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Am J Perinatol 2022; 39(03): 288-297
DOI: 10.1055/s-0040-1715822
Original Article

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

Abigail Flower
1   School of Data Science, University of Virginia, Charlottesville, Virginia
,
Daniel Vasiliu
2   Department of Mathematics, College of William & Mary, Williamsburg, Virginia
,
Tianrui Zhu
2   Department of Mathematics, College of William & Mary, Williamsburg, Virginia
,
Robert Andris
3   Department of Pediatrics, University of Virginia, Charlottesville, Virginia
,
Maryam Abubakar
3   Department of Pediatrics, University of Virginia, Charlottesville, Virginia
,
Karen Fairchild
3   Department of Pediatrics, University of Virginia, Charlottesville, Virginia
,
Santina Zanelli
3   Department of Pediatrics, University of Virginia, Charlottesville, Virginia
,
Julie Matsumoto
4   Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia
,
Amit M. Mathur
5   Division of Neonatal-Perinatal Medicine, Saint Louis University, St. Louis, Missouri
,
John Delos
6   Department of Physics, College of William & Mary, Williamsburg, Virginia
,
Zachary Vesoulis 
7   Department of Pediatrics, Washington University St. Louis, St. Louis, Missouri
› Institutsangaben
Funding This study received financial support from US Department of Health and Human Services, National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Human Development (grant number: R01 HD072071) and US Department of Health and Human Services, National Institutes of Health, National Institute of Neurological Disorders and Stroke (grant number: K23 NS111086).
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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

  • Early outcome prediction in HIE is suboptimal.

  • Patterns in blood pressure physiology may be predictive of short-term outcomes.

  • Early time- and frequency-domain measures of blood pressure variability predict short-term EEG outcomes in HIE infants better than perinatal factors alone.

Keywords

neonates - neurology - EEG - blood pressure - hypoxic ischemic encephalopathy

Supplementary Material



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Eingereicht: 10. Januar 2020

Angenommen: 17. Juli 2020

Artikel online veröffentlicht:
20. August 2020

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