Evidence map›Paper›PMID 33225453›Full record

ArticlePrenatal diagnosis2020

Trends in prenatal diagnosis: An analysis of 40 years of Medical Subject Heading (MeSH) terms in publications.

Ya-Ling Lu, Diana W Bianchi

Abstract read
In one paragraph

Article in Prenatal diagnosis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Liquid Biopsy in Adverse Neurodevelopment of Children: Problems and Prospects.Methods in molecular biology (Clifton, N.J.) · 2023
    Review
  3. 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

2 authors.

Ya-Ling LuNIH Library, Office of Research Services, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0002-7190-9903
Diana W BianchiNational Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0001-9270-5267

Funding

Sequence Analysis of Circulating Cell-free DNA During PregnancyZIAHG200400 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI BIANCHI, DIANA · 2018 to 2025
$524k
Intramural NIH HHS HG200400-03Intramural NIH HHS ZIA HG200400
6 · The paper itself

Abstract

objectiveTo understand the evolution of the field of prenatal diagnosis over the past four decades.

methodWe analyzed the publications in the journal Prenatal Diagnosis from its inception in 1980 to 2019 using Medical Subject Headings (MeSH) to examine the major research topics and trends. The results were analyzed by 10-year intervals.

resultsPublications on prenatal cytogenetics, congenital anomalies and fetal imaging predominated during the first three decades, with a steady increase in molecular genetics over time. Publications on NIPT did not appear until the most recent decade and are likely under-counted because there was no MeSH term for NIPT until 2020.

conclusionThe topics covered in Prenatal Diagnosis articles have evolved considerably over the past four decades and reflect a response to advances in technology and widespread incorporation of prenatal screening and diagnosis into standard obstetric care. The strengths of this analysis are its objective nature, its use of the standard MeSH terms used for coding, and application of a novel cluster analysis to visualize trends. The analysis also pointed out the fact that MeSH terms in this sub-specialty area are often inconsistent due to manually coding based on individual subject matter expertise.

Indexed as

BibliometricsMedical Subject HeadingsAbstracting and IndexingFemaleHumansNoninvasive Prenatal TestingPeriodicals as TopicPregnancyPrenatal Diagnosis

Identifiers

PMID33225453
PMCPMC10040213

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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.