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العنوان
EEG monitoring for abnormal movements or behaviors during the first week of life /
الناشر
Yosra Hany Mahmoud Hammouda ,
المؤلف
Yosra Hany Mahmoud Hammouda
هيئة الاعداد
باحث / Yosra Hany Mahmoud Hammouda
مشرف / Ann Ali AbdElkader
مشرف / Amira Ahmed Ali Labib
مشرف / May AK Abdellatif
تاريخ النشر
2019
عدد الصفحات
126 P. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
علم الأعصاب السريري
تاريخ الإجازة
1/12/2019
مكان الإجازة
جامعة القاهرة - كلية الطب - Clinical Neurophysiology
الفهرس
Only 14 pages are availabe for public view

from 152

from 152

Abstract

The current gold standard for seizure detection is the visual interpretation of conventional multichannel video-EEG by the human expert. Objective: To assess the role of video electroencephalogram in the diagnosis and management of clinically suspicious seizures occurring during the first 7 days of life, differentiating the epileptic from the non-epileptic motor events. Methods: This study included 60 neonates of both genders. Their gestational ages ranged from 30 to 41 weeks. Poly-graphic video EEG recording was done for each of the neonates for a minimum of 2 hours duration in the Neonatal Intensive Care Unit. Results: Our study included 70% males and 30 % females. The most common causes of seizures encountered were hypoxic ischemic encephalopathy (36.7%) and intracranial hemorrhage (16.7%). Most common seizure type was tonic movements (30%), followed by subtle movements (26.7%). Based upon EEG findings, patients were classified into 2 groups, (1) unclassified group and (2) severe group. Our study showed that 16.7% of our neonates had totally normal EEGs. EEG of both groups were compared in regard to the gestational age and the Apgar score taken at 5 minutes, showing P-value of 0.024 and 0.025, respectively which are significant. Regarding the cranial ultrasound findings in both groups, significant difference of P-value 0.021 was found concerning the hypoxic changes. group (1) was then analyzed based on scoring system created in our study, in attempt to help better classification of these not very well-defined EEGs. This scoring system was correlated with the clinical variables to assess its predictive value