifestations following COVID-19 infection.

    METHODS: This is a retrospective observational case series of patients under 18 years old who fulfilled the WHO COVID-19 case definition and were referred to our paediatric neurology unit at Hospital Tunku Azizah Kuala Lumpur. Their demographic data, neurological symptoms, laboratory and supporting investigations, neuroimaging, treatment and outcomes were collected and analysed.

    RESULTS: There were eleven patients with neurological manifestations who fulfilled the WHO COVID-19 case definition. Nine patients presented with seizures and/or encephalopathy, one patient with eye opsoclonus and another patient with persistent limbs myokymia. Based on the history, clinical, electrophysiological and radiological findings, two of them had febrile infection-related epilepsy syndrome, two had acute disseminated encephalomyelitis, two had acute necrotising encephalopathy of childhood, one each had hemiconvulsion-hemiplegia-epilepsy syndrome, acute encephalopathy with bilateral striatal necrosis, hemi-acute encephalopathy with biphasic seizures and reduced diffusion, infection-associated opsoclonus and myokymia.

    CONCLUSIONS: This case series highlighted a wide spectrum of neurological manifestations of COVID-19 infection. Early recognition and prompt investigations are important to provide appropriate interventions. It is essential that these investigations should take place in a timely fashion and COVID-19 quarantine period should not hinder the confirmation of various presenting clinical syndromes.

    Matched MeSH terms: Seizures/etiology; Seizures/therapy
  16. Juvale IIA, Che Has AT
    Eur J Neurosci, 2021 03;53(6):1998-2026.
    PMID: 33306252 DOI: 10.1111/ejn.15079
    Epilepsy is one of the oldest known neurological disorders and is characterized by recurrent seizure activity. It has a high incidence rate, affecting a broad demographic in both developed and developing countries. Comorbid conditions are frequent in patients with epilepsy and have detrimental effects on their quality of life. Current management options for epilepsy include the use of anti-epileptic drugs, surgery, or a ketogenic diet. However, more than 30% of patients diagnosed with epilepsy exhibit drug resistance to anti-epileptic drugs. Further, surgery and ketogenic diets do little to alleviate the symptoms of patients with pharmacoresistant epilepsy. Thus, there is an urgent need to understand the underlying mechanisms of pharmacoresistant epilepsy to design newer and more effective anti-epileptic drugs. Several theories of pharmacoresistant epilepsy have been suggested over the years, the most common being the gene variant hypothesis, network hypothesis, multidrug transporter hypothesis, and target hypothesis. In our review, we discuss the main theories of pharmacoresistant epilepsy and highlight a possible interconnection between their mechanisms that could lead to the development of novel therapies for pharmacoresistant epilepsy.
    Matched MeSH terms: Seizures/drug therapy
  17. Paranjothy M
    Med J Malaysia, 1978 Sep;33(1):17-9.
    PMID: 750889
    Matched MeSH terms: Seizures/chemically induced*
  18. GRIFFITH DH
    Med J Malaya, 1958 Dec;13(2):125-38.
    PMID: 13632210
    Matched MeSH terms: Seizures*
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