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Study of electroencephalography in people with generalized epilepsy in a Saudi population

BACKGROUND: Electroencephalography (EEG) remains a vital tool in the diagnostic evaluation of patients with epilepsy (GE), however, there is scarcity of information on the yield and potential clinical variables that are associated with EEG abnormalities in people with GE. OBJECTIVE: The study aimed...

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Detalles Bibliográficos
Autores principales: Owolabi, Lukman Femi, Reda, AbdulRazeq Ahmed, El Sayed, Raafat, Morsy, Dina Fares Mohamed, Enwere, Okezie Oguamanam, Mba, Uchechukwu Agbese, Adamu, Bappa, AlGhamdi, Mushabab
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7599013/
https://www.ncbi.nlm.nih.gov/pubmed/33194127
http://dx.doi.org/10.1080/20009666.2020.1809255
Descripción
Sumario:BACKGROUND: Electroencephalography (EEG) remains a vital tool in the diagnostic evaluation of patients with epilepsy (GE), however, there is scarcity of information on the yield and potential clinical variables that are associated with EEG abnormalities in people with GE. OBJECTIVE: The study aimed to evaluate the yield and pattern of EEG abnormalities in patients with GE with the view to determining factors that are independently associated with abnormal EEG in them. METHODS: We characterized EEG features and evaluated associated factors in a sample of people with GE in a Saudi population. Standard definition of interictal epileptiform discharges was used. RESULTS: A total of 1105 (77%) out of 1436 GE patients had EEG. Five hundred and ninety-five (53.85%) patients had abnormal EEG. Factors associated with EEG abnormalities before adjustment for confounders were age, gender, duration of epilepsy, and seizure frequency. However, only frequency of seizure (P = 0.0018), gender (P < 0.0001), and age (P < 0.0001) were independently associated with EEG abnormalities. CONCLUSION: The study showed a modest yield (54%) of abnormal EEG in the cohort of patients with GE. Frequency of seizure, age, and gender, independently predicted the presence of EEG abnormality in people living with GE.