ArticlePediatric research2026
Early outcome-prediction with an automated EEG background trend in hypothermia-treated newborns with encephalopathy.
Article in Pediatric research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A minimally invasive, scalable and reproducible neonatal rat model of severe focal brain injury.Brain communications · 2026Article
- Automated EEG Background Analysis and 2-Year Outcomes in Neonatal Hypoxic-Ischemic Encephalopathy.JAMA network open · 2025Article
- Extending the Branches of Neonatal Neurocritical Care.Seminars in perinatology · 2025Review
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5 authors.
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Abstract
backgroundTherapeutic 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.
methodThe 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).
resultsDuring 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).
conclusionBSN 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. IMPACT: 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.
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