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.
Seizures during sleep increase the probability of complication and sudden death. Effective prediction of seizures in sleep allows doctors and patients to take timely treatments to reduce the aforementioned probability. Most of the existing methods make use of electroencephalogram (EEG) to predict seizures, which are not specific developed for the sleep. However, EEG during sleep has its characteristics compared with EEG during other states. Therefore, in order to improve the sensitivity and reduce the false alarm rate, this paper utilized the characteristics of EEG to predict seizures during sleep. We firstly constructed the feature vector including the absolute power spectrum, the relative power spectrum and the power spectrum ratio in different frequencies. Secondly, the separation criterion and branch-and-bound method were applied to select features. Finally, support vector machine classifier were trained, which is then employed for online prediction. Compared with the existing method that do not consider the characteristics of sleeping EEG (sensitivity 91.67%, false alarm rate 9.19%), the proposed method was superior in terms of sensitivity (100%) and false alarm rate (2.11%). This method can improve the existing epilepsy prediction methods and has important clinical value.
Objective To retrospectively analyze the epidemiology, clinical characteristics and causes of misdiagnosis of Juvenile myoclonic epilepsy (JME) in Xinjiang Uygur Autonomous Region, so as to provide basis for improving the diagnosis and treatment of JME. Methods 979 patients with epilepsy in Xinjiang Uygur Autonomous Region were analyzed retrospectively. There.were515males and 464females,average.age(18.66+8.31)years,.The epidemiological characteristics of JME were analyzed. The clinical characteristics, EEG, treatment effect and prognosis of patients diagnosed with JME were analyzed. The causes of misdiagnosis, missed diagnosis and delayed treatment were analyzed. Results The proportion of JME in 979 patients with epilepsy was 1.4%, a total of 14 cases. The median age of onset was (15+5.83) years, the median time from onset to treatment was 3 years, and the median time from onset to diagnosis was 6 years. All patients showed myoclonic seizures, 13 cases were complicated with generalized tonic clonic seizures, and 4 cases were accompanied by absence seizures. EEG findings include normal background activity, 3-6 Hz generalized spikes or frontal dominant multiple spikes at the beginning of arousal. seven patients were treated with levetiracetam, and the other seven patients were treated with lamotrigine and / or sodium valproate. Incomplete collection of medical history and failure to describe the medical history in detail are the main reasons for delaying diagnosis. Conclusion Juvenile myoclonic epilepsy is an treatable disease, but it is easy to be misdiagnosed. The rate of misdiagnosis and missed diagnosis of JME in Xinjiang is higher, and the delay of diagnosis and treatment is longer. The inquiry of more detailed and demonstrative medical history is of great significance to improve the diagnostic accuracy.
Seizure clusters, a severe form of epilepsy requiring urgent intervention, are challenging to manage in out-of-hospital settings due to limitations of traditional benzodiazepine administration routes. Diazepam nasal spray (DZP-NS), a novel intranasal formulation, achieves rapid absorption through the nasal mucosa, bypassing first-pass metabolism, with bioavailability comparable to rectal gel and faster onset. Clinical studies demonstrate its high efficacy in treating seizure clusters and prolonged seizures (≥5 minutes), with an initial control rate of 87.4% and low second-dose utilization (12.6%). No severe adverse reactions, such as cardiorespiratory depression, were observed. Long-term use (12 months) showed no tolerance development, significantly extending seizure intervals (SEIVAL) (from 12.2 to 25.7 days) and improving quality of life scores, particularly in "epilepsy-related concerns" and "social functioning" domains. The non-invasive delivery method was favored by over 80% of patients and healthcare providers for its convenience compared to rectal administration. Subgroup analyses confirmed consistent safety and efficacy across genders, ages, concomitant medications (including cannabidiol), and patients with allergy histories. In conclusion, DZP-NS provides an efficient, safe, and socially accepted out-of-hospital rescue therapy for seizure clusters, positioning it as a potential cornerstone in standardized epilepsy emergency care.
ObjectiveTo report the clinical manifestations and genetic characteristics of a child with epilepsy caused by a de novo mutation in the HCN1 gene. MethodsThe clinical data and HCN1 gene mutation characteristics of a child with epilepsy admitted to our hospital in May 2020 were analyzed, and the relevant domestic and foreign literature were reviewed. ResultsA 7-month-old male child developed epileptic seizures for the first time, with various forms of seizures, beginning with atonic seizures, followed by febrile seizures, focal seizures, generalized tonic-clonic seizures, and absence seizures. During hospitalization, his cerebrospinal fluid (CSF), hematuria tandem mass spectrometry (HVMS), cranial imaging and other examinations showed no obvious abnormality. The results of genetic testing showed that there was a heterozygous missense mutation c.839A>C (p.Gln280Pro) in the second exon region of the HCN1 gene of the child, and neither of his parents carried the mutation, suggesting that the mutation is novel. According to the guidelines of America Society of Medical Genetics and Genomics (ACMG), the variation was rated as likely pathogenic. The child was diagnosed with HCN1 gene mutation-related epilepsy and was treated with a combination of levetiracetam and sodium valproate. The child’s epilepsy was well controlled and discharged when his condition was stable. Following up to now after discharge, the patient is prone to convulsions during the course of febrile disease, but his growth and development level is normal. Literature review shows that HCN1 gene mutation-related epilepsy is mainly de novo in patients, most of which are located in the 2nd and 4th exon regions. ConclusionsFor children with clinically unexplained early-onset epilepsy, gene sequencing should be performed as soon as possible to analyze possible genetic etiology, which will help confirm the diagnosis and guide treatment.
ObjectiveTo investigate the classification of seizures, etiology,EEG examination, treatment and prognosis of senile epilepsy. MethodsThe clinical data of 92 senile epileptsy patients in the Second Affiliated Hospital Of Chongqing Medical University from January 2012 to September 2015 were retrospectively analyzed. ResultsFrom the selected sample,15 cases suffered from SPS(16.3%),22 cases suffered from CPS(23.9%),40 cases suffered from GTCS(43.5%),4 cases suffered from partial seizures with secondary generalization(4.3%),11 cases suffered from both partial seizures and generalized seizures(12.0%).The common causes include cerebrovascular disease (57.6%),intracranial tumors (10.9%), degenerative brain diseases (7.6%) and so on.The abnormal ratio of REEG and AEEG was 87.1% and 91.7% respectively.The ratio of typical epileptiform activity in the REEG and AEEG was 22.6% and 70.8% respectively.82 cases(89.1%) were treated with AED,but only 69 cases had been taking orally AED among the patients treated with AED.57 cases(82.6%) were on monotherapy.55 cases (67.1%) were controlled effectively with drug treatment,11 cases (13.4%) were ineffective and 16 patients (19.5%) died. Advanced age was the important cause of death. Age was positively correlated with the fatality rate.9 cases(10.9%) appeared side effect,the frequency of sleepiness was the highest among all the adverse reactions. ConclusionThe majority of senile epilepsy suffer from symptomatic epilepsy.The main cause is cerebrovascular disease,the generalized tonic-clonic seizures constituted a high proprotion in the sample.The ratio of typical epileptic discharge in the REEG was low from senile patients with epilepsy,we recommend the AEEG examination in the senile patients suspected with epilepsy. AED has excellent therapeutic effects in senile epileptics,and a few patients appeared light adverse reactions.
The electroencephalogram (EEG) has proved to be a valuable tool in the study of comprehensive conditions whose effects are manifest in the electrical brain activity, and epilepsy is one of such conditions. In the study, multi-scale permutation entropy (MPE) was proposed to describe dynamical characteristics of EEG recordings from epilepsy and healthy subjects, then all the characteristic parameters were forwarded into a support vector machine (SVM) for classification. The classification accuracies of the MPE with SVM were evaluated by a series of experiments. It is indicated that the dynamical characteristics of EEG data with MPE could identify the differences among healthy, inter-ictal and ictal states, and there was a reduction of MPE of EEG from the healthy and inter-ictal state to the ictal state. Experimental results demonstrated that average classification accuracy was 100% by using the MPE as a feature to characterize the healthy and seizure, while 99.58% accuracy was obtained to distinguish the seizure-free and seizure EEG. In addition, the single-scale permutation entropy (PE) at scales 1-5 was put into the SVM for classification at the same time for comparative analysis. The simulation results demonstrated that the proposed method could be a very powerful algorithm for seizure prediction and could have much better performance than the methods based on single scale PE.
Modified electroconvulsive therapy (MECT) and magnetic seizure therapy (MST) are effective treatments for severe major depression. MECT has better efficacy in the treatment than MST, but it has cognitive and memorial side effects while MST does not. To study the causes of these different outcomes, this study contrasted the electric filed strength and spatial distribution induced by MECT and MST in a realistic human head model. Electric field strength induced by MECT and MST are simulated by the finite element method, which was based on a realistic human head model obtained by magnetic resonance imaging. The electrode configuration of MECT is standard bifrontal stimulation configuration, and the coil configuration of MST is circular. Maps of the ratio of the electric field strength to neural activation threshold are obtained to evaluate the stimulation strength and stimulation focality in brain regions. The stimulation strength induced by MECT is stronger than MST, and the activated region is wider. MECT stimulation strength in gray matter is 17.817 times of that by MST, and MECT stimulation strength in white matter is 23.312 times of that by MST. As well, MECT stimulation strength in hippocampi is 35.162 times of that by MST. More than 99.999% of the brain volume is stimulated at suprathreshold by MECT. However, MST activated only 0.700% of the brain volume. The stimulation strength induced by MECT is stronger than MST, and the activated region is wider may be the reason that MECT has better effectiveness. Nevertheless, the stronger stimulation strength in hippocampi induced by MECT may be the reason that MECT is more likely to give rise to side effects. Based on the results of this study, it is expected that a more accurate clinical quantitative treatment scheme should be studied in the future.
ObjectiveTo explore and clarify the relationship between epileptic seizure and inducing factors. Avoid inducing factors and reduce epileptic seizure, so as to improve the quality of life in patients with epilepsy.MethodsClinical data of 604 patients diagnosed with epilepsy in Xijing Hospital of Air Force Military Medical University from January 2018 to January 2019 were collected. The clinical data of patients with epilepsy were followed up 6 months.ResultsAmong the 604 patients, 318 (52.6%) were seizure-free in the last 6 months, 286 (47.4%) had seizures. 169 (59.1%) had seizures with at least one inducing factor. Common inducing factors: 123 cases of sleep disorder (72.8%), 114 cases of emotion changes (67.5%), 87 cases of irregular medication (51.5%), 97 cases of diet related (57.4%), 33 cases of menstruation and pregnancy (19.5%), etc. Using the χ2 test, seizures with age, gender differences had no statistical significance (P > 0.05), but seizure type was statistically different between inducing factors. In generalized seizures, tonic-clonic seizures associated with sleep deprivation (χ2= 0.189), absence seizures and anger (χ2= 0.237), pressure (χ2= 0.203), irregular life (χ2= 0.214). In the focal seizures, focal motor seizures was correlated with coffee consumption (χ2=0.145), focal sensory seizures with cold (χ2=0.235), electronic equipment use (χ2 =0.153), satiety (χ2 =0.257). Complex partial seizures was correlated with anger (χ2 =0.229), stress (χ2 =0.187), and cold (χ2 =0.198). The secondarily generalized seizures was correlated with drug missing (χ2 =0.231), sleep deprivation (χ2 =0.158), stress (χ2 =0.161), cold (χ2 =0.263), satiety (χ2 =0.182). Among the inducing factors, sleep deprivation was correlated with anger (χ2 =0.167), fatigue (χ2 =0.283), and stress (χ2 =0.230).ConclusionsEpileptic seizure were usually induced by a variety of factors. Generalized seizures were associated with sleep disorders, emotional changes, stress, irregular life, etc. While focal seizures were associated with stress, emotional changes, sleep disorders, cold, satiety, etc. An analysis of the triggers found that sleep deprivation was associated with anger, fatigue, and stress. Therefore, to clarify the inducing factors of epileptic seizure, avoid the inducing factors as much as possible, reduce the harm caused by seizures, and improve the quality of life of patients.
Objective To explore the clinical characteristics of patients with combined use of ≥2 kinds of anti-seizure medications in Tibetan plateau. Methods Epilepsy patients who were hospitalized in the People’s Hospital of Tibet Autonomous Region from September 2018 to September 2023 and used ≥2 kinds of anti-seizure medications in combination were selected. Their demographic data such as gender, age, and ethnicity, as well as diagnostic information, medication and other clinical data were collected, and relevant demographic and clinical characteristics were analyzed. In the later stage, telephone follow-up was used to record medication and epileptic seizure control. Results A total of 2295 patients with epilepsy were included, of which 142 (6.2%) met the inclusion criteria, of which 133 (93.7%) were Tibetans. There were more males than females (86 vs. 56, P<0.05), and more minors and young patients than middle-aged and elderly patients (106 vs. 36, P<0.05). 87.3% of the patients underwent magnetic resonance imaging (MRI) or computed tomography (CT), and 71.1% of the patients were abnormal. The main cause of epilepsy was structural etiology (84/142, 59.2%). The most common combination was two drugs (127/142, 89.4%). The largest proportion of combination was sodium valproate and levetiracetam (46/142, 32.4%). After standardized multi-drug combination therapy, the average frequency of epilepsy seizures was significantly reduced compared with the baseline, and the difference was statistically significant (P<0.05). Among the 98 patients aged ≥14 years, 15 cases (15.3%) had drug-refractory epilepsy, 18 cases (18.4%) had seizures controlled by standardized combination medication, 16 cases (16.3%) had seizures controlled by reducing combination medication to a single drug, 5 cases (5.1%) had good control and had stopped medication, 3 cases (3.1%) had frequent epileptic seizures due to poor medication compliance, 15 cases (15.3%) had irregular medication, 17 cases (17.3%) died, and 9 cases (9.2%) were lost. Conclusion The proportion of epilepsy treated with multiple drugs and refractory to drugs was lower than the conclusion of previous studies, and the anti-epileptic effect of multiple drugs was positive. Structural causes (stroke, etc.) are the main causes of epilepsy, and brain parasitic infection is a unique factor of high-altitude epilepsy. Strengthening the standardized use of drugs will help improve the treatment status and prognosis of patients.