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Journal articles on the topic 'Epileptic Seizure'
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1
Rangarajan, Punitha, Kulandaiammal Moorthy, and Arunan Subbiah. "Observational study on the utilization pattern of adjuvant anti-epileptics and their adverse effects." International Journal of Basic & Clinical Pharmacology 9, no. 1 (December 24, 2019): 170. http://dx.doi.org/10.18203/2319-2003.ijbcp20195781.
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Background: Epilepsy is a disease characterized by an enduring predisposition to generate epileptic seizures. Pharmacological therapy is the cornerstone of treatment of epilepsy. In more than 50% patients seizure not controlled with first-line anti-epileptic drugs so added with adjuvant drugs. Therefore adjuvant anti-epileptic drugs play an important role in preventing seizure remission in known epilepsy patients. Observational study was to evaluate the utilisation pattern of adjuvant anti-epileptic drugs and to assess their clinical correlation and observe the adverse effects of the adjuvant anti-epileptics.Methods: Eligible 100 patients who attended the neurology outpatient department where enrolled in the study. Demographic data, type of epilepsy, presence or absence of seizure episode (4 months), adjuvant anti-epileptic prescribed along with the first-line drugs and adverse effects were noted. Clinical correlation and rationale for the usage of adjuvant anti-epileptics were assessed. Descriptive statistics used for statistical analysis.Results: The most common types of seizures were generalised tonic clonic seizures (41%) and complex partial seizures (37%). Most commonly used 1st line drug was phenytoin tablet. Most common adjuvant anti-epileptics used were clonazepam (30), clobazam (24) tablets. Most common adverse effect noted was dizziness (31%).Conclusions: Tablet clonazepam is effective adjunct for tonic clonic seizures. Clobazam table is recommended as add-on drug for focal and generalised seizures. Adjuvant anti-epileptic drugs decrease seizure remission with fewer tolerable adverse effects.
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Schiefer, Johannes, and Rainer Surges. "Notfallversorgung und Erstbehandlung epileptischer Anfälle im Erwachsenenalter." DMW - Deutsche Medizinische Wochenschrift 144, no. 02 (January 2019): 83–92. http://dx.doi.org/10.1055/a-0660-3174.
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AbstractSuspected epileptic seizures are a frequent cause of emergency hospital care. After single seizures, the emergency management includes safety measures and diagnostic efforts to distinguish epileptic seizures from its manifold mimics and to possibly detect acute causes of epileptic seizures. Convulsive status epilepticus requires rapid anticonvulsant treatment according to established protocols and diagnostics to rule out underlying acute brain diseases. After a first seizure, typical EEG- and MRI findings may indicate an elevated recurrence risk, thereby justifying the ultimate diagnosis of epilepsy and initiation of anticonvulsant therapy. This article reviews the recent definition of epilepsy, summarizes clinical characteristics of epileptic seizures and its mimics and provides an overview of established therapies of single convulsive seizures, convulsive status epilepticus and early care of adults after first unprovoked seizures.
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Catenoix, H., R. Marignier, C. Ritleng, M. Dufour, F. Mauguière, C. Confavreux, and S. Vukusic. "Multiple sclerosis and epileptic seizures." Multiple Sclerosis Journal 17, no. 1 (September 22, 2010): 96–102. http://dx.doi.org/10.1177/1352458510382246.
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Background: The association between epilepsy and multiple sclerosis (MS) is not a coincidence. Objective: Our objective was to compare MS patients with or without history of seizures. Methods: In a population of 5041 MS patients, we identified 102 (2%) patients with epileptic seizures. In 67 patients (1.3%), epileptic seizure could not be explained by any cause other than MS. Results: In these 67 patients, the median age at occurrence of the first epileptic seizure was 33 years. Epilepsy was the initial clinical manifestation of MS in seven patients. In total, 62 patients (92.5%) presented only one or a few seizures, and 18 patients (27%) presented at least one episode of status epilepticus, fatal in two. Compared with MS patients without epilepsy, there was no difference in gender, type of MS course and time from onset of MS to the progressive phase. Conversely, the median age at MS onset was earlier (25.0 years vs. 30, p < 0.0001) and there was a trend for a shorter time from MS onset to non-reversible disability. Conclusions: Our study confirms an increased risk of epileptic seizures in MS patients. It underlines that seizures may be the first observable symptom in MS and the frequency and seriousness of status epilepticus.
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Pawar, Sanjay Shamrao, and Sangeeta Rajendra Chougule. "Classification and Severity Measurement of Epileptic Seizure using Intracranial Electroencephalogram (iEEG)." International Journal of Innovative Technology and Exploring Engineering 10, no. 2 (December 10, 2020): 36–41. http://dx.doi.org/10.35940/ijitee.b8249.1210220.
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The Epileptic seizure is one of major neurological brain disorders and about 50 million of world’s population is affected by it. Electroencephalography is medical test which records brain signal by mounting electrodes on scalp or brain cortex to diagnosis seizure. Scalp Electroencephalography has low spatial resolution and presence of external artifact as compared to Intracranial Electroencephalography. In Intracranial Electroencephalography strip, grid and depth type of electrodes are implanted on cortex of brain by surgery to measure brain signal. Analysis of brain signal was carried out in past in diagnosis of Epileptic seizure. Seizure classification and Severity measurement of Epileptic Seizure are still challenging areas of research. Seizures are classified as focal seizure, generalized and secondary generalized seizure depending upon the area of brain which it generates and how it spreads. Classification of seizure helps in treatment of seizure and during brain surgery to operate on brain part which is responsible for continuous seizures generation. Developed seizure classification algorithm classifies seizures as focal Seizure, generalized Seizure and secondary generalized seizure depending on the percentage of iEEG electrodes detecting seizure activity. Seizure severity measurement scale is developed by modification in National Hospital Seizure Severity Scale. Seizures are graded as Mild seizure, Moderate seizure and severe seizure depending on its severity. Seizure Classification and Seizure Severity Measurement improves life quality of Epileptic patients by proper drug management.
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Zambrana-Vinaroz, David, Jose Maria Vicente-Samper, Juliana Manrique-Cordoba, and Jose Maria Sabater-Navarro. "Wearable Epileptic Seizure Prediction System Based on Machine Learning Techniques Using ECG, PPG and EEG Signals." Sensors 22, no. 23 (December 1, 2022): 9372. http://dx.doi.org/10.3390/s22239372.
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Epileptic seizures have a great impact on the quality of life of people who suffer from them and further limit their independence. For this reason, a device that would be able to monitor patients’ health status and warn them for a possible epileptic seizure would improve their quality of life. With this aim, this article proposes the first seizure predictive model based on Ear EEG, ECG and PPG signals obtained by means of a device that can be used in a static and outpatient setting. This device has been tested with epileptic people in a clinical environment. By processing these data and using supervised machine learning techniques, different predictive models capable of classifying the state of the epileptic person into normal, pre-seizure and seizure have been developed. Subsequently, a reduced model based on Boosted Trees has been validated, obtaining a prediction accuracy of 91.5% and a sensitivity of 85.4%. Thus, based on the accuracy of the predictive model obtained, it can potentially serve as a support tool to determine the status epilepticus and prevent a seizure, thereby improving the quality of life of these people.
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Bhardwaj, Ankit, Atma Ram Sharma, and Sarla Sharma. "Cefixime induce non convulsive status epileptics: a neurotoxic effect." International Journal of Basic & Clinical Pharmacology 8, no. 10 (September 25, 2019): 2341. http://dx.doi.org/10.18203/2319-2003.ijbcp20194284.
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Nonconvulsive status epileptics comprises a group of syndromes that display a great diversity regarding response to anticonvulsants ranging from virtually self-limiting variants to entirely refractory forms cephalosporins are thought to provoke seizure through inhibitory effects on gamma-aminobutyric acid (GABA) transmission and GABA receptors. Interference with GABA transmission result in pre-disposition towards excitatory neurotransmission, which can leads to seizures. Antibiotics can alter the serum concentration of anti-epileptic, resulting in seizures and anti-epileptic drugs toxicity.
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Sills, Graeme J. "Seizures Beget Seizures: A Lack of Experimental Evidence and Clinical Relevance Fails to Dampen Enthusiasm." Epilepsy Currents 7, no. 4 (July 2007): 103–4. http://dx.doi.org/10.1111/j.1535-7511.2007.00189.x.
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Three Brief Epileptic Seizures Reduce Inhibitory Synaptic Currents, GABAACurrents, and GABAA-Receptor Subunits. Evans MS, Cady CJ, Disney KE, Yang L, LaGuardia JJ. Epilepsia 2006;4710):1655–1664. PURPOSE: Cellular mechanisms activated during seizures may exacerbate epilepsy. γ-Aminobutyric acid (GABA) is the major inhibitory neurotransmitter in brain, and we hypothesized that brief epileptic seizures may reduce GABA function. METHODS: We used audiogenic seizures (AGSs) in genetically epilepsy-prone rats (GEPRs) to investigate effects of seizures on GABA-mediated inhibition in the presence of epilepsy. GEPRs are uniformly susceptible to AGSs beginning at 21 postnatal days. AGSs are brief convulsions lasting 20 s, and they begin in inferior colliculus (IC). We evoked three seizures in GEPRs and compared the results with those in seizure-naive GEPRs and nonepileptic Sprague-Dawley (SD) rats, the GEPR parent strain. RESULTS: Whole-cell recording in IC slices showed that GABA-mediated monosynaptic inhibitory postsynaptic currents (IPSCs) were reduced 55% by three brief epileptic seizures. Whole-cell recording in IC neuronal cultures showed that currents elicited by GABA were reduced 67% by three seizures. Western blotting for the alpha1 and alpha4 subunits of the GABAA receptor showed no statistically significant effects. In contrast, three brief epileptic seizures reduced gamma2 subunit levels by 80%. CONCLUSIONS: The effects of the very first seizures, in animals known to be epileptic, in an area of brain known to be critical to the seizure network, were studied. The results indicate that even brief epileptic seizures can markedly reduce IPSCs and GABA currents and alter GABAA-receptor subunit protein levels. The cause of the reductions in IPSCs and GABA currents is likely to be altered receptor subunit composition, with reduced gamma2 levels causing reduced GABAA-receptor sensitivity to GABA. Seizure-induced reductions in GABA-mediated inhibition could exacerbate epilepsy.
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Ben-Menachem, Elinor. "Is Prolactin a Clinically Useful Measure of Epilepsy?" Epilepsy Currents 6, no. 3 (May 2006): 78–79. http://dx.doi.org/10.1111/j.1535-7511.2006.00104.x.
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Use of Serum Prolactin in Diagnosing Epileptic Seizures: Report of the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology Chen DK, So YT, Fisher RS Neurology 2005;65(5):668–675 (Review) Objective The purpose of this article is to review the use of serum prolactin assay in epileptic seizure diagnosis. Methods The authors identified relevant studies in multiple databases and reference lists. Studies that met inclusion criteria were summarized and rated for quality of evidence, and the results were analyzed and pooled where appropriate. Results Most studies used a serum prolactin of at least twice baseline value as abnormal. For the differentiation of epileptic seizures from psychogenic nonepileptic seizures, one Class I and seven Class II studies showed that elevated serum prolactin was highly predictive of either generalized tonic–clonic or complex partial seizures. Pooled sensitivity was higher for generalized tonic–clonic seizures (60.0%) than for complex partial seizures (46.1%), while the pooled specificity was similar for both (approximately 96%). Data were insufficient to establish validity for simple partial seizures. Two Class II studies were consistent in showing prolactin elevation after tilt-test–induced syncope. Inconclusive data exist regarding the value of serum prolactin following status epilepticus, repetitive seizures, and neonatal seizures. Recommendations Elevated serum prolactin assay, when measured in the appropriate clinical setting at 10 to 20 minutes after a suspected event, is a useful adjunct for the differentiation of generalized tonic–clonic or complex partial seizure from psychogenic nonepileptic seizure among adults and older children (Level B). Serum prolactin assay does not distinguish epileptic seizures from syncope (Level B). The use of serum PRL assay has not been established in the evaluation of status epilepticus, repetitive seizures, and neonatal seizures (Level U).
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Masood, Eatemadifar, and Sepanj neya khaterah. "Seizure relationship and epileptic seizures." Pars of Jahrom University of Medical Sciences 3, no. 3 (July 1, 2006): 34–38. http://dx.doi.org/10.29252/jmj.3.3.34.
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Alves, Lucas Victor, Danielle Di Cavalcanti Sousa Cruz, Ana Maria Campos van der Linden, Ana Rodrigues Falbo, Maria Júlia Gonçalves de Mello, Camila Esteves Paredes, Germanna Virginya Cavalcanti Silva, José Natal Figueiroa, and Patrícia Gomes de Matos Bezerra. "Epileptic seizures in children with congenital Zika virus syndrome." Revista Brasileira de Saúde Materno Infantil 16, suppl 1 (November 2016): S27—S31. http://dx.doi.org/10.1590/1806-9304201600s100003.
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Abstract Objectives: to describe preliminary data referred to epileptic seizures and the probability of occurring these epileptic seizures in the infants' first months of life with congenital Zika virus (ZIKV) syndrome. Methods: concurrent cohort study including newborns and infants with congenital Zika virus syndrome attended at the specialized outpatient clinic at IMIP, Recife, Pernambuco, from October 2015 to May 2016. Results: data on 106 infants were analyzed with confirmed or suspected association to ZIKV infection. Forty children (38.7%) presented an epileptic seizure, classified at 43.3% of the cases as being spasms, 22.7% as generalized tonic seizures, 20.5% as partial and 4.5% other types of seizures. The median of days until the first report on the occurrence of epileptic seizure was 192 days of life. Conclusions: children with congenital Zika virus syndrome presented a high incidence of epileptic seizures before the end of the first semester of life, and spasm was the epileptic seizure mostly observed.
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Prokudin, Mikhail Yu, Olga V. Tikhomirova, Sergey N. Bazilevich, Dmitriy E. Dyskin , Nikolay V. Tsygan , Anna M. Moiseeva, and Svetlana S. Prokudina. "Acute symptomatic epileptic seizures and epilepsy after stroke." Russian Military Medical Academy Reports 41, no. 4 (November 17, 2022): 407–13. http://dx.doi.org/10.17816/rmmar111881.
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Acute symptomatic epileptic seizures occur within 7 days after the stroke onset. Acute symptomatic epileptic seizures occur in 6.3% of stroke cases: ischemic stroke 4.2%, cerebral infarction with hemorrhagic transformation 12.5%, intracerebral hemorrhage 16.2%. Cumulative risk of subsequent unprovoked epileptic seizure after the first acute symptomatic seizure at follow-up for 10 years is 18.7 %. In acute symptomatic epileptic seizure secondary prevention with antiepileptic drugs usually is not indicated. If antiepileptic drug treatment is initiated after a single acute symptomatic seizure, it should be discontinued after the acute period of the disease. The 10-years risk of subsequent unprovoked epileptic seizures after the single unprovoked epileptic seizure in stroke patients is 71.5%. In this situation the epilepsy diagnosis is reasonable and antiepileptic drug treatment should be initiated. The incidence of epilepsy after acute ischemic or hemorrhagic stroke is identical 1012%. The choice of the group of antiepileptic drugs should be based on clinical guidelines for patients with focal forms of epilepsy. Pharmacokinetic interactions between antiepileptic drugs and oral anticoagulants, antiplatelet agents, antihypertensive drugs, and other xenobiotics should be minimized. Thus antiepileptic drugs that induce or inhibit microsomal liver enzymes should also be avoided.
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Mangunsong, Harry. "Serum prolactin for differentiating epileptic seizures in children." Paediatrica Indonesiana 55, no. 5 (October 1, 2015): 273. http://dx.doi.org/10.14238/pi55.5.2015.273-6.
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Background Serum prolactin level has been used as a marker to differentiate epileptic from non-epileptic seizures in adults. Electroencephalogram (EEG) examination is the primary diagnostic tool used to assess seizures. However, EEGs are quite difficult to perform in children and have sensitivity of only 50%- 55%, with 96% specificity. Objective To assess the diagnostic potential of serum prolactin level as an alternative tool for children for differentiating between epileptic and non-epileptic seizures. Methods This diagnostic study was performed between January 2013 and December 2013. Thirty patients aged 3 months to 15 years with seizures and without fever who visited the Emergency Department of Arifin Ahmad Hospital, Pekanbaru, Riau, were included. Blood specimens were collected within 2 hours after seizure. Subjects underwent serum prolactin measurements and EEG examinations. Results Fifteen subjects had normal EEGs and 15 subjects had abnormal EEGs. Post-ictal serum prolactin levels were significantly higher in the epileptiform EEG group. The mean serum prolactin levels were 23.78 (SD 21.86) ng/mL and 10.57 (SD 5.62)ng/mL in patients with epileptic and non-epileptic patients, respectively. Using a prolactin cut-off point of 17.2 ng/mL, serum prolactin had a 73.3% sensitivity and 93.3% specificity for differentiating between epileptic and non-epileptic seizures. Conclusion Our findings suggest that serum prolactin level increases after an epileptic seizure, but not after a non-epileptic seizure. Post-ictal prolactin elevation within 2 hours may be useful in differentiating epileptic seizures from non-epileptic seizures.
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Buckmaster, P. S., E. Tam, and P. A. Schwartzkroin. "Electrophysiological correlates of seizure sensitivity in the dentate gyrus of epileptic juvenile and adult gerbils." Journal of Neurophysiology 76, no. 4 (October 1, 1996): 2169–80. http://dx.doi.org/10.1152/jn.1996.76.4.2169.
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1. Naturally occurring inherited epilepsy is common among Mongolian gerbils, providing an opportunity to identify neurological factors that correlate with seizure behavior. In the present study we examine the ontogeny of seizure behavior and compare the electrophysiology and anatomy of the dentate gyrus in epileptic and nonepileptic gerbils. 2. Behavioral seizure testing revealed that young gerbils do not begin having seizures until they are 2 mo of age, at which time seizure incidence across animals is at its highest level. Most seizure-positive juvenile gerbils became epileptic adults, but 30% outgrew their epileptic condition. 3. The number of somatostatin- and parvalbumin-immunoreactive neurons in the dentate gyrus and Ammon's horn was counted, with the use of quantitative stereological techniques, in juvenile and adult gerbils. No significant differences were detected between epileptic and nonepileptic groups. 4. In dentate gyrus field potential responses to perforant path stimulation, adult epileptic gerbils showed enhanced paired-pulse inhibition at short (30 ms) interstimulus intervals and enhanced facilitation at intermediate (70 ms) intervals compared with nonepileptic controls. These differences were most pronounced when stimuli were delivered at faster (1.0 Hz) rather than slower (0.1 Hz) rates. 5. Compared with seizure-negative juveniles, seizure-positive juveniles showed the same pattern of paired-pulse response abnormalities as epileptic adults. However, seizure-positive juveniles had a lower threshold for maximal dentate activation than epileptic adults. 6. These results demonstrate similar functional abnormalities in the dentate gyri of epileptic adult gerbils and in juvenile gerbils before they experience multiple seizures. Such findings suggest that abnormalities in functional inhibition of the dentate gyrus network precede and therefore might contribute to overt seizure activity.
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Johanes, Stephanie, and Budi Riyanto Wreksoatmodjo. "Kaitan COVID-19 dengan Risiko Bangkitan Epileptik." Cermin Dunia Kedokteran 49, no. 5 (May 2, 2022): 248–53. http://dx.doi.org/10.55175/cdk.v49i5.228.
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COVID-19 dapat menyebabkan kegagalan organ tubuh seperti sistem pernapasan, ginjal, hati, dan jantung. Pada beberapa orang juga ditemukan gejala sistem saraf, seperti delirium, confusion, nyeri kepala, vertigo, hemorrhagic stroke dan iskemik, hilangnya sensasi penciuman dan perasa, kejang atau bangkitan epileptik. Bangkitan epileptik pada kasus COVID-19 dapat dikaitkan dengan aktivasi sel glia, kerusakan sawar darah-otak, keadaan hipertermia atau gangguan elektrolit dan gangguan neurotransmiter. Di lain pihak, pengaruh infeksi COVID-19 pada pasien epilepsi masih belum diketahui pasti.
COVID-19 can cause organ failure such as the respiratory system, kidneys, liver, and heart. Risks of neurological complications are delirium, stroke, loss of smell dan taste, and convulsion/epileptic seizure. Seizures in COVID-19 may be associated with glial activation, blood-brain barrier disruption, and hyperthermia and/ or neurotransmitter dysregulation. On the other hand, the impact of COVID-19 on epileptic patients is yet to be identified
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Egorova, E. V., and D. V. Dmitrienko. "Developmental Venous Anomalies and Epilepsy." Doctor.Ru 20, no. 9 (2021): 21–25. http://dx.doi.org/10.31550/1727-2378-2021-20-9-21-25.
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Objective of the Review: To study the role of developmental venous anomaly (DVA) of the brain in the development of epileptic seizures. Key Points. Vascular malformations (cavernous angiomas and aneurysms), arterivenous malformations and aneurysms are known to contribute to the development of epileptic seizures. DVAs can be associated with epileptic seizures; however, their role in the epileptogenesis is not clear yet. This article describes possible mechanisms of epileptic seizure development caused by vascular malformations and possible causes of epilepsy associated with brain DVA. Conclusion. The association between epileptic seizures and uncomplicated DVAs is arguable. The primary mechanisms of epileptic seizures in DVAs are age-related cortical hypometabolism and hematoencephalic barrier dysfunctions which can cause pharmacoresistent epilepsy. These data are controversial and require further evaluation and analysis. Keywords: epilepsy, epileptic seizure, venous angioma, venous development anomalies, positron emission tomography.
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Purnomo, Adenuar, and Handayani Tjandrasa. "Epileptic Seizure Classification using Deep Batch Normalization Neural Network." Lontar Komputer : Jurnal Ilmiah Teknologi Informasi 11, no. 3 (December 22, 2020): 124. http://dx.doi.org/10.24843/lkjiti.2020.v11.i03.p01.
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Epilepsy is a chronic noncommunicable brain disease. Manual inspection of long-term Electroencephalogram (EEG) records for detecting epileptic seizures or other diseases that lasted several days or weeks is a time-consuming task. Therefore, this research proposes a novel epileptic seizure classification architecture called the Deep Batch Normalization Neural Network (Deep BN3), a BN3 architecture with a deeper layer to classify big epileptic seizure data accurately. The raw EEG signals are first to cut into pieces and passed through the bandpass filter. The dataset is very imbalanced, so an undersampling technique was used to produce a balanced sample of data for the training and testing dataset. Furthermore, the balanced data is used to train the Deep BN3 architecture. The resulting model classifies the EEG signal as an epileptic seizure or non-seizure. The classification of epileptic seizures using Deep BN3 obtained pretty good results compared to other architectures used in this research, with an accuracy of 53.61%.
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Li, Jiajia, Peihua Feng, Liang Zhao, Junying Chen, Mengmeng Du, Jian Song, and Ying Wu. "Transition behavior of the seizure dynamics modulated by the astrocyte inositol triphosphate noise." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 11 (November 2022): 113121. http://dx.doi.org/10.1063/5.0124123.
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Epilepsy is a neurological disorder with recurrent seizures, which convey complex dynamical characteristics including chaos and randomness. Until now, the underlying mechanism has not been fully elucidated, especially the bistable property beneath the epileptic random induction phenomena in certain conditions. Inspired by the recent finding that astrocyte GTPase-activating protein (G-protein)-coupled receptors could be involved in stochastic epileptic seizures, we proposed a neuron–astrocyte network model, incorporating the noise of the astrocytic second messenger, inositol triphosphate (IP3) that is modulated by G-protein-coupled receptor activation. Based on this model, we have statistically analyzed the transitions of epileptic seizures by performing repeatable simulation trials. Our simulation results show that the increase in the IP3 noise intensity induces depolarization-block epileptic seizures together with an increase in neuronal firing frequency, consistent with corresponding experiments. Meanwhile, the bistable states of the seizure dynamics were present under certain noise intensities, during which the neuronal firing pattern switches between regular sparse spiking and epileptic seizure states. This random presence of epileptic seizures is absent when the noise intensity continues to increase, accompanying with an increase in the epileptic depolarization block duration. The simulation results also shed light on the fact that calcium signals in astrocytes play significant roles in the pattern formations of the epileptic seizure. Our results provide a potential pathway for understanding the epileptic randomness in certain conditions.
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Johanes, Stephanie, and Budi Riyanto Wreksoatmodjo. "Kaitan COVID-19 dengan Risiko Bangkitan Epileptik." Cermin Dunia Kedokteran 49, no. 5 (April 27, 2022): 248. http://dx.doi.org/10.55175/cdk.v49i5.1847.
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<p>COVID-19 dapat menyebabkan kegagalan organ tubuh seperti sistem pernapasan, ginjal, hati, dan jantung. Pada beberapa orang juga ditemukan gejala sistem saraf, seperti delirium, confusion, nyeri kepala, vertigo, hemorrhagic stroke dan iskemik, hilangnya sensasi penciuman dan perasa, kejang atau bangkitan epileptik. Bangkitan epileptik pada kasus COVID-19 dapat dikaitkan dengan aktivasi sel glia, kerusakan sawar darah-otak, keadaan hipertermia atau gangguan elektrolit dan gangguan neurotransmiter. Di lain pihak, pengaruh infeksi COVID-19 pada pasien epilepsi masih belum diketahui pasti.</p><p> </p><p>COVID-19 can cause organ failure such as the respiratory system, kidneys, liver, and heart. Risks of neurological complications are delirium, stroke, loss of smell dan taste, and convulsion/epileptic seizure. Seizures in COVID-19 may be associated with glial activation, blood-brain barrier disruption, and hyperthermia and/or neurotransmitter dysregulation. On the other hand, the impact of COVID-19 on epileptic patients is yet to be identified. </p>
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Schwabe, Meike, Markus Reuber, Martin Schöndienst, and Elisabeth Gülich. "Listening to people with seizures: How can linguistic analysis help in the differential diagnosis of seizure disorders?" Communication and Medicine 5, no. 1 (November 27, 2008): 59–72. http://dx.doi.org/10.1558/cam.v5i1.59.
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Despite advances in medical technology, the patients’ history remains the most crucial tool in the differential diagnosis of epileptic or non-epileptic seizures (NES). The distinction of these two types of seizures is a common and important task for neurologists. Whereas epileptic seizures would be treated with antiepileptic drugs, non-epileptic seizures are thought to be a manifestation of psychological or social distress and can improve with psychotherapy. This paper summarizes the findings of a series of multidisciplinary research studies undertaken at the Bethel Epilepsy Centre and the University of Bielefeld in Germany in which linguistic analysis was carried out to identify and describe linguistic and interactional features in clinical exchanges between doctors and patients with seizures. Two distinct communication profiles emerged in these studies based on the analysis of transcripts of over 110 doctor-patient encounters. Epileptic seizure descriptions are characterized by formulation effort, provide the doctor with a coherent account of individual seizures, relate subjective seizure experiences and use consistent metaphoric conceptualizations. Patients with NES tend not to volunteer subjective seizure symptoms, give accounts of their seizures which are difficult to understand and are inconsistent in their choice of metaphors.
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Jones, Michael W. "Consequences of Epilepsy: Why do We Treat Seizures?" Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 25, S4 (November 1998): S24—S26. http://dx.doi.org/10.1017/s0317167100034934.
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ABSTRACT:Improving health-related quality of life in epileptic patients, rather than simply reducing seizures, has become the principal goal in epilepsy management. Reducing seizure frequency is one of the main factors contributing to improved quality of life. Evidence for and risk of the following potential adverse effects of seizures is reviewed: brain damage from seizures, sudden unexpected death, status epilepticus, kindling, falls or injury and psychosocial consequences. Although the evidence for seizure frequency influencing some of these factors is not clear-cut, as a whole, they offer a strong impetus toward an aggressive approach to controlling recurrent seizures in most cases.
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Fiza, Bushra, Maheep Sinha, Shalu Sharma, and Sumit Kumar Tiwari. "Evaluation of Serum Calcium Levels in Patients with Epileptic Seizure." Journal of Mahatma Gandhi University of Medical Sciences and Technology 5, no. 2 (2020): 35–37. http://dx.doi.org/10.5005/jp-journals-10057-0112.
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ABSTRACT Introduction Epilepsy is a disorder of the central nervous system, characterized by an epileptic seizure. Epileptic seizures occur due to abnormal synchronous activity in the brain. Calcium is an essential component of bone. Hypocalcemia enhances neuronal excitability, and there are many causes of which include hypocalcemia, vitamin D deficiency, and PTH resistance. Materials and methods The study was conducted in Department of Biochemistry in association with the Department of Neurology of Mahatma Gandhi Medical College and Hospital, Jaipur. Fifty patients diagnosed for epileptic seizure and 50 controls, visiting the inpatient department (IPD) and outpatient department (OPD) of Neurology fulfilling the inclusion criteria, were enrolled for the study. Result The present study showed significantly lower level of serum calcium in patients with epileptic seizure when compared to controls. Conclusion The serum calcium was measured between epileptic seizure and controls. Our present study showed significantly lower value of calcium. It is therefore suggested that there should be regular screening for calcium in patients with epileptic seizure. The serum calcium is biomarker of bone metabolism; so, the correlation can be further studied with some more bone metabolism markers in epileptic seizure patients. How to cite this article Sharma S, Fiza B, Tiwari SK, et al. Evaluation of Serum Calcium Levels in Patients with Epileptic Seizure. J Mahatma Gandhi Univ Med Sci Tech 2020;5(2):35–37.
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Jan, Mohammed M. S., and John P. Girvin. "Seizure Semiology: Value in Identifying Seizure Origin." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 35, no. 1 (March 2008): 22–30. http://dx.doi.org/10.1017/s0317167100007526.
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ABSTRACT:The diagnosis of epilepsy depends upon a number of factors, particularly detailed and accurate seizure history, or semiology. Other diagnostic data, consisting of electroencephalography, video-monitoring of the seizures, and magnetic resonance imaging, are important in any comprehensive epilepsy program, particularly with respect to lateralizing and localizing the seizure focus, if such a focus exists, and with respect to determining the type of seizure or seizure syndrome. The aim of this review is to present a survey of important semiologic characteristics of various seizures that provide the historian with observations, which help to lateralize and localize epileptic zones. Clinical semiology is the starting point of understanding a seizure disorder and making the diagnosis of epilepsy. While it may not provide unequivocal evidence of localization of the epileptic focus, nevertheless it usually directs subsequent investigations, whose concordance is necessary for the ultimate localization.
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Ülgey, Ayşe, Recep Aksu, and Cihangir Bicer. "Nasal and Buccal Treatment of Midazolam in Epileptic Seizures in Pediatrics." Clinical Medicine Insights: Pediatrics 6 (January 2012): CMPed.S8330. http://dx.doi.org/10.4137/cmped.s8330.
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Acute seizure and status epilepticus constitute major medical emergencies in children. Four to six percent of children will have at least one seizure in the first 16 years of life. Status epilepticus is a common neurological emergency in childhood and is associated with significant morbidity and mortality. The early application of antiepileptic treatment is very important. Because early treatment prevents the status epilepticus formation and shortens the duration of seizure activity. For this reason administration of anticonvulsant therapy in the prehospital setting is very important. Seizures generally begin outside the hospital, and thus parents and caregivers need simple, safe and effective treatment options to ensure early intervention. The only special preparation used for this purpose is rectal diazepam but has some disadvantages. Midazolam is a safe, short-acting benzodiazepin. It is suitable to use oral, buccal, nasal, im and iv routes. This provides a wide area for clinical applications. Recently there are many clinical studies about the usage of nasal and buccal midazolam for treatment of pediatric epileptic seizures. The nasal and buccal applications in pediatric seizures are very practical and effective. Parents and caregivers can apply easily outside the hospital.
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Hussen, Hoger Mahmud. "The State of the Art in Feature Extraction Methods for EEG Classification." UHD Journal of Science and Technology 3, no. 2 (July 25, 2019): 16. http://dx.doi.org/10.21928/uhdjst.v3n2y2019.pp16-23.
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Epileptic seizure is a neurological disease that is common around the world and there are many types (e.g. Focal aware seizures and atonic seizure) that are caused by synchronous or abnormal neuronal activity in the brain. A number of techniques are available to detect the brain activities that lead to Epileptic seizures; one of the most common one is Electroencephalogram (EEG) that uses visual scanning to measure brain activities generated by nerve cells in the cerebral cortex. The techniques make use of different features detected by EEG to decide on the occurrence and type of seizures. In this paper we review EEG features proposed by different researches for the purpose of Epileptic seizure detection, also analyze, and compare the performance of the proposed features.
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Plug, Leendert, Basil Sharrack, and Markus Reuber. "Metaphors in the description of seizure experiences: Common expressions and differential diagnosis." Language and Cognition 3, no. 2 (June 2011): 209–33. http://dx.doi.org/10.1515/langcog.2011.008.
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AbstractThis paper explores the use of metaphorical expressions in the description of seizure experiences by patients with epilepsy and patients with psychogenic non-epileptic seizures. The paper addresses two main questions. First, what is the range of metaphorical expressions which patients use to describe their seizure experiences, and can these be related to conventional metaphors used by healthy individuals? Second, is the difference in the underlying cause of our patients' seizure experiences in any way reflected in their use of metaphorical expressions? The paper suggests that the answer to both of these questions is affirmative, which strengthens the embodiment hypothesis. Implications for our understanding of patients' experiences of seizures and of the difference between epileptic and non-epileptic seizures are also discussed.
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Zena, Dawit, Abilo Tadesse, Nebiyu Bekele, Samson Yaregal, Nuria Sualih, and Edilawit Worku. "Seizure control and its associated factors among epileptic patients at Neurology Clinic, University of Gondar hospital, Northwest Ethiopia." SAGE Open Medicine 10 (January 2022): 205031212211006. http://dx.doi.org/10.1177/20503121221100612.
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Background: Epilepsy is characterized by two or more unprovoked recurrent seizures, which often respond to available antiseizure medications. However, seizure control among epileptic patients in the developing world is low. Factors determining seizure control among epileptic patients were not evidently explored in the study setting. Objectives: This study aimed to determine the magnitude of uncontrolled seizures and associated factors among epileptic patients at the University of Gondar hospital. Methods: This cross-sectional study was conducted at the University of Gondar hospital, Northwest Ethiopia. A convenience sampling method was used to recruit study subjects. Controlled seizure was defined as seizure freedom for the past 1 year. Logistic regression analysis was used to identify factors associated with seizure control. A p-value < 0.05 was used to declare a significant association. Results: A total of 320 study subjects were included in the study. The mean (±SD) age of patients was 27.5 ± 7.6 years. More than half (182/320, 57%) of epileptic patients had uncontrolled seizures. Five or more pretreatment seizure episodes (adjusted odds ratio = 3.98, 95% confidence interval: 1.81–8.75, p = 0.001), less than 2 years on anti-seizure medications (adjusted odds ratio = 8.64, 95% confidence interval: 3.27–22.85, p < 0.001), taking 2 or more ASMs (adjusted odds ratio = 2.48, 95% confidence interval: 1.23–5.02, p = 0.011), poor adherence to ASMs (adjusted odds ratio = 9.37, 95% confidence interval: 4.04–21.75, p < 0.001), and living at a single trip distance from hospital equaled 1 h or more (adjusted odds ratio = 4.20, 95% confidence interval: 2.11–8.41, p < 0.001) were significantly associated with uncontrolled seizures. Conclusion: The dose of a preferred anti-seizure medication should be optimized before combinations of anti-seizure medications are used. Adherence to anti-seizure medications should be reinforced for better seizure control. Epilepsy care should be integrated into primary health care services in the catchment region.
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Panigrahi, Millee, Dayal Kumar Behera, and Krishna Chandra Patra. "Epileptic seizure classification of electroencephalogram signals using extreme gradient boosting classifier." Indonesian Journal of Electrical Engineering and Computer Science 25, no. 2 (February 1, 2022): 884. http://dx.doi.org/10.11591/ijeecs.v25.i2.pp884-891.
Full textAbstract:
Epilepsy causes repeated seizures in an individual's life, which causes transient irregularities in the brain's electrical activity. It results in different physical symptoms that are abnormal. Various antiepileptic drugs fail to minimize repeated patient seizures. The electroencephalogram (EEG) signal recordings provide us with time-series data set for epileptic seizure detection and analysis. These signals are highly nonlinear and inconsistent, and they are recorded over time. Predicting the ictal period (seizure period at the time of epilepsy) is thus a challenging task in the naked eye for the medical practitioners. Various machine learning techniques are applied to identify the seizure's occurrence and its classification in multiple domains. A classification model based on extreme gradient boosting (SCLXGB) is proposed here for the classification of the EEG signals. The SCLXGB model implements binary seizure classification on the benchmark dataset. Compared with K-nearest neighbor, linear regression, and Decision treebased models, the proposed model achieves the best area under receiver operating curve (AUC) of 0.9462 and an accuracy of 96% which signifies accurate prediction of seizure and non seizure period. The proposed model SCLXGB was validated by taking different performance metrics to indicate the occurrence and non-occurrence of seizures in patients more appropriately.
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Luan, K., J. Mailo, N. Liu, J. Kassiri, and DB Sinclair. "P.103 Midline Spikes and Intractable Seizures in Pediatric Epilepsy." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 48, s3 (November 2021): S49. http://dx.doi.org/10.1017/cjn.2021.381.
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Background: Epileptic discharges localized to the midline vertex are rare. However, they have been associated with intractable seizures and severe long-term consequences in the developing brain. Our study aimed to understand the etiology of pediatric midline seizures and define post-surgical seizure outcomes. Methods: We reviewed charts, electroencephalography (EEG), and neuroimaging studies of ten pediatric patients with epileptic discharges localized to the midline vertex in the Comprehensive Epilepsy Program. The seizures were classified according to the International League Against Epilepsy criteria, patient age, sex, neuroimaging results, seizure etiology and outcomes were obtained. Results: Age of seizure onset was within the first 10 years of life in 90% of patients, with focal seizures being the most prevalent. Focal cortical dysplasia (FCD) was the most common etiology present in 50% of patients. These children had normal neuroimaging studies and intractable epilepsy. However, seizure freedom was achieved following surgical resection of the epileptogenic zone. Conclusions: We demonstrated that patients with midline epileptic discharges are associated with intractable focal seizures and early seizure onset. Despite normal neuroimaging reports, FCD was the most common pathology. Thus our study suggests early localization and resection of the epileptogenic zone may be beneficial for achieving seizure freedom in children with this electroclinical syndrome.
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Han, Min, Sunan Ge, Minghui Wang, Xiaojun Hong, and Jie Han. "A Novel Dynamic Update Framework for Epileptic Seizure Prediction." BioMed Research International 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/957427.
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Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients’ daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients’ physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures’ arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient’s preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.
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Perez-Sanchez, Andrea V., Carlos A. Perez-Ramirez, Martin Valtierra-Rodriguez, Aurelio Dominguez-Gonzalez, and Juan P. Amezquita-Sanchez. "Wavelet Transform-Statistical Time Features-Based Methodology for Epileptic Seizure Prediction Using Electrocardiogram Signals." Mathematics 8, no. 12 (November 27, 2020): 2125. http://dx.doi.org/10.3390/math8122125.
Full textAbstract:
Epilepsy is a brain disorder that affects about 50 million persons around the world and is characterized by generating recurrent seizures, which can put patients in permanent because of falls, drowning, burns, and prolonged seizures that they can suffer. Hence, it is of vital importance to propose a methodology with the capability of predicting a seizure with several minutes before the onset, allowing that the patients take their precautions against injuries. In this regard, a methodology based on the wavelet packet transform (WPT), statistical time features (STFs), and a decision tree classifier (DTC) for predicting an epileptic seizure using electrocardiogram (ECG) signals is presented. Seventeen STFs were analyzed to measure changes in the properties of ECG signals and find characteristics capable of differentiating between healthy and 15 min prior to seizure signals. The effectiveness of the proposed methodology for predicting an epileptic event is demonstrated using a database of seven patients with 10 epileptic seizures, which was provided by the Massachusetts Institute of Technology–Beth Israel Hospital (MIT–BIH). The results show that the proposed methodology is capable of predicting an epileptic seizure 15 min before with an accuracy of 100%. Our results suggest that the use of STFs at frequency bands related to heart activity to find parameters for the prediction of epileptic seizures is suitable.
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Ali, Irfan, and Dave F. Clarke. "Febrile Seizure Plus and PCDH19-Related Epilepsy Syndromes." Journal of Pediatric Epilepsy 08, no. 03 (September 2019): 074–78. http://dx.doi.org/10.1055/s-0040-1701202.
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AbstractEpilepsy is a disorder of the brain characterized by an enduring predisposition to generate epileptic seizures. Practically, a patient has epilepsy if having two unprovoked seizures more than 24 hours apart, one unprovoked seizure and significant risk of another seizure, or epilepsy syndrome. Seizures induced by fever do not therefore fit this classification. An initial febrile seizure may therefore cause a false sense of security in children who evolve to febrile seizure plus syndromes. Sodium channel defects seem to predominate as the main causative factor for febrile seizure plus syndromes. More severe pathological variants, such as Dravet's syndrome, have phenotypic similarities to other fever-associated epileptic encephalopathies, including those caused by mutations in protocadherin 19 (PCDH19). The clinical presentations, investigational studies, and management of febrile seizure plus syndrome, as well as epilepsies associated with PCDH19 mutations will be reviewed.
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Rossi, Rosario, Maria Valeria Saddi, Alessandro Mela, and Anna Ticca. "Posterior Reversible Encephalopathy Syndrome with Bilateral Independent Epileptic Foci Precipitated By Guillain-Barrè Syndrome." Case Reports in Neurological Medicine 2016 (2016): 1–4. http://dx.doi.org/10.1155/2016/5913840.
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We report the case of a 56-year-old woman who developed status epilepticus (SE) related to independent occipital foci as clinical manifestation of posterior reversible encephalopathy syndrome (PRES) in the background of Guillain-Barrè syndrome (GBS). SE resulted from a series of focal seizures clinically characterized by left- and rightward deviations of the head and consequent oculoclonic movements. Electroencephalography recorded independent seizure activity in both occipital regions with alternate involvement of the two cerebral hemispheres. The epileptic foci corresponded topographically to parenchymal abnormalities of PRES in the occipital lobes. The manifestation of bilateral, independent occipital seizures with alternate deviations of the head and oculoclonic movements, previously not reported in patients with PRES, highlights the acute epileptogenicity of the cerebral lesions in this syndrome. Despite the variable clinical expression of seizures due to occipital damage in PRES, the development of independent seizure activity in both occipital lobes might represent a distinctive epileptic phenomenon of this encephalopathy.
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Batham, Lalima, Lokesh Choudhary, Alka Mishra, and Vandana Shrivastava. "Yagya Therapy for Epileptic Seizures: A Case Study." Interdisciplinary Journal of Yagya Research 1, no. 2 (October 31, 2018): 37–42. http://dx.doi.org/10.36018/ijyr.v1i2.14.
Full textAbstract:
Epileptic seizure is a neurological condition in which brief to long episodes of vigorous shaking, convulsions, blackouts, fainting, unresponsiveness, jerks, etc. occur in the patients. Current treatment approaches are anti-seizure medicines, which patients are bound to take throughout life. These medications are mostly not able to reverse or eradicate the condition. Vedic literature recommends Yagya as a therapy for mental conditions similar to mania, seizure, etc. Yagya-Therapy provides pulmonary inhalation of medicinal-smoke of multiple herbs (generated through oblation in fire along with chanting of Vedic hymns), which have the potential for seizure treatment. A case study is being reported wherein Yagya-Therapy was prescribed to an epileptic seizure patient. Before the start of Yagya-Therapy, the patient (Male/65 years) had been suffering from epileptic seizures (~8-10 episodes annually) since ~3 years (pre-observation). Subsequently, the patient has been doing Yagya-Therapy since past ~3.5 years, wherein only 2-3 episodes occurred during the first year, that too during sleep only, and after that no seizures have been experienced. All this time, the patient continued to take the allopathic medication that he was taking earlier. Thus, Yagya-Therapy can be an effective treatment option for epileptic seizure patients.
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TSAKALIS, KOSTAS, and LEON IASEMIDIS. "CONTROL ASPECTS OF A THEORETICAL MODEL FOR EPILEPTIC SEIZURES." International Journal of Bifurcation and Chaos 16, no. 07 (July 2006): 2013–27. http://dx.doi.org/10.1142/s0218127406015866.
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We discuss the key features of theoretical models of networks of coupled chaotic oscillators that produce seizure-like events and bear striking similarities to dynamics of epileptic seizures. Our long-term objective is to understand the basic functional mechanisms that can produce seizures and may ultimately lead to strategies for seizure suppression and control. We show that, from a dynamical systems point of view, a plausible cause of seizures is a pathological feedback in the brain circuitry. This suggests new seizure control approaches, as well as systematic methods to tune existing ones. While the suggested models and control approaches are far from being considered optimal for epileptic seizures, they have interesting physical interpretation and implications for treatments of epilepsy. They also have close ties with a variety of recent practical observations in the human and animal epileptic brain, and with theories from adaptive systems, optimization and chaos.
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Arbune, Anca Adriana, Oana Tarta Arsene, Lacramioara Brinduse, and Dana Craiu. "EPILEPTIC SEIZURE TRIGGERS IN CHILDREN FROM ROMANIA." Romanian Journal of Neurology 15, no. 2 (June 30, 2016): 80–85. http://dx.doi.org/10.37897/rjn.2016.2.5.
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Objectives. The identification of the types, characteristics and correlations of epileptic seizure triggers in children with epilepsy from Romania. Material and methods. Transversal observational study on 278 children with epilepsy using the questionnaire method, containing questions regarding seizure characteristics, demographical information and medical history. Results. The lot characteristics were average age 9.74 years; 57.2% males; 19.4% positive epilepsy family history; 48.2% late psychomotor development; 54% deficitary neuropsychological development; 25.2% treatment resistant epilepsies; 59.7% of children had focal epileptic seizures, 35.3% had generalized. Average number of triggering factors was 3 and 20.1% of children had no seizure trigger. The most frequently reported factors were: sleep deprivation 39.57%, anxiety 23%, sleep disturbances 22.66%, fever 20.50%, anger 19%, light stimulation 17.27%, crying 16.19%, interrupting antiepileptic medication administration 14.39%, watching too much TV 14.39%, physical fatigue 12.59%. The number of seizure triggers can be mathematically modelled according to age and treatment resistance. Unresponsiveness to treatment of the epilepsy has a few predictors: timing of the seizure occurrence, imaging alterations, late psychomotor development, IQ, the number of seizure triggering factors. Conclusions. There was at least one seizure trigger identified in 79.9% of children with epilepsy. The most frequent reported trigger was sleep deprivation. The number of seizure triggers can be estimated through mathematical modelling. Treatment resistance of epileptic seizures has more predicting factors.
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Alam, Md Niyaz, Jainendra Jain, Azhar Danish Khan, Rahul Kaushik, Najam Ali Khan, and Lubhan Singh. "Devices used for Treatment of Epilepsy." INTERNATIONAL JOURNAL OF PHARMACEUTICAL EDUCATION AND RESEARCH (IJPER) 2, no. 02 (December 30, 2020): 56–60. http://dx.doi.org/10.37021/ijper.v2i2.5.
Full textAbstract:
Epilepsy is a group of chronic neurological disorder of the brain that affects around 1-2% of the population across the world. According to the World Health Organization (WHO), epilepsy is characterized by periodically spontaneous seizures, which are usually due to excessive electrical discharges in a group of brain cells. The earlier day electroencephalogram (EEG) signals are useful tool for detection of epileptic seizures.Epileptogenesis is a slow process. After several months of initial insult, spontaneous recurrent seizures begin to appear. Epilepsy is considered to be resolved for individuals who are seizure-free for the last 10 years, with no seizure medicines for the last 5 years. Currently, used drugs available for treating epilepsy have draw backs like Epileptogenesis and other dose-related side effects. In spite of daily treatment, nearly 30% of patients continue to have convulsions and fail to provide a complete cure. Hence, there is a need for another alternative option to control the epileptic seizure and minimize the duration of seizure without taking a medicine and improving the quality of patient’s life. In current scenario the Vagus nerve stimulation (VNS) has become an important tool for controlling the epileptic seizure. Vagus nerve stimulation is used for patient with refractory and drug resistant epilepsy. Various non-drug therapies form preclinical to clinical for controlling seizures in epileptic patients with drug resistance current available have been highlighted in this review.
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Alam, Md Niyaz, Jainendra Jain, Azhar Danish Khan, Rahul Kaushik, Najam Ali Khan, and Lubhan Singh. "Devices used for Treatment of Epilepsy." INTERNATIONAL JOURNAL OF PHARMACEUTICAL EDUCATION AND RESEARCH (IJPER) 2, no. 02 (December 30, 2020): 56–60. http://dx.doi.org/10.37021/ijper.v2i2.5.
Full textAbstract:
Epilepsy is a group of chronic neurological disorder of the brain that affects around 1-2% of the population across the world. According to the World Health Organization (WHO), epilepsy is characterized by periodically spontaneous seizures, which are usually due to excessive electrical discharges in a group of brain cells. The earlier day electroencephalogram (EEG) signals are useful tool for detection of epileptic seizures.Epileptogenesis is a slow process. After several months of initial insult, spontaneous recurrent seizures begin to appear. Epilepsy is considered to be resolved for individuals who are seizure-free for the last 10 years, with no seizure medicines for the last 5 years. Currently, used drugs available for treating epilepsy have draw backs like Epileptogenesis and other dose-related side effects. In spite of daily treatment, nearly 30% of patients continue to have convulsions and fail to provide a complete cure. Hence, there is a need for another alternative option to control the epileptic seizure and minimize the duration of seizure without taking a medicine and improving the quality of patient’s life. In current scenario the Vagus nerve stimulation (VNS) has become an important tool for controlling the epileptic seizure. Vagus nerve stimulation is used for patient with refractory and drug resistant epilepsy. Various non-drug therapies form preclinical to clinical for controlling seizures in epileptic patients with drug resistance current available have been highlighted in this review.
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Nishad P, Muhammed, A. Priya, and K. Arun Chander. "A Case Report on SCN2A-Related Developmental and Epileptic Encephalopathy and Benign Familial Infantile Seizures." International Journal of Health Sciences and Research 13, no. 4 (April 8, 2023): 54–58. http://dx.doi.org/10.52403/ijhsr.20230408.
Full textAbstract:
The phenotypic spectrum of SCN2A-related epilepsy was broad, ranging from benign epilepsy in neonate and infancy to severe epileptic encephalopathy. Developmental and epileptic encephalopathy and benign familial infantile seizures are caused by heterozygous mutations in the SCN2A gene. Developmental and epileptic encephalopathy is a neurologic disorder characterized by the onset of seizures in the first days, weeks, or months of life. Seizures comprise multiple types, including tonic, generalized, and myoclonic, and tend to be refractory to medication. Additional common features include microcephaly, hypotonia, and abnormal movements, such as dystonia, dyskinesias, and chore athetotic movements. The phenotype is highly variable, even in patients with the same mutation. Benign familial infantile seizure is a seizure disorder of early childhood with age at onset from 3 months up to 24 months. It is characterized by brief seizures beginning with a slow deviation of the head and eyes to one side and progressing to generalized motor arrest and hypotonia, apnoea and cyanosis, and limb jerks. Seizures that begin shortly after birth or in infancy and are not associated with fever may suggest an SCN2A-related disorder. Genetic testing is required to confirm a diagnosis. Treatment for SCN2A-related disorders will depend on the type and severity of the seizures. Even Sodium channel-blocking medications are more effective, a combination of seizure medications is typically used to control the different seizure types. Key words: SCN2A gene, Developmental and epileptic encephalopathy, Benign familial infantile seizures, Genetic testing.
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Mahendrappa, Kotyal B., S. Perumal Sathya, and M. N. Suma. "Serum Prolactin Level in Children with Febrile Seizure and Epileptic Seizure; Comparative Study." Journal of Nepal Paediatric Society 37, no. 1 (October 4, 2017): 67–71. http://dx.doi.org/10.3126/jnps.v37i1.16502.
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Introduction: Transient hyperprolactinaemia has been reported to follow unprovoked seizures, a finding proposed to be useful in the differential diagnosis of epilepsy. On this basis we conducted a study with an objective to compare the postictal serum prolactin level in children with febrile seizures (FS) and epileptic seizures (ES) to evaluate, whether serum prolactin (PL) could be used a predictor in the diagnosis of ES.Material and Methods: This was a prospective comparative study was conducted on 52 children (26 in febrile seizures group and 26 in epileptic seizure group) in the age group of six months to five years. Children with CNS infection, developmental delay, structural CNS defects or neurological abnormality, metabolic disorders and those on drugs, known to have altered serum prolactin level were excluded. Blood for estimation of serum prolactin was collected within 180 minutes of occurrence of seizure. Level of serum prolactin was quantitatively assayed by chemiluminescence method and the levels were considered high, if values were greater than 23 ng/ml, which is the upper limit of normal for all age groups and both sex.Results: The mean serum prolactin level in epileptic seizures group was 25 ng/ml and that of febrile seizures group was 10.72 ng/ml. High level of serum prolactin was noted in 17 children (77.2%) with GTCS and 3 children (75%) with CPS. None of the children with febrile seizures had significant raise in the level of serum prolactin.Conclusion: There is a significant rise in serum prolactin level in children with epileptic seizures compared to febrile seizures, if measured within 3 hours of occurrence of seizures. Thus, the post-ictal serum prolactin level can be used as an additional investigation to diagnose or predict epileptic seizures in children.
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Reza, Mohammad Ali, and ASM Shamsul Arefin. "Epileptic Seizure Prediction and Source Localization using Entropy Analysis of Scalp EEG." Bangladesh Journal of Medical Physics 11, no. 1 (November 15, 2019): 16–25. http://dx.doi.org/10.3329/bjmp.v11i1.44054.
Full textAbstract:
Epilepsy is one of most common neurological disorders that affects people of all ages and can cause unpredictable seizures which may even cause death. The prediction of epileptic activities thus can have a great impact in avoiding fatal injuries through early preparation with medicines and also in improving the efficacy of medicines. A technique for early prediction of epileptic seizure from EEG signal is proposed in this paper. The pre-ictal period of epileptic seizure clearly depicts a start of seizure and comparing the changes in entropy of EEG signals in different brain regions during the pre-seizure period, the proposed technique could successfully predict the seizure using entropy analysis. Moreover, the region of the epileptic activities was also localized by dividing the total brain into four topographic regions and by calculating the entropy from this four zones separately. Thus, this proposed technique has the potential to help the clinical neurologists to investigate seizure detection and treat the patient in a better way with less supervision and better accuracy.
Bangladesh Journal of Medical Physics Vol.11 No.1 2018 P 16-25
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Paudel, Yam Nath, Yatinesh Kumari, Syafiq Asnawi Zainal Abidin, Iekhsan Othman, and Mohd Farooq Shaikh. "Pilocarpine Induced Behavioral and Biochemical Alterations in Chronic Seizure-Like Condition in Adult Zebrafish." International Journal of Molecular Sciences 21, no. 7 (April 3, 2020): 2492. http://dx.doi.org/10.3390/ijms21072492.
Full textAbstract:
Epilepsy is a devastating neurological condition exhibited by repeated spontaneous and unpredictable seizures afflicting around 70 million people globally. The basic pathophysiology of epileptic seizures is still elusive, reflecting an extensive need for further research. Developing a novel animal model is crucial in understanding disease mechanisms as well as in assessing the therapeutic target. Most of the pre-clinical epilepsy research has been focused on rodents. Nevertheless, zebrafish disease models are relevant to human disease pathophysiology hence are gaining increased attention nowadays. The current study for the very first time developed a pilocarpine-induced chronic seizure-like condition in adult zebrafish and investigated the modulation in several neuroinflammatory genes and neurotransmitters after pilocarpine exposures. Seizure score analysis suggests that compared to a single dose, repeated dose pilocarpine produces chronic seizure-like effects maintaining an average seizure score of above 2 each day for a minimum of 10 days. Compared to the single dose pilocarpine treated group, there was increased mRNA expression of HMGB1, TLR4, TNF-α, IL-1, BDNF, CREB-1, and NPY; whereas decreased expression of NF-κB was upon the repeated dose of pilocarpine administration. In addition, the epileptic group demonstrates modulation in neurotransmitters levels such as GABA, Glutamate, and Acetylcholine. Moreover, proteomic profiling of the zebrafish brain from the normal and epileptic groups from LCMS/MS quantification detected 77 and 13 proteins in the normal and epileptic group respectively. Summing up, the current investigation depicted that chemically induced seizures in zebrafish demonstrated behavioral and molecular alterations similar to classical rodent seizure models suggesting the usability of adult zebrafish as a robust model to investigate epileptic seizures.
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Gülersoy, E., S. S. İyigün, and B. B. Erol. "An overview of seizures and epilepsy in rabbits: etiological differences and clinical management." Naukovij vìsnik veterinarnoï medicini, no. 1(165) (May 25, 2021): 159–64. http://dx.doi.org/10.33245/2310-4902-2021-165-1-159-164.
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World Health Organization data suggest that neurological disorders are an important and growing cause of morbidity. One of the most common neurological disorder affecting people is epilepsy. Many companion animal neurological diseases share epidemiologic, pathophysiologic and clinical features with their human counterparts. In companion animals, affected species are mostly dogs, cats and rabbits. Seizure is defined as the clinical manifestation of abnormal electrical activity in the brain. Epilepsy is a brain disease characterized by the psychological, cognitive, social and environmental consequences of seizures. The epileptic seizures are recurrent events characterized by behavioral alterations that reflect the underlying neural mechanisms of the disease. In most cases, the disease can be diagnosed by anamnesis or observing the seizure. There are many reviews and researches about epilepsy and epileptic seizures in companion animals such as dogs and cats but not in rabbits. There are several causes of epilepsy in rabbits including viral, bacterial, parasitic, metabolic, respiratory, cardiovascular, nutritional, toxic, traumatic, enviromental and non-epileptic causes. Rabbits can be considered suitable for seizure and epilepsy investigations due to their recurrent seizures with low risk of death. As mentioned, there are several causes of epilepsy in rabbits but still to elucidate the exact mechanism of epilepsy and epileptic seizures in rabbits more studies need to be carried out. Despite the advances in the disease management, epilepsy is still an important cause of disability and mortality in both humans and companion animals. As tonic-clonic seizures with brainstem origin mostly affect children, epileptic seizures in rabbits may be a good model for further studies. Key words: Brain disease, epilepsy, neural disturbances, behavioral alterations, rabbit, seizure.
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YASAK, Ibrahim Halil, Mustafa YILMAZ, Murat GÖNEN, Metin ATESCELIK, Mehtap GURGER, Nevin ILHAN, and Mehmet Cagri GOKTEKIN. "Evaluation of ubiquitin C-terminal hydrolase-L1 enzyme levels in patients with epilepsy." Arquivos de Neuro-Psiquiatria 78, no. 7 (July 2020): 424–29. http://dx.doi.org/10.1590/0004-282x20200040.
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ABSTRACT Objective: Ubiquitin C-terminal Hydrolase-L1 (UCH-L1) enzyme levels were investigated in patients with epilepsy, epileptic seizure, remission period, and healthy individuals. Methods: Three main groups were evaluated, including epileptic seizure, patients with epilepsy in the non-seizure period, and healthy volunteers. The patients having a seizure in the Emergency department or brought by a postictal confusion were included in the epileptic attack group. The patients having a seizure attack or presenting to the Neurology outpatient department for follow up were included in the non-seizure (remission period) group. Results: The UCH-L1 enzyme levels of 160 patients with epilepsy (80 patients with epileptic attack and 80 patients with epilepsy in the non-seizure period) and 100 healthy volunteers were compared. Whereas the UCH-L1 enzyme levels were 8.30 (IQR=6.57‒11.40) ng/mL in all patients with epilepsy, they were detected as 3.90 (IQR=3.31‒7.22) ng/mL in healthy volunteers, and significantly increased in numbers for those with epilepsy (p<0.001). However, whereas the UCH-L1 levels were 8.50 (IQR=6.93‒11.16) ng/mL in the patients with epileptic seizures, they were 8.10 (IQR=6.22‒11.93) ng/mL in the non-seizure period, and no significant difference was detected (p=0.6123). When the UCH-L1 cut-off value was taken as 4.34 mg/mL in Receiver Operating Characteristic (ROC) Curve analysis, the sensitivity and specificity detected were 93.75 and 66.00%, respectively (AUG=0.801; p<0.0001; 95%CI 0.747‒0.848) for patients with epilepsy. Conclusion: Even though UCH-L1 levels significantly increased more in patients with epilepsy than in healthy individuals, there was no difference between epileptic seizure and non-seizure periods.
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Statsenko, Yauhen, Vladimir Babushkin, Tatsiana Talako, Tetiana Kurbatova, Darya Smetanina, Gillian Lylian Simiyu, Tetiana Habuza, et al. "Automatic Detection and Classification of Epileptic Seizures from EEG Data: Finding Optimal Acquisition Settings and Testing Interpretable Machine Learning Approach." Biomedicines 11, no. 9 (August 24, 2023): 2370. http://dx.doi.org/10.3390/biomedicines11092370.
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Deep learning (DL) is emerging as a successful technique for automatic detection and differentiation of spontaneous seizures that may otherwise be missed or misclassified. Herein, we propose a system architecture based on top-performing DL models for binary and multigroup classifications with the non-overlapping window technique, which we tested on the TUSZ dataset. The system accurately detects seizure episodes (87.7% Sn, 91.16% Sp) and carefully distinguishes eight seizure types (95–100% Acc). An increase in EEG sampling rate from 50 to 250 Hz boosted model performance: the precision of seizure detection rose by 5%, and seizure differentiation by 7%. A low sampling rate is a reasonable solution for training reliable models with EEG data. Decreasing the number of EEG electrodes from 21 to 8 did not affect seizure detection but worsened seizure differentiation significantly: 98.24 ± 0.17 vs. 85.14 ± 3.14% recall. In detecting epileptic episodes, all electrodes provided equally informative input, but in seizure differentiation, their informative value varied. We improved model explainability with interpretable ML. Activation maximization highlighted the presence of EEG patterns specific to eight seizure types. Cortical projection of epileptic sources depicted differences between generalized and focal seizures. Interpretable ML techniques confirmed that our system recognizes biologically meaningful features as indicators of epileptic activity in EEG.
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Hashem Attia, Atef, and Ashraf Mahroos Said. "Brain seizures detection using machine learning classifiers based on electroencephalography signals: a comparative study." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 2 (August 1, 2022): 803. http://dx.doi.org/10.11591/ijeecs.v27.i2.pp803-810.
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The <span>paper demonstrates various machine learning classifiers, they have been used for detecting epileptic seizures quickly and accurately through electroencephalography (EEG), in real time. Symptoms of epilepsy are caused abnormal brain activity. Analyzing and detecting epileptic seizures presents many challenges because EEG signals are non-stationary, and the patterns of the seizure vary for each patient. Moreover, the EEG signals are noisy, and this affect the process of seizure detection. On the other hand, Machine learning algorithms are very accurate, adaptive and generalize very well when provided with diverse and big training data and can easily analyze complex structure of the EEG signal despite the noisiness when compared to other methods. With this approach the features of epileptic seizures can be learned and used to correctly identify other seizure cases. The demonstration states a comparison between various classifiers, including random forests, K-nearest neighbors (K-NN), decision trees, support vector machine (SVM), logistic regression and naïve bayes. Different performance metrics is used such as accuracy, receiver operating characteristics (ROC), mean absolute error (MAE), root-mean-square error (RMSE) and most importantly detection time for each algorithm. The Bonn university dataset has been used for demonstration process for the classification of the epileptic seizure.</span>
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Usman, Syed Muhammad, Muhammad Usman, and Simon Fong. "Epileptic Seizures Prediction Using Machine Learning Methods." Computational and Mathematical Methods in Medicine 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/9074759.
Full textAbstract:
Epileptic seizures occur due to disorder in brain functionality which can affect patient’s health. Prediction of epileptic seizures before the beginning of the onset is quite useful for preventing the seizure by medication. Machine learning techniques and computational methods are used for predicting epileptic seizures from Electroencephalograms (EEG) signals. However, preprocessing of EEG signals for noise removal and features extraction are two major issues that have an adverse effect on both anticipation time and true positive prediction rate. Therefore, we propose a model that provides reliable methods of both preprocessing and feature extraction. Our model predicts epileptic seizures’ sufficient time before the onset of seizure starts and provides a better true positive rate. We have applied empirical mode decomposition (EMD) for preprocessing and have extracted time and frequency domain features for training a prediction model. The proposed model detects the start of the preictal state, which is the state that starts few minutes before the onset of the seizure, with a higher true positive rate compared to traditional methods, 92.23%, and maximum anticipation time of 33 minutes and average prediction time of 23.6 minutes on scalp EEG CHB-MIT dataset of 22 subjects.
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Serdyuk, S. E., K. V. Davtyan, S. G. Burd, E. S. Mishina, O. M. Drapkina, and E. I. Gusev. "“Ictal” Bradyarrhythmias in Patients with Drug-Resistant Epilepsy: Results of Long-Term Heart Rhythm Monitoring." Kardiologiia 60, no. 12 (January 19, 2021): 90–96. http://dx.doi.org/10.18087/cardio.2020.12.n1379.
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Aim To determine the type and incidence of ictal bradyarrhythmias in patients with drug-resistant types of epilepsy by long-term electrocardiogram (ECG) monitoring.Material and methods Subcutaneous ECG monitors programed for recording pauses >3 sec and episodes of bradycardia ≤45 bpm were implanted in 193 patients with persistent epileptic seizures without organic pathology of the myocardium. Recording was activated by the patient/family at the onset of epileptic seizure. The follow-up period was 36 months with visits to the clinic every three months.Results For 36 months of monitoring, 6494 ECG fragments were recorded. Ictal bradycardia was observed in 6.7 % of patients, including ictal asystole in 2.6 % of patients. Episodes of bradycardia and asystole during epileptic seizures were transient and developed significantly more frequently in men, patients with long duration of the disease, bilateral tonic-clonic or focal seizures with disorder of consciousness, during sleep, on the background of treatment with several antiepileptic agents, mostly from the group of potassium channel blockers.Conclusion Bradyarrhythmias accompanying epileptic seizures are transient and reproducible from seizure to seizure. They reflect functional changes in the myocardium and do not determine the life prediction for patients with epilepsy without organic pathology of the heart.
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Vieira, Simone Carreiro, Paulo Breno Noronha Liberalesso, Mônica Jaques Spinosa, Adriana Banzzatto Ortega, Alaídes Suzana Fojo Olmos, and Alfredo Löhr Júnior. "First unprovoked seizure: clinical and electrographic aspects." Journal of Epilepsy and Clinical Neurophysiology 12, no. 2 (June 2006): 69–72. http://dx.doi.org/10.1590/s1676-26492006000300004.
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OBJECTIVE: To evaluate classification, EEG tracings and neuroimage following the first episode of unprovoked epileptic seizure in a pediatric population. METHODS: Patients diagnosed with first episode of unprovoked epileptic seizure from May 2000 to May 2005 were included. All subjects were submitted to EEG and cranial CT in the first 72 hours after the event. Seizures were classified according to the ILAE classification criteria of 1981. RESULTS: 387 patients, 214 (55.3%) male, average age 4.2 years. Neuropsicomotor development was normal in 315 (81.4%) patients. Seizure classification: 167 (43.15%) generalized, tonic-clonic being the most frequent of these (105/62.85%), followed by typical absence (22/13.17%), clonic (20/11.98%), tonic (13/7.78%) and atonic (7/4.19%). Focal seizures: 220 (56.85%), complex partial with secondary generalization as the most common of these (81/36.82%). EEG was normal in 208 (53.75%) cases. Brain atrophy was the most frequent abnormality on cranial CT. DISCUSSION: The majority of the children had normal neurodevelopment after a first unprovoked epileptic seizure. Partial seizures were more frequent than generalized seizures. Early EEG identifies interictal paroxysms or focal slowing in virtually half the patients.
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Miziara, Carmen Silvia M. G., and Maria Luiza G. Manreza. "Benign focal epilepsy of childhood with centrotemporal spikes (BECTS): clinical characteristics of seizures according to age at first seizure." Arquivos de Neuro-Psiquiatria 60, no. 2B (June 2002): 390–94. http://dx.doi.org/10.1590/s0004-282x2002000300010.
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BECTS is characterized by the presence of simple partial motor seizures in the face and/or oropharynx, with or without sensory symptoms and often with secondary generalization. These seizures tend to occur more often during sleep or drowsiness. According to some authors, generalized seizures prevail over other types particularly among children aged five or less. The purpose of this study is to determine the characteristics of the first epileptic episode among children with BECTS, grouped by age as of their first epileptic seizure, as well as to analyze how such seizures change over the course of clinical evolution. A total of 61 children were examined, 16 of whom below the age of 5 and 45 above. With regard to the first and recurrent epileptic episodes, our final assessment showed that partial seizures occurred more frequently than generalized tonic-clonic seizures in both groups. Although no conclusive relation could be established between the type of partial seizure (i.e. simple versus complex) and the children's age as of their first epileptic episode, it was possible to correlate the type of epileptic seizure with their clinical evolution, in which case simple partial seizures proved to be more frequent than complex partial seizures. It should be noted that the number of children under the age of five was relatively small, which evinces the need for further studies. It should also be borne in mind that the reported frequency of generalized seizures in these children's first epileptic episode may be due to their parents' lack of attention and familiarity with this pathology and their attendant difficulty in characterizing its clinical symptoms.
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Moosavi, S. Amin, Viktor K. Jirsa, and Wilson Truccolo. "Critical dynamics in the spread of focal epileptic seizures: Network connectivity, neural excitability and phase transitions." PLOS ONE 17, no. 8 (August 23, 2022): e0272902. http://dx.doi.org/10.1371/journal.pone.0272902.
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Focal epileptic seizures can remain localized or, alternatively, spread across brain areas, often resulting in impairment of cognitive function and loss of consciousness. Understanding the factors that promote spread is important for developing better therapeutic approaches. Here, we show that: (1) seizure spread undergoes “critical” phase transitions in models (epileptor-networks) that capture the neural dynamics of spontaneous seizures while incorporating patient-specific brain network connectivity, axonal delays and identified epileptogenic zones (EZs). We define a collective variable for the spreading dynamics as the spread size, i.e. the number of areas or nodes in the network to which a seizure has spread. Global connectivity strength and excitability in the surrounding non-epileptic areas work as phase-transition control parameters for this collective variable. (2) Phase diagrams are predicted by stability analysis of the network dynamics. (3) In addition, the components of the Jacobian’s leading eigenvector, which tend to reflect the connectivity strength and path lengths from the EZ to surrounding areas, predict the temporal order of network-node recruitment into seizure. (4) However, stochastic fluctuations in spread size in a near-criticality region make predictability more challenging. Overall, our findings support the view that within-patient seizure-spread variability can be characterized by phase-transition dynamics under transient variations in network connectivity strength and excitability across brain areas. Furthermore, they point to the potential use and limitations of model-based prediction of seizure spread in closed-loop interventions for seizure control.