Evidence map›Paper›PMID 32819015›Full record

Observational studyAmerican journal of perinatology2022

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

Abigail Flower, Daniel Vasiliu, Tianrui Zhu, Robert Andris, Maryam Abubakar, Karen Fairchild, Santina Zanelli, Julie Matsumoto, Amit M Mathur, John Delos and 1 more

Open access · greenAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in American journal of perinatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 1 country.

Abigail FlowerSchool of Data Science, University of Virginia, Charlottesville, Virginia.
Daniel VasiliuDepartment of Mathematics, College of William & Mary, Williamsburg, Virginia.
Tianrui ZhuDepartment of Mathematics, College of William & Mary, Williamsburg, Virginia.
Robert AndrisDepartment of Pediatrics, University of Virginia, Charlottesville, Virginia.
Maryam AbubakarDepartment of Pediatrics, University of Virginia, Charlottesville, Virginia.
Karen FairchildDepartment of Pediatrics, University of Virginia, Charlottesville, Virginia.
Santina ZanelliDepartment of Pediatrics, University of Virginia, Charlottesville, Virginia.
Julie MatsumotoDepartment of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia.
Amit M MathurDivision of Neonatal-Perinatal Medicine, Saint Louis University, St. Louis, Missouri.
John DelosDepartment of Physics, College of William & Mary, Williamsburg, Virginia.
Zachary VesoulisDepartment of Pediatrics, Washington University St. Louis, St. Louis, Missouri.ORCID 0000-0001-8290-0069
University of Virginia · USWilliam & Mary · USSaint Louis University · USWashington University in St. Louis · US

Funding

Predictive Informatics Monitoring in the Neonatal Intensive Care UnitR01HD072071 · NICHD · UNIVERSITY OF VIRGINIA · PI KAREN D FAIRCHILD, Brynne Archer Sullivan · 2014 to 2026
$7.6M
Integrated physiomarker, biomarker and clinical predictive analytics for early warning of sepsis and necrotizing enterocolitis in very low birth weight infants.K23HD097254 · NICHD · UNIVERSITY OF VIRGINIA · PI SULLIVAN, BRYNNE ARCHER · 2019 to 2023
$897k
Racial Disparities in Preterm Brain Injury Are Driven by Differences in Cerebral AutoregulationK23NS111086 · NINDS · WASHINGTON UNIVERSITY · PI VESOULIS, ZACHARY ANDREW · 2019 to 2022
$736k
NICHD NIH HHS K23 HD097254NICHD NIH HHS R01 HD072071NINDS NIH HHS K23 NS111086
6 · The paper itself

Abstract

objectiveThis 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

designIn 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.

resultsNinety-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.

conclusionTime- 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..

Indexed as

Blood PressureElectroencephalographyApgar ScoreBiomarkersFemaleHumansHypoxia-Ischemia, BrainInfant, NewbornLogistic ModelsMalePrognosisROC CurveBiomarkers

Identifiers

PMID32819015
PMCPMC7895863
OpenAlexW3080256582

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.