Jain Siddharth V, Mathur Amit, Srinivasakumar Preethi, Wallendorf Michael, Culver Joseph P, Zempel John M
Division of Pediatric and Developmental Neurology, Department of Neurology, Washington University School of Medicine, St. Louis, Missouri.
Division of Newborn Medicine, Washington University School of Medicine, St. Louis, Missouri.
Pediatr Neurol. 2017 Feb;67:64-70.e2. doi: 10.1016/j.pediatrneurol.2016.10.019. Epub 2016 Nov 11.
The severity of the initial encephalopathy in neonatal hypoxic-ischemic encephalopathy correlates with seizure burden. Early electroencephalograph (EEG) background activity reflects the severity of encephalopathy. Thus, we hypothesized that early EEG background would be predictive of subsequent seizures in neonatal hypoxic-ischemic encephalopathy.
This study included infants undergoing therapeutic hypothermia at St. Louis Children's Hospital between January 2009 and April 2013. Two pediatric epilepsy specialists independently characterized EEG background qualitatively using amplitude-integrated EEG trends. Total EEG power in the 1-20 Hz frequency band was calculated for quantitative EEG background assessment. Seizures were identified on conventional full montage EEG. Statistical analysis was performed using logistic regression.
Seventy-eight of the 93 eligible infants had artifact-free EEG data; 23 of 78 infants (29%) developed seizures, and of these, 11 developed status epilepticus. The best predictors of subsequent seizures during the first hour of EEG recording were a flat tracing pattern on amplitude-integrated EEG (sensitivity 26%, specificity 98%, likelihood ratio 13, positive predictive value 85%) and the total EEG power less than 10 μV (sensitivity 52%, specificity 98%, likelihood ratio 30, positive predictive value 92%).
Early EEG biomarkers predict subsequent seizures in infants with hypoxic-ischemic encephalopathy. Compared with the qualitative amplitude-integrated EEG background, total EEG power improves our ability to identify high-risk infants from the first hour of EEG recording. Infants with a total EEG power of less than 10 μV have a 90% risk of subsequent seizures. Quantitative EEG measures could stratify cohorts while evaluating novel neuroprotective strategies in neonatal hypoxic-ischemic encephalopathy.
新生儿缺氧缺血性脑病初始脑病的严重程度与癫痫发作负担相关。早期脑电图（EEG）背景活动反映了脑病的严重程度。因此，我们推测早期EEG背景可预测新生儿缺氧缺血性脑病随后的癫痫发作。
本研究纳入了2009年1月至2013年4月在圣路易斯儿童医院接受治疗性低温治疗的婴儿。两名儿科癫痫专家使用振幅整合EEG趋势独立对EEG背景进行定性分析。计算1-20Hz频段的总EEG功率以进行定量EEG背景评估。通过传统的全导联EEG识别癫痫发作。使用逻辑回归进行统计分析。
93名符合条件的婴儿中有78名具有无伪迹的EEG数据；78名婴儿中有23名（29%）发生了癫痫发作，其中11名发生了癫痫持续状态。EEG记录的第一个小时内随后癫痫发作的最佳预测指标是振幅整合EEG上的平坦波形模式（敏感性26%，特异性98%，似然比13，阳性预测值85%）和总EEG功率小于10μV（敏感性52%，特异性98%，似然比30，阳性预测值92%）。
早期EEG生物标志物可预测缺氧缺血性脑病婴儿随后的癫痫发作。与定性的振幅整合EEG背景相比，总EEG功率提高了我们从EEG记录的第一个小时就识别高危婴儿的能力。总EEG功率小于10μV的婴儿随后发生癫痫发作的风险为90%。在评估新生儿缺氧缺血性脑病的新型神经保护策略时，定量EEG测量可对队列进行分层。
