{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T10:58:24Z","timestamp":1785409104862,"version":"3.56.0"},"reference-count":22,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T00:00:00Z","timestamp":1759104000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Pediatr."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Hypoxic ischemic encephalopathy (HIE) is the most common neurologic emergency in the neonatal population, with a broad spectrum of potential neurodevelopmental outcomes. Additionally, HIE is the most common cause of seizures during the acute neonatal period. Unfortunately, predicting neurodevelopmental outcomes and epilepsy risk is difficult in this population, and seizure burden during the acute period has not consistently been correlated with outcomes in prior studies. We aimed to examine EEG background data to determine whether there is a relationship between background abnormalities, neurodevelopmental outcomes, and epilepsy risk, and whether this information is more informative for predicting outcomes compared to other clinical data points.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Patients were retrospectively recruited from level 3 Neonatal Intensive Care Units (NICU's) in Calgary, Alberta, from 2014 to 2020. All patients who met the criteria for therapeutic hypothermia after being classified as at risk for HIE were included in the study. Clinical information captured included measures from clinical examination, blood work, MRI (day 3\u20135, scored using Barkovich scoring system) and medications. Continuous video EEG (cvEEG) recordings were separated into day 1, 2, and 3, and separate classifications systems were used for background and ictal findings. Neurodevelopmental follow-up was completed at two years of age, and patients were also categorized as having no epilepsy, or either well-controlled or refractory epilepsy. Poisson regression models and relative risk were used to compare background and ictal scores to long term neurodevelopmental outcomes and future epilepsy risk. Three supervised learning algorithms were trained to predict neurodevelopmental outcomes based on clinical factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Two-hundred and six patients were eligible for the study. Among neonates with seizures, only 18% developed epilepsy, while 52% of those with severely abnormal EEG background patterns did. Total ictal burden was not significantly associated with epilepsy at follow up, and no antiseizures medications were significant predictors. In contrast, EEG background score was strongly associated with epilepsy risk (adjusted\n                      <jats:italic>\u00df<\/jats:italic>\n                      \u2009=\u20092.75,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.002), with severely abnormal backgrounds conferring significantly increased risk (37.5% vs. 5.2%, RR\u2009=\u20097.22, 95% CI: 3.09\u201316.88). Similarly, ictal burden did not predict poor neurodevelopmental outcome or death, whereas background score was a strong predictor (adjusted\n                      <jats:italic>\u00df<\/jats:italic>\n                      \u2009=\u20091.74,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&amp;lt;\u20090.001; RR\u2009=\u20092.44, 95% CI: 1.70\u20133.50). Machine learning models identified background features as more predictive than ictal scores, with XGBoost achieving the best classification performance (accuracy 0.724) and random forest yielding the highest AUC (0.751).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In our cohort, EEG background patterns outperformed ictal burden in predicting both neurodevelopmental outcomes and future epilepsy risk. Although background patterns are not directly modifiable, they provide powerful, early markers of brain injury severity, offering clinicians a valuable tool for prognostication and family counseling at a critical juncture in care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fped.2025.1560760","type":"journal-article","created":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T05:26:41Z","timestamp":1759123601000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["The future is in the background: background EEG patterns, not acute seizures, predict epilepsy and neurodevelopmental outcomes in neonatal HIE"],"prefix":"10.3389","volume":"13","author":[{"given":"Kristine E.","family":"Woodward","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pauline","family":"de Jesus","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kimberly","family":"Amador","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pauline","family":"Mouches","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marvin","family":"Braun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khorshid","family":"Mohammad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nils D.","family":"Forkert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael J.","family":"Esser","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,9,29]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/j.earlhumdev.2010.05.010","article-title":"Epidemiology of neonatal encephalopathy and hypoxic-ischaemic encephalopathy","volume":"86","author":"Kurinczuk","year":"2010","journal-title":"Early Hum Dev"},{"key":"B2","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1203\/PDR.0b013e31822f24c7","article-title":"Risk factors for epilepsy in children with neonatal encephalopathy","volume":"70","author":"Glass","year":"2011","journal-title":"Pediatr Res"},{"key":"B3","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1111\/j.1528-1167.2011.03401.x","article-title":"The temporal evolution of electrographic seizure burden in neonatal hypoxic ischemic encephalopathy","volume":"53","author":"Lynch","year":"2012","journal-title":"Epilepsia"},{"key":"B4","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.seizure.2015.10.007","article-title":"The temporal characteristics of seizures in neonatal hypoxic ischemic encephalopathy treated with hypothermia","volume":"33","author":"Lynch","year":"2015","journal-title":"Seizure"},{"key":"B5","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1177\/0883073810380915","article-title":"Clinical seizures in neonatal hypoxic-ischemic encephalopathy have no independent impact on neurodevelopmental outcome: secondary analyses of data from the neonatal research network hypothermia trial","volume":"26","author":"Kwon","year":"2011","journal-title":"J Child Neurol"},{"key":"B6","doi-asserted-by":"publisher","first-page":"1242","DOI":"10.1111\/dmcn.13215","article-title":"Seizure burden and neurodevelopmental outcome in neonates with hypoxic-ischemic encephalopathy","volume":"58","author":"Kharoshankaya","year":"2016","journal-title":"Dev Med Child Neurol"},{"key":"B7","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1016\/j.bj.2020.06.008","article-title":"Seizures severity during rewarming can predict seizure outcomes of infants with neonatal hypoxic-ischemic encephalopathy following therapeutic hypothermia","volume":"43","author":"Chen","year":"2020","journal-title":"Biomed J"},{"key":"B8","doi-asserted-by":"publisher","first-page":"1484","DOI":"10.1001\/jamaneurol.2021.3723","article-title":"Association between increased seizures during rewarming after hypothermia for neonatal hypoxic ischemic encephalopathy and abnormal neurodevelopmental outcomes at 2-year follow-up: a nested multisite cohort study","volume":"78","author":"Chalak","year":"2021","journal-title":"JAMA Neurol"},{"key":"B9","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1111\/dmcn.15302","article-title":"The prognostic value of neonatal conventional-EEG monitoring in hypoxic-ischemic encephalopathy during therapeutic hypothermia","volume":"65","author":"Bourel-Ponchel","year":"2023","journal-title":"Dev Med Child Neurol"},{"key":"B10","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1016\/j.seizure.2018.09.003","article-title":"High electroencephalographic seizure exposure is associated with unfavorable outcomes in neonates with hypoxic-ischemic encephalopathy","volume":"61","author":"Fitzgerald","year":"2018","journal-title":"Seizure"},{"key":"B11","doi-asserted-by":"publisher","first-page":"e459","DOI":"10.1542\/peds.2008-2190","article-title":"Early EEG findings in hypoxic-ischemic encephalopathy predict outcomes at 2 years","volume":"124","author":"Murray","year":"2009","journal-title":"Pediatrics"},{"key":"B12","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1093\/pch\/pxy028","article-title":"Hypothermia for newborns with hypoxic-ischemic encephalopathy","volume":"23","author":"Lemyre","year":"2018","journal-title":"Paediatr Child Health"},{"key":"B13","doi-asserted-by":"publisher","first-page":"696","DOI":"10.1001\/archneur.1976.00500100030012","article-title":"Neonatal encephalopathy following fetal distress. A clinical and electroencephalographic study","volume":"33","author":"Sarnat","year":"1976","journal-title":"Arch Neurol"},{"key":"B14","first-page":"143","article-title":"Prediction of neuromotor outcome in perinatal asphyxia: evaluation of MR scoring systems","volume":"19","author":"Barkovich","year":"1998","journal-title":"AJNR Am J Neuroradiol"},{"key":"B15","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1097\/WNP.0b013e3182872b24","article-title":"American clinical neurophysiology society standardized EEG terminology and categorization for the description of continuous EEG monitoring in neonates: report of the American clinical neurophysiology society critical care monitoring committee","volume":"30","author":"Tsuchida","year":"2013","journal-title":"J Clin Neurophysiol Off Publ Am Electroencephalogr Soc"},{"key":"B16","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1016\/j.bmhimx.2016.07.008","article-title":"Ages and stages questionnaire: a global screening scale","volume":"74","author":"Singh","year":"2017","journal-title":"Bol Med Hosp Infant Mex"},{"key":"B17","doi-asserted-by":"publisher","first-page":"062001","DOI":"10.1088\/1741-2552\/abbff2","article-title":"Supervised machine learning tools: a tutorial for clinicians","volume":"17","author":"Lo Vercio","year":"2020","journal-title":"J Neural Eng"},{"key":"B18","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1139\/gen-2020-0131","article-title":"Machine learning for precision medicine","volume":"64","author":"MacEachern","year":"2021","journal-title":"Genome"},{"key":"B19","doi-asserted-by":"publisher","first-page":"e07411","DOI":"10.1016\/j.heliyon.2021.e07411","article-title":"Predictive modelling of hypoxic ischaemic encephalopathy risk following perinatal asphyxia","volume":"7","author":"Mooney","year":"2021","journal-title":"Heliyon"},{"key":"B20","doi-asserted-by":"publisher","first-page":"e2223","DOI":"10.1212\/WNL.0000000000207744","article-title":"Association of EEG background and neurodevelopmental outcome in neonates with hypoxic-ischemic encephalopathy receiving hypothermia","volume":"101","author":"Glass","year":"2023","journal-title":"Neurology"},{"key":"B21","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1001\/jamaneurol.2021.1437","article-title":"Safety of early discontinuation of antiseizure medication after acute symptomatic neonatal seizures","volume":"78","author":"Glass","year":"2021","journal-title":"JAMA Neurol"},{"key":"B22","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1159\/000511540","article-title":"Effect of phenobarbitone on amplitude-integrated electroencephalography in neonates with hypoxic-ischemic encephalopathy during hypothermia","volume":"117","author":"Deshpande","year":"2020","journal-title":"Neonatology"}],"container-title":["Frontiers in Pediatrics"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fped.2025.1560760\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T10:59:58Z","timestamp":1764327598000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fped.2025.1560760\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,29]]},"references-count":22,"alternative-id":["10.3389\/fped.2025.1560760"],"URL":"https:\/\/doi.org\/10.3389\/fped.2025.1560760","relation":{},"ISSN":["2296-2360"],"issn-type":[{"value":"2296-2360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,29]]},"article-number":"1560760"}}