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Heart rate variability analysis for the prediction of EEG grade in infants with hypoxic ischaemic encephalopathy within the first 12 h of birth

Pavel, Andreea M; Mathieson, Sean R; Livingstone, Vicki; O’Toole, John M; Pressler, Ronit M; de Vries, Linda S; Rennie, Janet M; ... Boylan, Geraldine B; + view all (2023) Heart rate variability analysis for the prediction of EEG grade in infants with hypoxic ischaemic encephalopathy within the first 12 h of birth. Frontiers in Pediatrics , 10 , Article 1016211. 10.3389/fped.2022.1016211. Green open access

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Abstract

Background and aims Heart rate variability (HRV) has previously been assessed as a biomarker for brain injury and prognosis in neonates. The aim of this cohort study was to use HRV to predict the electroencephalography (EEG) grade in neonatal hypoxic-ischaemic encephalopathy (HIE) within the first 12 h. Methods We included 120 infants with HIE recruited as part of two European multi-centre studies, with electrocardiography (ECG) and EEG monitoring performed before 12 h of age. HRV features and EEG background were assessed using the earliest 1 h epoch of ECG-EEG monitoring. HRV was expressed in time, frequency and complexity features. EEG background was graded from 0-normal, 1-mild, 2-moderate, 3-major abnormalities to 4-inactive. Clinical parameters known within 6 h of birth were collected (intrapartum complications, foetal distress, gestational age, mode of delivery, gender, birth weight, Apgar at 1 and 5, assisted ventilation at 10 min). Using logistic regression analysis, prediction models for EEG severity were developed for HRV features and clinical parameters, separately and combined. Multivariable model analysis included 101 infants without missing data. Results Of 120 infants included, 54 (45%) had normal-mild and 66 (55%) had moderate-severe EEG grade. The performance of HRV model was AUROC 0.837 (95% CI: 0.759–0.914) and clinical model was AUROC 0.836 (95% CI: 0.759–0.914). The HRV and clinical model combined had an AUROC of 0.895 (95% CI: 0.832–0.958). Therapeutic hypothermia and anti-seizure medication did not affect the model performance. Conclusions Early HRV and clinical information accurately predicted EEG grade in HIE within the first 12 h of birth. This might be beneficial when EEG monitoring is not available in the early postnatal period and for referral centres who may want some objective information on HIE severity.

Type: Article
Title: Heart rate variability analysis for the prediction of EEG grade in infants with hypoxic ischaemic encephalopathy within the first 12 h of birth
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fped.2022.1016211
Publisher version: https://doi.org/10.3389/fped.2022.1016211
Language: English
Additional information: © 2023 Pavel, Mathieson, Livingstone, O' Toole, Pressler, de Vries, Rennie, Mitra, Dempsey, Murray, Marnane, Boylan and ANSeR Consortium. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: newborn, neonatal encephalopathy, heart rate variability, electroencephalography, electrocardiogram
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health > Neonatology
URI: https://discovery.ucl.ac.uk/id/eprint/10163491
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