Objective To explore the effects of propofol and thiopental sodium injection on convulsive seizure in electro-convulsive therapy(ECT) and to provide evidence to help the selection of intravenous anaesthetics in improved ECT. Methods Total of 111 patients who received ECT in the 3rd Pepole’s Hospital of Panzhihua from July to December 2005 were divided into a thiopental sodium group (n =62) and a propofol group (n =49). These patients received intravenous anaesthesia with suxamethonium plus thiopental sodium or propofol for the implementation of ECT, respectively. The status of convulsive seizure was compared between the two groups. Results There were no significant differences between the two groups in terms of main demographic data, disease category and ECT parameters (Pgt;0.05). Motor seizure and electricity discharge lasted significantly longer in the propofol group than in the thiopental sodium group (Plt;0.01). Conclusion Thiopental sodium can increase the excitation threshold of brain cortical neurons and decrease the level of convulsive seizure induced by ECT. Propofol may decrease the excitation threshold, and increase the level of convulsive seizure under the same ECT parameters, but may have the potential to induce epileptic seizure.
ObjectiveTo investigate the etiology, clinical features, treatment, and prognosis of Partial status epilepticus (PSE). MethodsSeventeen PSE patients were hospitalized in the Department of Neurology at the First Hospital of Jilin University from April 2013 to June 2015. Clinical data were retrospectively analyzed. ResultsA total of 17 patients, 8 male and 9 female, 18~91years old, at mean age (48.90±21.17) years were included. About 12 cases (70.59%) had acute symptomatic status epilepticus, the etiologies including central nervous system inflammation (5 cases), cortical infarction (3 cases), metabolic disorder (1 case), hypoxic-ischemic encephalopathy (1 case), space-occupying lesions(1 case) and degeneration (1 case); four cases (23.53%) were diagnosed with epilepsy, one case (5.88%) had no definite pathogenesis. The seizure types included complex partial status epilepticus (8 cases, 47.06%), complex part of the secondary comprehensive status epilepticus (3 cases, 17.65%), supplementary motor area (SMA) status epilepticus (4 cases, 23.53%), epilepsia partialis continua (EPC) (1case, 5.88%)and complex partial status epilepticus & aura continua (1case, 5.88%). Nine cases (52.94%) were effective after one hour treament, eight cases (47.06%) were negative. 17 cases are followed-up and 4 cases lost, the average follow-up time is (10.89±8.64) months. 8 cases are completely seizure free, and 3 cases have experience less seizures or the symptom is relived; the other 2 cases die from Creutzfeldt-Jacob desease(case No.10) and Respiratory failure(case No.12). ConclusionsThe inpatients of partial status epilepticus are mostly "situation related". Patients with clinical suspect should be administrated with long term video-Electroencephalogram(EEG) monitoring timely. Early diagnosis, treatment and the aggressive treatment can help to improve the prognosis. Patients of encephalitis usually progress into refractory status epilepticus, the anesthetic drugs should be used as soon as possible.
ObjectiveImpaired breathing during and following seizures is an important cause of sudden unexpected death in epilepsy (SUDEP), but the network mechanisms by which seizures impair breathing have not been thoroughly investigated. Progress would be greatly facilitated by a model in which breathing could be investigated during seizures in a controlled setting. MethodRecent work with an acute Long-Evans rat model of limbic seizures has demonstrated that depression of brainstem arousal systems may be critical for impaired consciousness during and after seizures. We now utilize the same rat model to investigate breathing during partial seizures with secondary generalization. ResultBreathing is markedly impaired during seizures(P < 0.05;n=21), and that the severity of breathing impairment is strongly correlated with the extent of seizure propagation (Pearson R=-0.73;P < 0.001;n=30). ConclusionSeizure propagation could increase the severity of breathing impairment caused by seizures. Based on these results, we suggest that this animal model would help us to improve understanding of pathways involved in impairment of breathing caused by seizures and this is an important initial step in addressing this significant cause of SUDEP in people living with epilepsy.
ObjectiveThe optimal target of deep brain stimulation (DBS) for treating intractable epilepsy is still undefined. Cumulative studies suggest that the mediodorsal thalamic nucleus (MD) is involved in seizure activity, the purpose of this study was to investigate the effect of high frequency stimulation in MD on pentylenetetrazole (PTZ)-induced seizures in rats. MethodsThe experimental rats (Male Sprague-Dawley rats 280-350 g) were all provided by Experimental Animal Center, Zhejiang Academy of Medical Science, Hangzhou, China. The rats were given unilateral or bilateral stimulation of the MD at 100 Hz (HFS group) and sham stimulation, others were given unilateral stimulation of the MD at 1 Hz (LFS group). EEGs in the cortex and seizure behavior were recorded with the Neuroscan system at the same time. ResultsNeither LFS nor HFS of the MD changed the latency to the first spikes or EEG manifestations for stage 3 and stage 5 seizures; animals receiving unilateral or bilateral HFS of the MD decreased the number of stage 5 EEG seizure synchronized with the convulsive episodes; LFS and sham stimulation showed multiple periods of continuous spikes which accompanied stage 5 or stage 4 seizures. HFS of unilateral or bilateral MD, but not LFS, decreased the seizure stage, the number of clonic movement episodes, and the duration of acute PTZ-induced seizures. The average latency to onset of myoclonic jerks did not differ among groups. Unilateral and bilateral HFS of the MD had a similar antiepileptic effect. ConclusionHFS of the MD may be of value as a new antiepileptic approach for patients with generalized epilepsy, besides, the seizure model, should be fully considered in clinical application.
ObjectiveTo explore the clinical value of video-electroencephalograph (VEEG) for non-epileptic seizures disease in children. MethodsThe clinical data of 58 children with non-epileptic seizures (NES) diagnosed by VEEG from October 2010 to November 2012 were retrospectively analyzed. ResultsIn 50 out of 58 patients in the process of monitoring,the NES clinical onset was found while no synchronized epileptiform discharges was observed;in five patients with NES combined with epilepsy,no epileptiform discharges was found by VEEG at the clinical onset of NES;there were 3 patients with epileptiform discharges without seizures,who had no history of epilepsy,but non-synchronized clinical nonparoxysmal epileptiform discharges was found by VEEG monitoring. ConclusionVEEG is an effective diagnosis method for NES and seizures in children,which could be regarded as the gold standard for NES diagnosis.
Studies have shown that the clinical manifestation of patients with neuropsychiatric disorders might be related to the abnormal connectivity of brain functions. Psychogenic non-epileptic seizures (PNES) are different from the conventional epileptic seizures due to the lack of the expected electroencephalographically epileptic changes in central nervous system, but are related to the presence of significant psychological factors. Diagnosis of PNES remains challenging. We found in the present work that the connectivity between the frontal and parieto-occipital in PNES was weaker than that of the controls by using network analysis based on electroencephalogram (EEG) signals. In addition, PNES were recognized by using the network properties as linear discriminant nalysis (LDA) input and classification accuracy was 85%. This study may provide a feasible tool for clinical diagnosis of PNES.
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.
The clinical electroencephalogram (EEG) monitoring systems based on personal computer system can not meet the requirements of portability and home usage. The epilepsy patients have to be monitored in hospital for an extended period of time, which imposes a heavy burden on hospitals. In the present study, we designed a portable 16-lead networked monitoring system based on the Android smart phone. The system uses some technologies including the active electrode, the WiFi wireless transmission, the multi-scale permutation entropy (MPE) algorithm, the back-propagation (BP) neural network algorithm, etc. Moreover, the software of Android mobile application can realize the processing and analysis of EEG data, the display of EEG waveform and the alarm of epileptic seizure. The system has been tested on the mobile phones with Android 2.3 operating system or higher version and the results showed that this software ran accurately and steadily in the detection of epileptic seizure. In conclusion, this paper provides a portable and reliable solution for epileptic seizure monitoring in clinical and home applications.
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.
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.