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Purpose/Significance The recent applications of machine learning in epilepsy seizure prediction,diagnosis prediction,seizure detection,efficacy prediction of antiepileptic drugs,and epilepsy surgery prediction are summarized and analyzed.Method/Processs Literatures are searched through PubMed to summarize the performance of each machine learning model and the challenges exist-ing in machine learning technology.Result/Conclusion Machine learning plays an important role in the diagnosis and treatment of epi-lepsy,and can provide reference for clinical doctors'diagnosis and treatment work.
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Autoimmune encephalitis (AE) is closely related to epileptic seizure, which is a common clinical manifestation or even the only symptom at acute phase of AE. Most patients do not develop seizures after treatment at acute or subacute stages, and these patients are classified as acute symptomatic seizures secondary to AE (ASSAE). Only a minority of patients will eventually develop autoimmune associated epilepsy (AAE). At present, no unified standard for clinical diagnosis is noted between ASSAE and AAE, but some differences exist in definition, pathogenesis, diagnosis and treatment. This paper summarizes the similarities and differences between ASSAE and AAE in the above aspects, aiming at providing help for clinicians to differentiate the diagnosis of the two diseases.
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@#ObjectiveTo study the effect and mechanism of vagus nerve stimulation(VNS) on seizure in animal with epilepsy.MethodsSeizures of 34 rats and 8 rabbits were induced by Penicillin, Kainic acid(KA) and Strychnice respectively. Electrocorticographic(ECoG), electrical activition of hippocampal neurons and behaviour were observed to evidence the effects of left intermittent VNS .ResultsVNS could suppress seizures in animal models with epilepsy. There were significant changes in epileptiform ECoG, discharges of hippcampal neuron and behaviour. ConclusionSomatic seizure can be effectively inhibited by visceral afferent inputs through integration in cortical and hippocampal parts.
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Objective To determine the clinical characteristics of post ictal headache (PIH) and clinical risk factors associated with the occurrence of PIH in patients with localization related epilepsy.Methods The subjects were 47 patients with temporal lobe epilepsy (TLE),21 patients with occipital lobe epilepsy (OLE),and 29 patients with frontal lobe epilepsy (FLE).The subjects were directly asked whether headaches occurred just after seizures and its characteristics.Results The characteristics of PIH were:throbbing quality,which was exacerbated by coughing,vomiting,bending,and sudden head movement,accompanied by photophobia,phonophobia,and relieved by sleep.The incidence of PIH was 21 3% for TLE,61 9% for OLE,and 41 4% for FLE.The risk of PIH was significantly higher for OLE than for TLE or FLE,and for patients with generalized tonic clonic seizures.Younger onset age of epilepsy was also a risk factor for PIH.Conclusions PIH possess some characteristics similar to migraine.The occurrence of PIH may be related to the region of epileptic focus and the region of the spread of epileptic discharges.