Evidence map›Paper›PMID 38013902›Full record

ArticleComputing in cardiology2021

Temporal Evolution of Intrapartum Fetal Heart Rate Features.

Johann Vargas-Calixto, Yvonne Wu, Michael Kuzniewicz, Marie-Coralie Cornet, Heather Forquer, Lawrence Gerstley, Emily Hamilton, Philip Warrick, Robert Kearney

Abstract read
In one paragraph

Article in Computing in cardiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

9 authors.

Johann Vargas-CalixtoMcGill University, Montreal, Canada.
Yvonne WuUniversity of California, San Francisco, USA.
Michael KuzniewiczKaiser Permanente, Northern California, USA.
Marie-Coralie CornetUniversity of California, San Francisco, USA.
Heather ForquerKaiser Permanente, Northern California, USA.
Lawrence GerstleyKaiser Permanente, Northern California, USA.
Emily HamiltonMcGill University, Montreal, Canada.
Philip WarrickMcGill University, Montreal, Canada.
Robert KearneyMcGill University, Montreal, Canada.

Funding

Maternal Antecedents and Electronic Fetal Monitoring in Term Asphyxia (MAESTRA)R01HD099216 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KEARNEY, ROBERT EDWARD, WU, YVONNE W · 2020 to 2025
$2.8M
NICHD NIH HHS R01 HD099216
6 · The paper itself

Abstract

Our research goal is to improve the intrapartum identification of tracings associated with severe acidosis at birth and subsequent hypoxic-ischemic encephalopathy so that timely interventions could avoid such complications without causing excessive unnecessary interventions in births with normal outcomes. The present study examines the evolution of fetal heart rate (FHR) features over the course of labor. We analyzed FHR signals collected in the last 6 hours before delivery in 21,853 births with normal neonatal outcomes and in 163 that developed hypoxic-ischemic encephalopathy (HIE) from 15 hospitals of Kaiser Permanente Northern California. We divided these six hours into 18 nonoverlapping 20-minute epochs. The power spectral density of each epoch was divided into three bands: low frequency (LF, 30-150 mHz), movement frequency (MF, 150-500 mHz), and high frequency (HF, 500-1000 mHz). We also estimated the LF/(MF+HF) ratio, the mean and standard deviation of the FHR signal, the approximate entropy (ApEn), and the deceleration capacity (DC). In our results, ApEn, the standard deviation, and DC showed a promising ability to detect risk of HIE as early as 120 minutes before birth, which gives enough leading time for timely interventions.

Identifiers

PMID38013902
PMCPMC10681033

What OpenQuestion holds

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Registered trials

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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.