Displaying publications 1 - 20 of 236 in total

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  1. Ong MJY, Khoo CS, Lee YX, Poongkuntran V, Tang CK, Choong YJ, et al.
    Epilepsia Open, 2023 Mar;8(1):236.
    PMID: 36504315 DOI: 10.1002/epi4.12675
    Matched MeSH terms: Epilepsy*
  2. Islam MA, Alam F, Cavestro C, Calcii C, Sasongko TH, Levy RA, et al.
    Autoimmun Rev, 2018 Aug;17(8):755-767.
    PMID: 29885542 DOI: 10.1016/j.autrev.2018.01.025
    BACKGROUND: Autoimmunity is believed to play an important causative role in the pathogenesis of epilepsy. There are evidences for the presence of autoantibodies in patients with epilepsy. To date, many studies have assessed the presence of antiphospholipid antibodies (aPLs) in epilepsy patients, though the relationship has been inconclusive.

    AIMS: The aim of this systematic review and meta-analysis was to evaluate the presence of aPLs in epileptic patients as compared to healthy controls.

    METHODS: Five electronic databases (PubMed, Web of Science, Embase, Scopus and Google Scholar) were searched systematically. Study-specific odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using random-effects model. Quality assessment was carried out by using the modified 9-star Newcastle-Ottawa Scale (NOS). L'Abbé plots were generated to visually inspect heterogeneity while publication bias was evaluated via visualization of contour- enhanced funnel plots, and Begg's and Egger's tests.

    RESULTS: Based on the inclusion criteria, 14 studies were selected involving 1248 epilepsy patients and 800 healthy controls. The majority of epilepsy was categorised as generalised or partial and none had comorbidity with autoimmune diseases. Significant presence of both anticardiolipin (aCL) antibodies (OR: 5.16, 95% CI: 3.21-8.28, p 
    Matched MeSH terms: Epilepsy/etiology*; Epilepsy/pathology*
  3. Sivalingam N
    Family Physician, 1992;4:23-26.
    Matched MeSH terms: Epilepsy
  4. Abualsaud K, Mahmuddin M, Saleh M, Mohamed A
    ScientificWorldJournal, 2015;2015:945689.
    PMID: 25759863 DOI: 10.1155/2015/945689
    Brain status information is captured by physiological electroencephalogram (EEG) signals, which are extensively used to study different brain activities. This study investigates the use of a new ensemble classifier to detect an epileptic seizure from compressed and noisy EEG signals. This noise-aware signal combination (NSC) ensemble classifier combines four classification models based on their individual performance. The main objective of the proposed classifier is to enhance the classification accuracy in the presence of noisy and incomplete information while preserving a reasonable amount of complexity. The experimental results show the effectiveness of the NSC technique, which yields higher accuracies of 90% for noiseless data compared with 85%, 85.9%, and 89.5% in other experiments. The accuracy for the proposed method is 80% when SNR=1 dB, 84% when SNR=5 dB, and 88% when SNR=10 dB, while the compression ratio (CR) is 85.35% for all of the datasets mentioned.
    Matched MeSH terms: Epilepsy/physiopathology*
  5. Khaing M, Lim KS, Tan CT
    Epileptic Disord, 2014 Sep;16(3):370-4.
    PMID: 25166001 DOI: 10.1684/epd.2014.0672
    We report a patient with juvenile myoclonic epilepsy who subsequently developed temporal lobe epilepsy, which gradually became clinically dominant. Video telemetry revealed both myoclonic seizures and temporal lobe seizures. The temporal lobe seizures were accompanied by a focal recruiting rhythm with rapid generalisation on EEG, in which the ictal EEG pattern during the secondary generalised phase was morphologically similar to the ictal pattern during myoclonic seizures. The secondary generalised seizures of the focal epilepsy responded to sodium valproate, similar to the myoclonic epilepsy. In this rare case of coexistent Juvenile Myoclonic Epilepsy and Temporal lobe epilepsy, the possibility of focal epilepsy recruiting a generalised epileptic network was proposed and discussed.
    Matched MeSH terms: Epilepsy, Temporal Lobe/complications*; Epilepsy, Temporal Lobe/pathology; Epilepsy, Temporal Lobe/physiopathology; Myoclonic Epilepsy, Juvenile/complications*; Myoclonic Epilepsy, Juvenile/pathology; Myoclonic Epilepsy, Juvenile/physiopathology
  6. Wo SW, Ong LC, Low WY, Lai PSM
    Epilepsy Res, 2017 10;136:35-45.
    PMID: 28753498 DOI: 10.1016/j.eplepsyres.2017.07.009
    PURPOSE: To systematically examine published literature which assessed the prevalence of academic difficulties in children with epilepsy (CWE) of normal intelligence, and its associating factors.

    METHODS: A search was conducted on five databases for articles published in English from 1980 till March 2015. Included were studies who recruited children (aged 5-18 years), with a diagnosis or newly/recurrent epilepsy, an intelligent quotient (IQ) of ≥70 or attending regular school, with or without a control group, which measured academic achievement using a standardised objective measure, and published in English. Excluded were children with learning difficulties, intellectual disabilities (IQ<70) and other comorbidities such as attention deficits hyperactive disorder or autism. Two pairs of reviewers extracted the data, and met to resolve any differences from the data extraction process.

    RESULTS: Twenty studies were included. The majority of the studies assessed "low achievement" whist only two studies used the IQ-achievement discrepancy definition of "underachievement". Fourteen studies (70%) reported that CWE had significantly lower academic achievement scores compared to healthy controls, children with asthma or reported norms. The remaining six studies (30%) did not report any differences. CWE had stable academic achievement scores over time (2-4 years), even among those whose seizure frequency improved. Higher parental education and children with higher IQ, and had better attention or had a positive attitude towards epilepsy, were associated with higher academic achievement score. Older children were found to have lower academic achievement score.

    CONCLUSIONS: In CWE of normal intelligence, the majority of published literature found that academic achievement was lower than controls or reported norms. The high percentages of low achievement in CWE, especially in the older age group, and the stability of scores even as seizure frequency improved, highlights the need for early screening of learning problems, and continued surveillance.

    Matched MeSH terms: Epilepsy/psychology*
  7. Citation: Consensus Guidelines on the Management of Epilepsy 2017. Epilepsy Council, Malaysia Society of Neuroscience.

    Older version: Citation: Consensus Guidelines on the Management of Epilepsy 2010. Epilepsy Council, Malaysia Society of Neuroscience.
    http://www.neuro.org.my/MSN_GUIDELINE/MSN_GUIDELINE_Consensus%20Guidelines%20on%20the%20Management%20of%20Epilepsy%202010.pdf
    Keywords: CPG
    Matched MeSH terms: Epilepsy*
  8. Kumara Deva M
    Family Practitioner, 1977;2(7):11-13.
    Matched MeSH terms: Epilepsy*
  9. Fong CY, Bleasel A, Dexter MA, Lawson JA, Wong CH
    Epileptic Disord, 2020 Oct 01;22(5):633-641.
    PMID: 33146141 DOI: 10.1684/epd.2020.1211
    Evaluating the candidacy for epilepsy surgery in patients with tuberous sclerosis can be challenging, particularly when non-invasive investigations do not show a clear epileptogenic zone. Stereoencephalography may be useful in such cases. We present a case in which the primary epileptogenic tuber was successfully identified by stereoencephalography, which resulted in seizure freedom following epilepsy surgery. [Published with video sequences].
    Matched MeSH terms: Epilepsy/complications; Epilepsy/diagnosis; Epilepsy/surgery*
  10. 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: Epilepsy
  11. 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: Epilepsy
  12. Tamijani SM, Karimi B, Amini E, Golpich M, Dargahi L, Ali RA, et al.
    Seizure, 2015 Sep;31:155-64.
    PMID: 26362394 DOI: 10.1016/j.seizure.2015.07.021
    Thyroid hormones (THs) L-thyroxine and L-triiodothyronine, primarily known as metabolism regulators, are tyrosine-derived hormones produced by the thyroid gland. They play an essential role in normal central nervous system development and physiological function. By binding to nuclear receptors and modulating gene expression, THs influence neuronal migration, differentiation, myelination, synaptogenesis and neurogenesis in developing and adult brains. Any uncorrected THs supply deficiency in early life may result in irreversible neurological and motor deficits. The development and function of GABAergic neurons as well as glutamatergic transmission are also affected by THs. Though the underlying molecular mechanisms still remain unknown, the effects of THs on inhibitory and excitatory neurons may affect brain seizure activity. The enduring predisposition of the brain to generate epileptic seizures leads to a complex chronic brain disorder known as epilepsy. Pathologically, epilepsy may be accompanied by mitochondrial dysfunction, oxidative stress and eventually dysregulation of excitatory glutamatergic and inhibitory GABAergic neurotransmission. Based on the latest evidence on the association between THs and epilepsy, we hypothesize that THs abnormalities may contribute to the pathogenesis of epilepsy. We also review gender differences and the presumed underlying mechanisms through which TH abnormalities may affect epilepsy here.
    Matched MeSH terms: Epilepsy/metabolism*
  13. Jairoun AA, Al-Himyari SS, Shahwan M, Hassan N, Al-Tamimi S, Jairoun M, et al.
    Front Public Health, 2023;11:1251393.
    PMID: 37766744 DOI: 10.3389/fpubh.2023.1251393
    BACKGROUND: Previous studies have highlighted instances where pharmacists lacked knowledge regarding women's health issues related to epilepsy.

    OBJECTIVES: To assess UAE community pharmacists' knowledge, toward women's issues in epilepsy.

    METHODS: a cross-sectional research method was employed. A team of seven pharmacy students in their final year visited a randomly selected sample of community pharmacies in the UAE and face-to-face interviews were conducted with the pharmacists using a structured questionnaire. The questionnaire includes two parts; Eight questions designed to elicit data about the demographics of the study participants and 12 questions eliciting insights into the participants' knowledge of women's issues in epilepsy.

    RESULTS: A total of 412 community pharmacist were recruited in the study. The overall level of knowledge about women's issues in epilepsy was good and the average knowledge score was 81% with a 95% confidence interval (CI) [79.1, 82.7%]. The results of multivariate analysis showed higher knowledge scores in chain pharmacies (OR 1.37; 95% CI 1.12-1.67), Chief pharmacists (OR 1.44; 95% CI 1.01-2.06), Pharmacists in charge (OR 3.46; 95% CI 2.7-4.45), pharmacists with 1-5 Years of experience (OR 2.87; 95% CI 1.71-4.82), pharmacists with 6-10 Years (OR 2.63; 95% CI 1.58-4.38), pharmacists with >10 years (OR 3.13; 95% CI 2.03-4.83), graduation form regional universities (OR 1.37; 95% CI 1.12-1.67), graduation form international universities (OR 1.73; 95% CI 1.36-2.20) and receiving a training on epilepsy (OR 1.36; 95% CI 1.12-1.67).

    CONCLUSION: While the findings reveal an overall promising level of knowledge among community pharmacists regarding the issues faced by women with epilepsy, pinpointing which clinical and demographic factors have the most significant impact on this knowledge would permit the implementation of tailored educational interventions. Workshops and modules targeting the issues faced by women with epilepsy would further raise the knowledge and competence among community pharmacists in this area, ensuring better pharmaceutical care for this population.

    Matched MeSH terms: Epilepsy*
  14. 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: Epilepsy*
  15. Salih MR, Bahari MB, Shafie AA, Hassali MA, Al-lela OQ, Abd AY, et al.
    Seizure, 2012 Dec;21(10):764-9.
    PMID: 22939458 DOI: 10.1016/j.seizure.2012.08.005
    Aims of this study were to estimate the first-year medical care costs of newly diagnosed children with structural-metabolic epilepsy and to determine the cost-driving factors in the selected population.
    Matched MeSH terms: Epilepsy/economics*; Epilepsy/epidemiology*
  16. Kwan P, Cabral-Lim L, D'Souza W, Jain S, Lee BI, Liao W, et al.
    Epilepsia, 2015 May;56(5):667-73.
    PMID: 25823580 DOI: 10.1111/epi.12957
    The Asia-Oceanian region is the most populous region in the world. Although there has been substantial economic development and improvement in health services in recent years, epilepsy remains generally an underrecognized and understudied condition. To help promote research in the region, the Commission on Asian and Oceanian Affairs (CAOA) of the International League Against Epilepsy (ILAE) appointed the Research Task Force (RTF) to facilitate the development of research priorities for the region. Research that focuses on issues that are unique or of particular importance in the Asia-Oceanian region is encouraged, and that captures the impact of the dynamic socioeconomic changes taking place in the region is emphasized. Based on these considerations, we propose research "dimensions" as priorities within the Asia-Oceanian region. These are studies (1) that would lead to fuller appreciation of the health burden of epilepsy, particularly the treatment gap; (2) that would lead to better understanding of the causes of epilepsy; (3) that would alleviate the psychosocial consequences of epilepsy; (4) that would develop better therapies and improved therapeutic outcomes; and (5) that would improve the research infrastructure.
    Matched MeSH terms: Epilepsy/epidemiology; Epilepsy/therapy*
  17. Peng KL
    Aust N Z J Psychiatry, 1983 Dec;17(4):397-9.
    PMID: 6581801
    The causal explanation given by a 24-year-old Malay woman from a low socioeconomic class for her epilepsy is described. This case illustrates how cultural explanations can protect an individual from the stigma of illness. The Malay concept of the supernatural and the causation of illness is discussed.
    Matched MeSH terms: Epilepsy/etiology; Epilepsy/psychology*
  18. Thuy Le MA, Fong SL, Lim KS, Gunadharma S, Sejahtera DP, Visudtibhan A, et al.
    Seizure, 2019 Jul;69:51-56.
    PMID: 30974407 DOI: 10.1016/j.seizure.2019.04.002
    PURPOSE: This survey was performed to determine the availability of epilepsy surgery, and understand the limiting factors to epilepsy surgery in ASEAN countries with total of 640 million population.

    METHOD: A cross-sectional survey was completed by national representatives in all ASEAN countries (Brunei, Cambodia, East Timor, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam).

    RESULTS: Overall facilities for initial epilepsy pre-surgical evaluation are available in most countries, but further non-invasive and invasive investigations are limited. Three countries (Brunei, Cambodia, and East Timor) have no epilepsy center, and 2 countries (Laos, Myanmar) have level 2 centers doing tumor surgery only. Level-3 epilepsy centers are available in 6 countries (Indonesia, Malaysia, Philippine, Singapore, Thailand, Vietnam); only 5 countries (Indonesia, Malaysia, Philippine, Singapore, Thailand) has at least one level-4 epilepsy care facility. Indonesia with 261 million population only has one level 3 and another level 4 center. The costs of presurgical evaluation and brain surgery vary within and among the countries. The main barriers towards epilepsy surgery in ASEAN include lack of expertise, funding and facilities.

    CONCLUSIONS: Epilepsy surgery is underutilized in ASEAN with low number of level 3 centers, and limited availability of advanced presurgical evaluation. Lack of expertise, facilities and funding may be the key factors contributing to the underutilization.

    Matched MeSH terms: Epilepsy/economics*; Epilepsy/surgery*
  19. Lim, Kheng-Seang, Sherrini Ahmad Bazir Ahmad, Vairavan Narayanan, Kartini Rahmat, Norlisah Mohd Ramli, Mun, Kein-Seong, et al.
    Neurology Asia, 2017;22(4):299-305.
    MyJurnal
    Background and Objective: There is a great challenge to establish a level 4 epilepsy care offering
    complete evaluation for epilepsy surgery including invasive monitoring in a resource-limited country.
    This study aimed to report the setup of a level 4 comprehensive epilepsy program in Malaysia and the
    outcome of epilepsy surgery over the past 4 years.

    Methods: This is a retrospective study analyzing
    cases with intractable epilepsy in a comprehensive epilepsy program in University Malaya Medical
    Center (UMMC), Kuala Lumpur, from January 2012 to August 2016.

    Results: A total of 92 cases
    had comprehensive epilepsy evaluation from January 2012 till August 2016. The mean age was 35.57
    years old (range 15-59) and 54 (58.7%) were male. There were 17 cases having epilepsy surgery
    after stage-1 evaluation. Eleven cases had mesial temporal sclerosis and 81% achieved Engel class
    I surgical outcome. Six cases had lesionectomy and 60% had Engel class I outcome. A total of 16
    surgeries were performed after stage-2 evaluation, including invasive EEG monitoring in 9 cases.
    Among those with surgery performed more than 12 months from the time of data collection, 5/10
    (50%) achieved Engel I outcome, whereas 2 (20%) had worthwhile improvement (Engel class III)
    with 75% and 90% seizure reduction.

    Conclusion: Level 4 epilepsy care has an important role and is possible with joint multidisciplinary
    effort in a middle-income country like Malaysia despite resource limitation.
    Matched MeSH terms: Drug Resistant Epilepsy; Epilepsy; Epilepsy, Temporal Lobe
  20. 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: Epilepsy/diagnosis*; Epilepsy/physiopathology
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