ObjectiveTo investigate the clinical characteristics of epileptics with pregnancy and then provide reference for standardized management of epileptics with pregnancy. MethodsFrom June 2012 to June 2021, epileptics with pregnancy who delivered in Jinan Central Hospital were selected as the research subjects. The clinical data such as the application of Antiseizure medications (ASMs) during pregnancy, seizure frequency, pregnancy outcomes, delivery ways, offspring feeding ways and the incidence of complications were investigated and analyzed. ResultsAmong 36 epileptics with pregnancy, 20 cases (55.56%) were treated with ASMs alone, 5 cases (13.88%) were treated with combined medication, and 11 cases (30.56%) were treated without ASMs during pregnancy. 15 cases (41.67%) adhered to systematic application of ASMs, 17 cases (47.22%) did not adhere to systematic application of ASMs, and 4 cases (11.11%) had unknown medication history. The frequency of seizures increased in 5 cases, decreased in 7 cases and unchanged in 24 cases during pregnancy. Pregnancy outcomes: full-term delivery in 33 cases (91.67%), preterm delivery in 1 case (2.78%) and abortion in 2 cases (5.56%). Delivery mode: cesarean section in 31 cases (91.18%), vaginal delivery in 3 cases (8.82%). After delivery, 4 cases (11.76%) were fed with milk powder and 30 cases (88.24%) were breast-fed. Complications: There were 6 cases complicated with anemia (16.67%), 5 cases complicated with gestational hypertension (13.89%), 3 cases complicated with gestational diabetes (8.33%), 4 cases complicated with premature rupture of membranes (11.11%), 2 cases complicated with fetal growth restriction (5.56%), 2 cases complicated with oligohydramnios (5.56%), 3 cases complicated with fetal distress (8.33%) and 3 cases complicated with neonatal asphyxia (8.33%). ConclusionsThe proportion of epileptics with pregnancy who were systematically treated with ASMs was low and the seizures were poorly controlled. There is a lack of standardized management for such patients in clinical practice.
ObjectiveTo investigate the efficacy and safety of the phase Ⅰ corpus callosotomy in the treatment of adult refractory epilepsy. MethodsWe conducted a retrospective analysis of 56 adults with intractable epilepsy in Tangdu Hospital from January 2011 to July 2016.All patients were treated for the phase Ⅰ total corpus callosotomy, followed up 1~5 years after surgery. Results14 cases (25.0%) patients achieved complete seizure free after surgery, 19 cases (33.9%) whose seizures reduced more than 90%, 10 cases (17.9%) reduced between 50%~90%, 7 cases (12.5%) between 30%~50%, 6 cases (10.7%) decreased below 30%; Drop attacks of 47 cases (83.9%) patients disappeared. Postoperative complications occurred in 13 cases(23.2%), and most of them recovered well. 5 cases(8.9%) had long-term sensory disassociation, no serious complications and death. The percentage of patients reporting improvement in quality of life was 67.9%. ConclusionsFor patients with intractable epilepsy who can not undergo focal resection, Ⅰ phase total corpus callosotomy has a certain effect on reducing seizure frequency, eliminating drop attacks, and improving the quality of life.
Overexcitation of neurons in brain can lead to epilepsy seizures, and the key to control epilepsy seizures is to keep the balance between excitation and inhibition. In this paper, epileptiform index is presented to denote the seizure degree and used as control variable of PID controller to control epilepsy seizures. Neural mass model (NMM) is used as a test-bed to simulate the change of seizure degree with the increase of excitatory strength and two control strategies. Experimental results showed that the increase of excitatory strength could lead to a substantial increase of epileptiform index and trigger seizures. PID controller which is used to decrease excitatory strength or increase inhibitory strength can keep excitation-inhibition balance and inhibit epilepsy seizures. Epileptiform index can describe the linear and nonlinear feature of electroencephalogram (EEG) comprehensively, and PID controller is simple and independent of underlying physiological structure, which lays the foundation for its application in the clinic.
It is very important for epilepsy treatment to distinguish epileptic seizure and non-seizure. In this study, an automatic seizure detection algorithm based on dual density dual tree complex wavelet transform (DD-DT CWT) for intracranial electroencephalogram (iEEG) was proposed. The experimental data were collected from 15 719 competition data set up by the National Institutes of Health (NINDS) in Kaggle. The processed database consisted of 55 023 seizure epochs and 501 990 non-seizure epochs. Each epoch was 1 second long and contained 174 sampling points. Firstly, the signal was resampled. Then, DD-DT CWT was used for EEG signal processing. Four kinds of features include wavelet entropy, variance, energy and mean value were extracted from the signal. Finally, these features were sent to least squares-support vector machine (LS-SVM) for learning and classification. The appropriate decomposition level was selected by comparing the experimental results under different wavelet decomposition levels. The experimental results showed that the features selected in this paper were different between seizure and non-seizure. Among the eight patients, the average accuracy of three-level decomposition classification was 91.98%, the sensitivity was 90.15%, and the specificity was 93.81%. The work of this paper shows that our algorithm has excellent performance in the two classification of EEG signals of epileptic patients, and can detect the seizure period automatically and efficiently.
Febrile seizure is one of the most common emergencies in children, accounting for about 30% of all types of children, and the most common among children aged 6 months to 5 years. At the same time, children in this age group are at the peak of growth and development, and the content of various trace elements in the body is prone to abnormalities. At present, there are few related studies on febrile seizure and trace elements in children. This paper summarizes the related studies on febrile seizure and trace elements in order to provide theoretical guidance for the prevention and treatment of febrile seizure
Gelastic seizure (GS) is a type of epilepsy characterized primarily by inappropriate bursts of laughter, with or without other epileptic events. Based on the timing of symptoms, the presence of emotional changes, and disturbances of consciousness, GS is classified into simple and complex types. The generation of laughter involves two major neural pathways: the emotional pathway and the volitional pathway. The neural network involved in GS includes structures such as the frontal lobe, insula, cingulate gyrus, temporal lobe, and brainstem.The most common cause of GS is a hypothalamic hamartoma, and stereotactic electroencephalography can record discharges from the lesion itself. Surgical removal of the hypothalamic hamartoma can result in immediate cessation of GS in the majority of patients, while some may experience partial improvement with persistent epileptic-like discharges detectable on scalp electroencephalography (EEG). Early surgical intervention may improve prognosis.In cases of non-hypothalamic origin of GS with no apparent imaging abnormalities, focal discharges are often observed on EEG and these cases respond well to antiepileptic drugs. Conversely, patients with structural abnormalities suggested by imaging studies tend to have multifocal discharges and a poorer response to medication. In a small subset of medically refractory non-hypothalamic GS, surgical intervention can effectively control symptoms.This article provides a comprehensive review of the etiology, neural networks involved, EEG characteristics, and treatment options for GS, with the goal of improving understanding of this relatively rare type of epileptic seizure.
In recent years, epileptic seizure detection based on electroencephalogram (EEG) has attracted the widespread attention of the academic. However, it is difficult to collect data from epileptic seizure, and it is easy to cause over fitting phenomenon under the condition of few training data. In order to solve this problem, this paper took the CHB-MIT epilepsy EEG dataset from Boston Children's Hospital as the research object, and applied wavelet transform for data augmentation by setting different wavelet transform scale factors. In addition, by combining deep learning, ensemble learning, transfer learning and other methods, an epilepsy detection method with high accuracy for specific epilepsy patients was proposed under the condition of insufficient learning samples. In test, the wavelet transform scale factors 2, 4 and 8 were set for experimental comparison and verification. When the wavelet scale factor was 8, the average accuracy, average sensitivity and average specificity was 95.47%, 93.89% and 96.48%, respectively. Through comparative experiments with recent relevant literatures, the advantages of the proposed method were verified. Our results might provide reference for the clinical application of epilepsy detection.
ObjectiveTo explore the effects of cytokines on Febrile seizures (FS) in children with febrile seizures (Febrile seizures), febrile seizures duration and prognosis, and to explore the correlation between cytokines and the clinical manifestations and prognosis of FS. MethodsA retrospective analysis was performed on 121 children with FS (77 cases in the simple FS group and 44 cases in the complex FS group) who were treated in the pediatrics department of the Maternal and Child Health Hospital of Inner Mongolia Autonomous Region from January 2021 to October 2022 as the experimental group, including 71 males and 50 females, with a male-to-female ratio of 1.42:1, according to the type of attack (93 cases in the comprehensive group, 44 cases in the complex FS group). The focal group (28 cases) and convulsion duration (91 cases in <5 min group and 30 cases in ≥5 min group) were divided into groups, and 127 cases of children with fever but no convulsions were compared with the control group. In addition, 121 children with FS were followed up for 1 year by neurology specialist outpatient department and telephone follow-up. According to the follow-up, they were divided into the first course group, the relapse group and the secondary epilepsy group, so as to further explore the correlation between cytokines and the prognosis of children with FS. ResultsExperimental group compared with control group: Serum IL-1β (1.38 pg/mL), IL-2 (2.26 pg/mL), IL-4 (1.53 pg/mL), IL-6 (10.51 pg/mL), IL-10 (3.09 pg/mL), IL-12p70 (1.74 pg/mL), TNF-α (2.11 pg/mL), IFN-γ (46.56 pg/mL), IL-1β (1.38 pg/mL), IL-1β (1.26 pg/mL), IL-4 (1.53 pg/mL), IL-6 (10.51 pg/mL), IL-10 (3.09 pg/mL), IL-12P70 (1.74 pg/mL), TNF-α (2.11 pg/mL), IFN-γ (46.56 pg/mL). IFN-α (25.92 pg/mL) levels were higher, and the differences were statistically significant (P<0.05). There was no significant difference between the simple group and the complex group (P>0.05). <5 min group compared with control group: serum levels of IL-2 (2.32 pg/mL), IL-4 (1.53 pg/mL), IL-6 (9.65 pg/mL), IL-12p70 (1.74 pg/mL), TNF-α (2.11 pg/mL), IFN-γ (44.63 pg/mL), IFN-α (29.67 pg/mL) were higher, and the differences were statistically significant (P<0.05). Compared with control group, the levels of IL-2 (2.06 pg/mL), IL-6 (14.67 pg/mL), IL-12p70 (1.97 pg/mL), IFN-γ (58.56 pg/mL) and IFN-α (17.50 pg/mL) in ≥5 min group were higher, and the differences were statistically significant (P<0.05). ROC curve analysis showed that serum IFN-α had a high predictive value for FS onset, the cut-off point was 8.64pg/ml, and the sensitivity and specificity were 75.63% and 76.38%, respectively. There was no significant difference between the first course of disease group, relapse group and secondary epilepsy group. ConclusionSerum proinflammatory cytokines IL-1β, IL-2, IL-6, IL-12p70, TNF-α, IFN-γ, IFN-α and anti-inflammatory cytokines IL-4 and IL-10 are involved in the pathogenesis of FS. There was no correlation between the simplicity and complexity of serum cytokines. IL-2, IL-6, IL-12p70, IFN-γ, IFN-α were positively correlated with the duration of convulsion. When serum IFN-α>8.64 pg/ml, the possibility of FS attack increased.
Epilepsy is a common chronic disease of the nervous system, which has certain adverse effects on the cognitive, psychological and social functions of the patients. To date, anti-seizure medications (ASMs) remain the first-line treatment option for epilepsy, but many patients with epilepsy still do not have effective seizure control when multiple ASMs are used in combination. Therefore, there is an urgent need for a new target and mechanism ASMs to bring about new treatment options and hope for patients with intractable epilepsy. Perampanel, a new third-generation ASMs, whereas second-generation ASMs tend to exert anti-seizure effects mainly by regulating ion channels or enhancing related mechanisms such as gamma-aminobutyric acid (GABA) effects, perampanel exerts its effects mainly by targeting the excitatory neurotransmitter glutamate. Perampanel is the first selective α-amino-3-hydroxy-5-methyl-4-isoxazole-propionate (AMPA) receptor antagonist and the first selective inhibitory ASMs for excitatory postsynaptic function. Because of its unique target and mechanism, it has been approved by many countries in the world for adjuvant additive therapy and monotherapy for patients with focal and general epilepsy. In addition, with the discovery of the neuroprotective, antioxidant, neurotransmitter regulation effects of perampanel, it also provides a new potential choice for the treatment of other diseases. This article mainly reviews the mechanism of action, pharmacokinetics, clinical trials and treatment of other diseases other than epilepsy of perampanel.
Epilepsy and sleep disorders are common health problems in the world, and sleep disorders as a common comorbidity of epilepsy patients, there are high prevalence, low attention rate, low treatment rate phenomenon. In addition, epilepsy and sleep disorders can affect each other, exacerbating the onset of their own symptoms. Therefore, timely identification and treatment of these comorbidities are crucial to improve patients' quality of life, increase daytime alertness and reduce the occurrence of seizures. This article reviews the effects of different anti-seizure programs on patients with epilepsy comorbidities sleep disorders, in order to provide references for how to better choose epilepsy treatment measures for these patients.