Evidence map›Paper›PMID 39039325›Full record

ArticlePediatric research2024

Prognostic value of quantitative EEG in early hours of life for neonatal encephalopathy and neurodevelopmental outcomes.

Srinivas Kota, Shu Kang, Yu-Lun Liu, Hanli Liu, Saeed Montazeri, Sampsa Vanhatalo, Lina F Chalak

Abstract read
In one paragraph

Article in Pediatric research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Srinivas KotaDivision of Neonatal-Perinatal Medicine, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Shu KangDepartment of Bioengineering, University of Texas at Arlington, Arlington, TX, USA.
Yu-Lun LiuPeter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Hanli LiuDepartment of Bioengineering, University of Texas at Arlington, Arlington, TX, USA.
Saeed MontazeriDepartment of Physiology, University of Helsinki, Helsinki, Finland.
Sampsa VanhataloDepartment of Physiology, University of Helsinki, Helsinki, Finland.
Lina F ChalakDivision of Neonatal-Perinatal Medicine, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA. Lina.chalak@utsouthwestern.edu.

Funding

A Novel Wavelet Neurovascular Bundle for Real Time Detection of Injury in Neonatal EncephalopathyR01NS102617 · NINDS · UT SOUTHWESTERN MEDICAL CENTER · PI LINA F CHALAK · 2017 to 2026
$4.0M
NINDS NIH HHS R01 NS102617
6 · The paper itself

Abstract

backgroundThe ability to determine severity of encephalopathy is crucial for early neuroprotective therapies and for predicting neurodevelopmental outcome. The objective of this study was to assess a novel brain state of newborn (BSN) trend to distinguish newborns with presence of hypoxic ischemic encephalopathy (HIE) within hours after birth and predict neurodevelopmental outcomes at 2 years of age.

methodThis is a prospective cohort study of newborns at 36 weeks' gestation or later with and without HIE at birth. The Total Sanart Score (TSS) was calculated based on a modified Sarnat exam within 6 h of life. BSN was calculated from electroencephalogram (EEG) measurements initiated after birth. The primary outcome at 2 year of age was a diagnosis of death or disability using the Bayley Scales of Infant Development III.

resultsBSN differentiated between normal and abnormal neurodevelopmental outcomes throughout the entire recording period from 6 h of life. Additionally, infants with lower BSN values had higher odds of neurodevelopmental impairment and HIE. BSN distinguished between normal (n = 86) and HIE (n = 46) and showed a significant correlation with the concomitant TSS.

conclusionBSN is a sensitive real-time marker for monitoring dynamic progression of encephalopathy and predicting neurodevelopmental impairment. IMPACT: This is a prospective cohort study to investigate the ability of brain state of newborn (BSN) trend to predict neurodevelopmental outcome within the first day of life and identify severity of encephalopathy. BSN predicts neurodevelopmental outcomes at 2 years of age and the severity of encephalopathy severity. It also correlates with the Total Sarnat Score from the modified Sarnat exam. BSN could serve as a promising bedside trend aiding in accurate assessment and identification of newborns who may benefit from additional neuroprotection therapies.

Indexed as

ElectroencephalographyHypoxia-Ischemia, BrainBrainChild DevelopmentChild, PreschoolFemaleHumansInfant, NewbornMaleNeurodevelopmental DisordersPrognosisProspective StudiesSeverity of Illness Index

Identifiers

PMID39039325
PMCPMC11499260

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.