Aim: To identify the patients who are more likely to experience a seizure during short-term EEG recording.
Methods: We retrospectively reviewed the EEG recordings and medical records of 294 patients, who were admitted to the Pediatric Departments in Assaf Harofeh Medical Center, and referred for a short-term EEG during a 5-years period following a seizure.
Results: Fifteen (5.1%) patients had seizures during short-term EEG. The likelihood of seizure occurrence was increased by history of seizures (odds ratio 11.86, 95% confidence interval 2.54-55.37), abnormal neurological examination (odds ratio 3.33, 95% confidence interval 1.05-10.55), and the presence of interictal epileptiform discharges (odds ratio 10.07, 95% confidence interval 1.26-80.42). Treatment with antiepileptic drugs and mental retardation were significantly more common among patients with seizures.
Conclusions: Children with a higher likelihood of a seizure during short-term EEG can be identified using data mainly obtained by history and neurological examination.
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http://dx.doi.org/10.1016/j.braindev.2014.05.001 | DOI Listing |
J Nerv Ment Dis
December 2024
Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Section of Psychiatry, University of Genoa, Genoa, Italy.
This review aimed at summarizing the literature evidence on clinical, cognitive, and neurobiological correlates of impaired timing abilities in schizophrenia (SCZ). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic literature search was conducted in PubMed, EMBASE, and PsycInfo by looking at correlates between timing abilities and either symptom severity, cognition, and neurobiological data (imaging and electroencephalography) in individuals with SCZ, without restrictions on study design. A total of 45 articles were selected: associations were identified between impaired timing performance and positive, negative, and disorganization symptoms, as well as with executive functioning, working memory, and attention.
View Article and Find Full Text PDFEur J Paediatr Neurol
January 2025
Division of Pediatric Neurology, Department of Pediatrics, Faculty of Medicine, Ege University, İzmir, Turkey. Electronic address:
Aim: To evaluate the efficacy of initial pharmacotherapy for infantile epileptic spasm syndrome (IESS) with electro-clinical outcome characteristics.
Method: A retrospective comparative cohort study with 280 IESS patients was designed; I. vigabatrin monotherapy (n = 129, 46 %); II.
Psychosoc Interv
January 2025
Burapha University Faculty of Humanities and Social Sciences Department of Psychology Thailand Department of Psychology, Faculty of Humanities and Social Sciences, Burapha University, Thailand.
Mild cognitive impairment (MCI) has been recognized as a window of opportunity for therapeutic and preventive measures to slow cognitive decline. The current study investigated the efficacy of the virtual reality (VR) cognitive-based intervention on verbal and visuospatial short-term memory (STM), executive functions (EFs), and wellbeing among older adults with and without MCI. The immersive VR cognitive-based intervention comprised eight 60-minute sessions, held twice a week over a span of 30 days.
View Article and Find Full Text PDFThe Hybrid-Brain Computer Interface (BCI) has shown improved performance, especially in classifying multi-class data. Two non-invasive BCI modules are combined to achieve an improved classification which are Electroencephalogram (EEG) and functional Near Infra-red Spectroscopy (fNIRS). Classifying contralateral and ipsilateral motor movements is found challenging among the other mental activity signals.
View Article and Find Full Text PDFComput Biol Med
January 2025
Department of Computer Science, Jamia Hamdard University, Near Batra Hospital, New Delhi, 110062, India. Electronic address:
Schizophrenia detection involves identifying the schizophrenia by analyzing specific patterns in Electroencephalogram (EEG) signals, which reflect brain activity associated with symptoms, like hallucinations and cognitive impairments. Existing models face challenges due to the complex and variable nature of EEG data, which may struggle to accurately capture critical temporal dependencies and relevant features. Traditional approaches often lack adaptability, limiting their ability to differentiate schizophrenia patterns from other brain activities.
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