Low Variability of Blood Pressure Predicts Abnormal Electroencephalogram in Infants with Hypoxic Ischemic Encephalopathy

Author:

Flower Abigail1,Vasiliu Daniel2,Zhu Tianrui2,Andris Robert3,Abubakar Maryam3,Fairchild Karen3,Zanelli Santina3,Matsumoto Julie4,Mathur Amit M.5,Delos John6,Vesoulis Zachary7ORCID

Affiliation:

1. School of Data Science, University of Virginia, Charlottesville, Virginia

2. Department of Mathematics, College of William & Mary, Williamsburg, Virginia

3. Department of Pediatrics, University of Virginia, Charlottesville, Virginia

4. Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia

5. Division of Neonatal-Perinatal Medicine, Saint Louis University, St. Louis, Missouri

6. Department of Physics, College of William & Mary, Williamsburg, Virginia

7. Department of Pediatrics, Washington University St. Louis, St. Louis, Missouri

Abstract

Objective This study aimed to evaluate the role of an objective physiologic biomarker, arterial blood pressure variability, for the early identification of adverse short-term electroencephalogram (EEG) outcomes in infants with hypoxic-ischemic encephalopathy (HIE). Study Design In this multicenter observational study, we analyzed blood pressure of infants meeting these criteria: (1) neonatal encephalopathy determined by modified Sarnat exam, (2) continuous mean arterial blood pressure (MABP) data between 18 and 27 hours after birth, and (3) continuous EEG performed for at least 48 hours. Adverse outcome was defined as moderate–severe grade EEG at 48 hours. Standardized signal preprocessing was used; the power spectral density was computed without interpolation. Multivariate binary logistic regression was used to identify which MABP time and frequency domain metrics provided improved predictive power for adverse outcomes compared with standard clinical predictors (5-minute Apgar score and cord pH) using receiver operator characteristic analysis. Results Ninety-one infants met inclusion criteria. The mean gestational age was 38.4 ± 1.8 weeks, the mean birth weight was 3,260 ± 591 g, 52/91 (57%) of infants were males, the mean cord pH was 6.95 ± 0.21, and 10/91 (11%) of infants died. At 48 hours, 58% of infants had normal or mildly abnormal EEG background and 42% had moderate or severe EEG backgrounds. Clinical predictor variables (10-minute Apgar score, Sarnat stage, and cord pH) were modestly predictive of 48 hours EEG outcome with area under curve (AUC) of 0.66 to 0.68. A composite model of clinical and optimal time- and frequency-domain blood pressure variability had a substantially improved AUC of 0.86. Conclusion Time- and frequency-domain blood pressure variability biomarkers offer a substantial improvement in prediction of later adverse EEG outcomes over perinatal clinical variables in a two-center cohort of infants with HIE. Key Points

Funder

US Department of Health and Human Services, National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Human Development

US Department of Health and Human Services, National Institutes of Health, National Institute of Neurological Disorders and Stroke

Publisher

Georg Thieme Verlag KG

Subject

Obstetrics and Gynecology,Pediatrics, Perinatology and Child Health

Reference41 articles.

1. Epidemiology of neonatal encephalopathy and hypoxic-ischaemic encephalopathy;J J Kurinczuk;Early Hum Dev,2010

2. A validated clinical MRI injury scoring system in neonatal hypoxic-ischemic encephalopathy;S B Trivedi;Pediatr Radiol,2017

3. A novel magnetic resonance imaging score predicts neurodevelopmental outcome after perinatal asphyxia and therapeutic hypothermia;L C Weeke;J Pediatr,2018

4. Prediction of neuromotor outcome in perinatal asphyxia: evaluation of MR scoring systems;A J Barkovich;AJNR Am J Neuroradiol,1998

5. Heart rate variability in encephalopathic newborns during and after therapeutic hypothermia;A N Massaro;J Perinatol,2014

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