Background: Nonepileptic events misdiagnosed as epilepsy lead to a risk of iatrogenic morbidity, which increases health costs. Among the patients affected by nonepileptic events, 11-46% are psychogenic nonepileptic seizures (PNESs).
Objective: To investigate the usefulness of the semiological classification of PNESs among patients diagnosed by means of video electroencephalograms (vEEGs).
Methods: This was a retrospective review of the medical records of patients admitted to the adult vEEG unit between April 2007 and December 2016, who were diagnosed with PNES that was confirmed through vEEG. Analysis on demographic and clinical data and classification of PNESs according to the Magaudda classification were performed.
Results: We identified 143 patients, among whom 31.5% had also epilepsy. According to the Magaudda classification, the events were: hypermotor (58%); subjective symptoms (21.7%); akinetic (14.7%) and focal motor (5.6%). Hypermotor predominated in both genders, followed by subjective symptoms in women (23.9%) and akinetic in men (19.2%). The mean number of antiepileptic drugs (AEDs) prescribed per patient was 2.3. Thirty-two patients (22.4%) required at least one hospitalization for PNESs. 48.3% of the patients had psychiatric comorbidities.
Conclusion: The proposed semiological classification of PNESs is a relevant tool that general neurologists can use to characterize these events in their daily practice. Correct use of this classification, together with vEEG and appropriate clinical suspicion, makes it possible to reach an accurate early diagnosis, thus reducing morbidity and, possibly, the high costs associated with PNESs.
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http://dx.doi.org/10.1590/0004-282X-ANP-2019-0171 | DOI Listing |
Clin Neurol Neurosurg
July 2024
Department of Cognitive Neurology, Institute of Neuroscience, Kolkata, India. Electronic address:
Introduction: Seizure disorders have often been found to be associated with corpus callosum injuries, but in most cases, they remain undiagnosed. Understanding the clinical, electrographic, and neuroradiological alternations can be crucial in delineating this entity.
Objective: This systematic review aims to analyze the effects of corpus callosum injuries on seizure semiology, providing insights into the neuroscientific and clinical implications of such injuries.
Front Psychol
February 2024
São Paulo State University - UNESP. Marília, São Paulo, Brazil.
In this study the spelling errors of the 'Dyslexic Sight Words - DSW' list are analyzed according to the semiological classification. The spelling errors were made by schoolchildren with and without dyslexia. The high number of inaccuracies observed in the writing of the Group with dyslexia (GD) was often related to the complexity of syllabic structures and orthographic irregularity.
View Article and Find Full Text PDFSci Rep
January 2024
Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, 16145, Genoa, Italy.
Seizure
January 2024
Epilepsy-Center Berlin-Brandenburg, Ev. Krankenhaus Königin Elisabeth Herzberge, Herzbergstr. 79, 10365 Berlin, Germany. Electronic address:
Purpose: At onset of generalized seizures, focal electroclinical features are commonly seen, while generalized onset seizures with focal evolution (GOFE) are largely unknown bearing the risk of misclassification.
Methods: In two German epilepsy-centers, patients with GOFE documented by video-EEG monitoring (VEM) between 2017 and 2022 were identified retrospectively. In addition to analysis of ictal electroclinical features, detailed epilepsy and family history, response to antiseizure medication (ASM), and findings from neuroimaging were considered.
Front Neurol
November 2023
Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Introduction: This study evaluated the accuracy of motion signals extracted from video monitoring data to differentiate epileptic motor seizures in patients with drug-resistant epilepsy. 3D near-infrared video was recorded by the Nelli seizure monitoring system (Tampere, Finland).
Methods: 10 patients with 130 seizures were included in the training dataset, and 17 different patients with 98 seizures formed the testing dataset.
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