First Department of Pediatrics, Semmelweis University, Budapest, Hungary.
First Department of Pediatrics, Semmelweis University, Budapest, Hungary; MTA-SE Pediatric and Nephrology Research Group, Budapest, Hungary.
J Pediatr. 2022 Jul;246:19-25.e5. doi: 10.1016/j.jpeds.2022.04.013. Epub 2022 Apr 14.
To investigate the prognostic accuracy of longitudinal analysis of amplitude-integrated electroencephalography (aEEG) background activity to predict long-term neurodevelopmental outcome in neonates with hypoxic-ischemic encephalopathy (HIE) receiving therapeutic hypothermia.
This single-center observational study included 149 neonates for derivation and 55 neonates for validation with moderate-severe HIE and of gestational age ≥35 weeks at a tertiary neonatal intensive care unit. Single-channel aEEG background pattern, sleep-wake cycling, and seizure activity were monitored over 84 hours during therapeutic hypothermia and rewarming, then scored for each 6-hour interval. Neurodevelopmental outcome was assessed using the Bayley Scales of Infant Development, Second Edition. Favorable outcome was defined as having both a Mental Development Index (MDI) score and Psychomotor Development Index (PDI) score ≥70, and adverse outcome was defined as either an MDI or a PDI <70 or death. Regression modeling for longitudinal analysis of repeatedly measured data was applied, and area under the receiver operating characteristic curve (AUC) was calculated.
Longitudinal aEEG background analysis combined with sleep-wake cycling score had excellent predictive value (AUC, 0.90; 95% CI, 0.85-0.95), better than single aEEG scores at any individual time point. The model performed well in the independent validation cohort (AUC, 0.87; 95% CI, 0.62-1.00). The reclassification rate of this model compared with the conventional analysis of aEEG background at 48 hours was 18% (24 patients); 14% (18 patients) were reclassified correctly. Our results were used to develop a user-friendly online outcome prediction tool.
Longitudinal analysis of aEEG background activity and sleep-wake cycling is a valuable and accurate prognostic tool.
研究接受治疗性低温治疗的缺氧缺血性脑病（HIE）新生儿振幅整合脑电图（aEEG）背景活动的纵向分析对预测长期神经发育结局的预后准确性。
这项单中心观察性研究纳入了 149 例中重度 HIE 且胎龄≥35 周的新生儿，其中 149 例用于推导，55 例用于验证，在三级新生儿重症监护病房接受治疗性低温和复温期间，连续 84 小时监测单通道 aEEG 背景模式、睡眠-觉醒循环和痫性发作活动，然后对每个 6 小时间隔进行评分。使用贝利婴幼儿发育量表第二版评估神经发育结局。良好结局定义为精神发育指数（MDI）和运动发育指数（PDI）评分均≥70，不良结局定义为 MDI 或 PDI<70 或死亡。应用重复测量数据的纵向分析回归模型，并计算接受者操作特征曲线下面积（AUC）。
纵向 aEEG 背景分析结合睡眠-觉醒循环评分具有极好的预测价值（AUC，0.90；95%CI，0.85-0.95），优于任何单一时间点的单次 aEEG 评分。该模型在独立验证队列中表现良好（AUC，0.87；95%CI，0.62-1.00）。与 48 小时时的常规 aEEG 背景分析相比，该模型的重新分类率为 18%（24 例）；14%（18 例）被正确重新分类。我们的结果被用于开发一个易于使用的在线结局预测工具。
aEEG 背景活动和睡眠-觉醒循环的纵向分析是一种有价值且准确的预后工具。
