Gonzalez-Tamez Karla, Montazeri Saeed, Ågren Johan, Vanhatalo Sampsa, Hellström-Westas Lena
Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.
Departments of Clinical Neurophysiology and Physiology, University of Helsinki, Helsinki, Finland.
Pediatr Res. 2025 Jun 16. doi: 10.1038/s41390-025-04193-9.
Therapeutic hypothermia is an intervention that improves outcomes and alters early outcome-prediction in infants with moderate-severe hypoxic-ischemic encephalopathy (HIE). This study evaluated the early predictive accuracy of a fully automated continuous EEG background trend, Brain State of the Newborn (BSN) in a regional Swedish cohort of infants with presumed HIE.
The BSN trend characterizes 1-min segments of EEG from zero (inactive) to 100 (continuous) and was generated from aEEG/EEG in 85 infants treated with hypothermia. BSN trajectories were compared in relation to clinical grading of encephalopathy and outcome. Receiver operating characteristics were computed for good (no/mild impairment) and poor outcomes (moderate/severe impairment or death).
During the first 48 h, BSN levels differed significantly between moderate and severe HIE (typical median BSN levels >80 and <40, respectively). The predictive accuracy of BSN was high already at 6 h (AUC 0.84) and at 12 h (AUC 0.91), with corresponding positive predictive values (PPV) > 0.92 for good outcome (cutoff BSN > 80) and PPV > 0.95 for poor outcome (cutoff BSN < 40).
BSN gives a continuous and objective measure of EEG background activity, which is highly predictive of good and poor outcomes already from the first 6-12 h in hypothermia-treated infants with moderate-severe HIE.
Brain State of the Newborn (BSN) is a deep learning-based EEG trend displaying electrocortical activity as numerical values. Here we establish that BSN trends over the first 48 h differ between infants with moderate versus severe hypoxic-ischemic encephalopathy (HIE) and is highly predictive of long-term outcome. This is the first study applying BSN trends in a cohort of exclusively hypothermia-treated infants, demonstrating its value for outcome-prediction already from the first 12 h after birth. The BSN provides a continuous bedside evaluation of brain function that complements the visual aEEG/EEG review and can assist bedside assessments in neonatal intensive care units.
治疗性低温是一种可改善中度至重度缺氧缺血性脑病(HIE)婴儿的预后并改变早期预后预测的干预措施。本研究评估了一种全自动连续脑电图背景趋势——新生儿脑状态(BSN)在瑞典一个地区性疑似HIE婴儿队列中的早期预测准确性。
BSN趋势将脑电图的1分钟片段特征化为从0(无活动)到100(连续),并由85例接受低温治疗的婴儿的振幅整合脑电图(aEEG)/脑电图生成。比较了BSN轨迹与脑病临床分级及预后的关系。计算了良好(无/轻度损伤)和不良预后(中度/重度损伤或死亡)的受试者工作特征曲线。
在最初48小时内,中度和重度HIE之间的BSN水平存在显著差异(典型的中位数BSN水平分别>80和<40)。BSN在6小时(曲线下面积[AUC]0.84)和12小时(AUC 0.91)时的预测准确性就很高,良好预后(截断值BSN>80)的相应阳性预测值(PPV)>0.92,不良预后(截断值BSN<40)的PPV>0.9