No abstract available.
Diagnosis* ; Seizures*

In 2005, the ILAE conceptually defined epilepsy as a disorder of the brain, characterized by an enduring predisposition to generate epileptic seizures and by its psychosocial consequences. In clinical practice, this definition of epilepsy is usually taken to mean at least two unprovoked seizures more than 24 h apart. The operational definition for special circumstances that do not meet the criteria of two unprovoked attacks has been recommended. In 2014, the ILAE refined the practical definition of epilepsy. With this definition, epilepsy is a disease of the brain with either: (1) at least two unprovoked (or reflex) seizures occurring more than 24 h apart; (2) one unprovoked (or reflex) seizure and a probability of further seizures similar to the general recurrence risk (at least 60%) after two unprovoked seizures, occurring over the next 10 years; (3) diagnosis of an epilepsy syndrome. Epilepsy is considered to be resolved for individuals past the applicable age of an age-dependent epilepsy syndrome or those who have remained seizure-free for the past 10 years, without seizure medicines for the past 5 years.
Brain ; Diagnosis ; Epilepsy* ; Recurrence ; Seizures

OBJECTIVE: To propose a semi-supervised epileptic seizure prediction model (ST-WGAN-GP-Bi-LSTM) to enhance the prediction performance by improving time-frequency analysis of electroencephalogram (EEG) signals, enhancing the stability of the unsupervised feature learning model and improving the design of back-end classifier. METHODS: Stockwell transform (ST) of the epileptic EEG signals was performed to locate the time-frequency information by adaptive adjustment of the resolution and retaining the absolute phase to obtain the time-frequency inputs. When there was no overlap between the generated data distribution and the real EEG data distribution, to avoid failure of feature learning due to a constant JS divergence, Wasserstein GAN was used as a feature learning model, and the cost function based on EM distance and gradient penalty strategy was adopted to constrain the unsupervised training process to allow the generation of a high-order feature extractor. A temporal prediction model was finally constructed based on a bi-directional long short term memory network (Bi-LSTM), and the classification performance was improved by obtaining the temporal correlation between high-order time-frequency features. The CHB-MIT scalp EEG dataset was used to validate the proposed patient-specific seizure prediction method. RESULTS: The AUC, sensitivity, and specificity of the proposed method reached 90.40%, 83.62%, and 86.69%, respectively. Compared with the existing semi-supervised methods, the propose method improved the original performance by 17.77%, 15.41%, and 53.66%. The performance of this method was comparable to that of a supervised prediction model based on CNN. CONCLUSION The utilization of ST, WGAN-GP, and Bi-LSTM effectively improves the prediction performance of the semi-supervised deep learning model, which can be used for optimization of unsupervised feature extraction in epileptic seizure prediction.
Humans ; Memory, Short-Term ; Seizures/diagnosis* ; Electroencephalography

Febrile seizures are the most common convulsive disorder and one of the most common nervous system diseases in childhood. Generally, the prognosis is good. Recent studies have revealed a greater understanding about many issues related to the diagnosis and treatment of febrile seizures, including the definition of febrile seizures, clinical diagnosis and evaluation, drug treatment, and prevention. Clinicians should note the association between febrile seizures and epilepsy syndromes. Excessive examination and treatment for patients should be avoided. Effective communication with the parents of patients and health education are also the key points of diagnosis and treatment.
Humans ; Recurrence ; Seizures, Febrile ; diagnosis ; therapy

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.
Brain ; physiopathology ; Electroencephalography ; Epilepsy ; Humans ; Seizures ; diagnosis

No abstract available.
Diagnosis ; Seizures ; Tomography, Emission-Computed, Single-Photon

OBJECTIVETo study the clinical features of non-epileptic seizures associated with cerebral palsy (CP) in children.

METHODSA total of 1 198 children with CP (age: 9 months to 6 years) were enrolled. The children with paroxysmal events were monitored by 24 hrs video-EEG (VEEG) to make sure the seizures were epileptic or non-epileptic. The symptoms, age, CP types and EEG features were observed in children with non-epileptic CP.

RESULTSFive hundred and seventy-eight children (48.24%) presented paroxysmal events. The seizures were epileptic in 231 children (19.28%) and non-epileptic in 322 cases (26.88%). In the 322 cases of non-epileptic CP, the paroxysmal events were of various kinds, including non-epileptic seizure tonic, seizure shake head, shrug shoulder or head hypsokinesis, cry or scream, panic attacks, sleep myoclonic and stereotyped movement. One hundred and fifty-eight (49.1%) out of the 322 children demonstrated nonspecific EEG abnormalities. One hundred and eleven children (34.5%) were misdiagnosed as epilepsy in primary hospitals. The CP children less than one year old showed higher frequency of non-epileptic seizures than the age groups over 1 year and 3 to 6 years. The frequency of non-epileptic seizures was the highest in children with spastic CP (168 cases, 52.2%), followed by dyskinetic CP (69 cases, 21.4%) and mixed type CP (65 cases, 20.2%).

CONCLUSIONSThe paroxysmal events in children with CP partially are non-epileptic seizures and it is important to differentiate non-epileptic from epileptic seizures. The frequencies of non-epileptic seizures may be associated with a child's age and CP type.

PURPOSE: This study was launched to classify subjects of the CSF examination and improve early diagnosis of meningitis and its treatment in children who have had a first febrile seizure. METHODS: From March 1995 to September 2003, children aged 3 months to 5 years who had had treatment for febrile seizure were analyzed as to their age at first seizure, type of seizure, CSF examination, and prevalence of meningitis. RESULTS:The largest age group distribution among the 780 children was 356(45.6%) children who were under 18 months. One hundred ninteen(15.3%) patients received the CSF examination, and out of those 68(19.1%) were less than 18 months old. Twenty five(3.2%) children were diagnosed with meningitis; those less than 18 months old were 15(4.2%). Two(0.2%) were diagnosed as bacterial meningitis. Out of 780 patients 599(76.8%) were simple febrile seizure patients. Out of 32(5.3%) who received the CSF examination, nine were diagnosed as meningitis. In complex febrile seizure, 86(52.1 %) out of 165(21.2%) received CSF examinations and 16(9.7%) of those were diagnosed as meningitis. Thus, there was a higher prevalence of meningitis in children presenting complex febrile seizure. CONCLUSION: To diagnose meningitis with the CSF examination in the first febrile seizure, the patient's general condition, such as clinical symptoms and types of seizure, are more important than the ages of the patients. We suggest that experienced physicians should be concerned with doing an early diagnosis of meningitis and thus reduce the number of CSF examinations of children with febrile seizures.
Cerebrospinal Fluid ; Child ; Early Diagnosis ; Humans ; Infant ; Meningitis ; Meningitis, Bacterial ; Prevalence ; Seizures ; Seizures, Febrile*

Evaluation of seizure disorders revealed the important role of CT in establishing an etiologic diagnosis. The authors analized 207 patients who were checked at Seoul National University Hospital from October, 1977 to August, 1980. Over half of the cases were of normal findings(58%). The most frequent lesion was atrophic changes of the brain(16.4%). Other abnormalities were parasitic lesions, vascular anomalies, brain tumors, infarctions, porencephalic cysts, etc. There were higher rates of positive findings in focal seizures, and in patients with a short history of seizure disorders, and in patients of older age over 40.
Brain Neoplasms ; Diagnosis ; Epilepsy* ; Humans ; Infarction ; Seizures* ; Seoul

Two cases of Sturge-Weber disease in a 10 years old female and a 7 years old male were prese-nted. The diagnosis was established by charactristic features of Sturge-Weber disease including facial port-wine nevus, convulsion, typical ???ailread track pattern intracranial calcifications, some degree of mental retardation and hemiplegia. A brief review of related literature was made.
Child ; Diagnosis ; Female ; Hemiplegia ; Humans ; Intellectual Disability ; Male ; Nevus ; Seizures