Applied Research on Electrical Status Epilepticus during Sleep through Real-time Transcranial Doppler Ultrasound-video-electroencephalogram
- VernacularTitle:TCD-vEEG 同步监测技术在睡眠中癫痫电持续状态中的应用
- Author:
Bing-wei PENG
1
;
Jia-ling LI
1
;
Xiao-jing LI
1
;
Hai-xia ZHU
1
;
Wei LIANG
1
;
Hui-ci LIANG
1
Author Information
1. Department of Neurology, Guangzhou Women and Children's Medical Center, Guangzhou 510120, China
- Publication Type:Journal Article
- Keywords:
electrical status epilepticus during sleep(ESES);
TCD-vEEG monitoring;
neuro-vascular coupling;
ESES pattern;
cognition deficits
- From:
Journal of Sun Yat-sen University(Medical Sciences)
2020;41(3):485-492
- CountryChina
- Language:Chinese
-
Abstract:
【Objective】 To evaluate the cerebral hemodynamic changes due to interictal epileptic discharges(IEDs) and explore the associated neuroelectrophysiological factors and cognition deficits on electrical status epilepticus during sleep(ESES) through real-time transcranial Doppler ultrasound-video-electroencephalogram(TCD-vEEG) . 【Methods】 Eighteen ESES patients from August, 2017 to March, 2019 were recruited to undergo TCD-vEEG. The trend curve of mean cerebral blood flow velocity(MCBFV) was generated and analyzed. The spike wave index(SWI) and various TCD parameters during non-rapid eye movement(NREM) sleep were measured. The patients were divided into three clinical level groups based on seizures, their cognitive functions and the Activity of Daily Living Scale. According to the patterns of EEG during pre-ESES, the patients were also separately grouped to three groups: bilateral synchronous epileptogenic foci(BSEF), bilateral asynchronous epileptogenic foci(BAEF) and multiple epileptogenic foci(MEF). The patients were also separated into near-ESES and asymmetric ESES groups based on EEG patterns during ESES. We then performed Fisher's precise test, an analysis of variance(ANOVA) and Student's t-test, to determine that those parameters significantly varied according to clinical level and/or EEG pattern through SPSS 17.0. 【Results】 SWI was(85.22±10.33) % on average; MCBFV oscillations during deep sleep was(17.98±7.27) % on average(t = 7.579, P < 0.01); the mean of MCBFV(MCBFVm) was(92.81±21.53) cm/s on average(t = 6.464, P < 0.01); all increased significantly more than those of healthy children. SWI(F = 3.996, P < 0.05) revealed a statistically significant difference among three clinical level groups. ESES pattern had no obvious relation with the SWI, but Near-ESES influenced MCBFV oscillations during deep sleep significantly more(t = 2.885, P = 0.011) . 【Conclusions】 There are obvious cerebral hemodynamic changes during NREM in ESES, and IEDs frequency are the important factors of cognitive impairment due to ESES. ESES pattern is closely related to MCBFV oscillations during deep sleep.
