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ORIGINAL ARTICLE
Year : 2017  |  Volume : 130  |  Issue : 23  |  Page : 2808-2815

Clinical Manifestations and Amplitude-integrated Encephalogram in Neonates with Early-onset Epileptic Encephalopathy


1 Department of Pediatrics, Peking University First Hospital, Beijing 100034, China
2 Shenzhen Key Laboratory of Affective and Social Cognitive Science, College of Psychology and Sociology, Shenzhen University, Shenzhen, Guangdong 518060, China

Correspondence Address:
Xin-Lin Hou
Department of Pediatrics, Peking University First Hospital, Beijing 100034
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0366-6999.219152

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Background: The patients with early-onset epileptic encephalopathy (EOEE) suffer from neurodevelopmental delay. The aim of this study was to analyze the clinical manifestations and amplitude-integrated encephalogram (aEEG) characteristics of infants with EOEE with onset within the neonatal period, to make early diagnosis to improve the prognosis. Methods: One-hundred and twenty-eight patients with neonatal seizure were enrolled and followed up till 1 year old. Sixty-six neonates evolved into EOEE were as the EOEE group, the other 62 were as the non-EOEE (nEOEE) group. Then we compared the clinical and aEEG characteristics between the two groups to analyze the manifestations in neonates with EOEE. Results: Compared to the nEOEE group, the incidence of daily seizure attacks, more than two types of convulsions, more than two antiepileptic drugs (AEDs) application, severely abnormal aEEG background, absence of cyclicity, and more than two seizures detection were significantly higher in the EOEE group (P < 0.05) (97% vs. 54.8%; 30.3% vs. 14.5%; 97.0% vs. 25.4%; 39.4% vs. 3.2%; 57.6% vs. 9.7%; and 56% vs. 3.2%, respectively). Severely abnormal background pattern (odds ratio [OR] = 0.081, 95% confidence interval [CI]: 0.009–0.729, P = 0.025) and more than two seizures detection by aEEG (OR = 0.158, 95% CI: 0.043–0.576, P = 0.005) were the independent risk factors for the evolvement into EOEE. The upper and lower margins of active sleep (AS) and quiet sleep (QS) were significantly higher in EOEE group than those of the control group (P < 0.05) (34.3 ± 13.6 vs. 21.3 ± 6.4; 9.9 ± 3.7 vs. 6.7 ± 2.2; 41.2 ± 15.1 vs. 30.4 ± 11.4; and 11.9 ± 4.4 vs. 9.4 ± 4.0; unit: μV, respectively). AS upper margin was demonstrated a higher diagnostic specificity and sensitivity for EOEE than another three parameters according to the receiver operating characteristic curves; the area under the curve was 0.827. Conclusions: The clinical characteristics of the neonatal seizure which will evolve into EOEE were more than two AEDs application, high seizure frequency (daily attack), and more than two types of the seizure. Significant high voltage, severely abnormal background, absence of cyclicity, and more than two seizures detected on aEEG were the meaningful indicators to the prediction of EOEE.


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