Evidence map›Paper›PMID 29882903›Full record

ReviewJournal of clinical medicine2018

The Emerging Role of Biomarkers in the Diagnosis of Gestational Diabetes Mellitus.

Natassia Rodrigo, Sarah J Glastras

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 4 pooled it
7.3field-weighted citation impact, top 2% 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

44 citing papers in PubMed, 4 syntheses or guidelines pooled it, 78 citations in OpenAlex.

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  3. Association Of Blood Lipocalin-2 Levels with Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis.Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme · 2022
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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 at 1 institution in 1 country.

Natassia RodrigoDepartment of Diabetes, Endocrinology & Metabolism, Royal North Shore Hospital, St Leonards, Sydney 2065, Australia. natassia.rodrigo@sydney.edu.au.
Sarah J GlastrasDepartment of Diabetes, Endocrinology & Metabolism, Royal North Shore Hospital, St Leonards, Sydney 2065, Australia. sarah.glastras@sydney.edu.au.ORCID 0000-0002-9317-1348
The University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gestational diabetes mellitus (GDM) is a common complication of pregnancy; its rising incidence is a result of increased maternal obesity and older maternal age together with altered diagnostic criteria identifying a greater proportion of pregnant women with GDM. Its consequences are far-reaching, associated with poorer maternal and neonatal outcomes compared to non-GDM pregnancies, and GDM has implications for metabolic health in both mother and offspring. Objective markers to identify women at high risk for the development of GDM are useful to target therapy and potentially prevent its development. Established clinical risk factors for GDM include overweight/obesity, age, ethnicity, and family history of diabetes, though they lack specificity for its development. The addition of biomarkers to predictive models of GDM may improve the ability to identify women at risk of GDM prior to its development. These biomarkers reflect the pathophysiologic mechanisms of GDM involving insulin resistance, chronic inflammation, and altered placental function. In addition, the role of epigenetic changes in GDM pathogenesis highlights the complex interplay between genetic and environmental factors, potentially offering further refinement of the prediction of GDM risk. In this review, we will discuss the clinical challenges associated with the diagnosis of GDM and its current pathophysiologic basis, giving rise to potential biomarkers that may aid in its identification. While not yet validated for clinical use, we explore the possible clinical role of biomarkers in the future. We also explore novel diagnostic tools, including high throughput methodologies, that may have potential future application in the identification of women with GDM.

Indexed as

biomarkersgestational diabetes mellituspathophysiologypredictive diagnosis

Identifiers

PMID29882903
PMCPMC6024961
OpenAlexW2804344435

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.