Evidence map›Paper›PMID 39411687›Full record

ArticleF1000Research2023

Gestational diabetes mellitus in relation to serum per- and polyfluoroalkyl substances: A scoping review to evaluate the need for a new systematic review.

Ghazaleh Aali, Anna K Porter, Sebastian Hoffmann, Matthew P Longnecker, Farhad Shokraneh

Abstract readScoping Review
In one paragraph

Article in F1000Research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Ghazaleh AaliDepartment of Evidence Synthesis, Systematic Review Consultants LTD, Oxford, UK.
Anna K PorterRamboll U.S. Consulting, Inc., Raleigh, NC, USA.ORCID 0000-0002-4353-5422
Sebastian Hoffmannseh consulting + services, Paderborn, Germany.
Matthew P LongneckerRamboll U.S. Consulting, Inc., Raleigh, NC, USA.
Farhad ShokranehDepartment of Evidence Synthesis, Systematic Review Consultants LTD, Oxford, UK.ORCID 0000-0001-9687-8560

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Per- and polyfluoroalkyl substances (PFAS) were used or are being used in the manufacturing of products, including consumer-use products. The resulting environmental contamination has led to widespread human exposure. This review aimed to scope the characteristics of evidence covered and applied methodology of evidence to understand -- regardless of any results on the association of gestational diabetes mellitus (GDM) and PFAS -- if a new systematic review would be justified. Methods: We systematically identified reports investigating associations of PFAS with GDM following a pre-specified and pre-registered PECO framework and protocol. Results: The previous systematic reviews included 8-11 reports and either conducted meta-analyses stratified by comparator, analyzed results based on only high and low exposure categories, or pooled results across comparators. Included 20 reports presented data on 24 PFAS with PFOA, PFOS, PFHxS, PFNA, and PFDA being examined in almost all. The comparators employed were heterogeneous across the reports. Conclusions: Because data from at least one new report on GDM is available since the previous systematic reviews and heterogeneous comparators, an updated systematic review using SWiM could add value to the literature.

Indexed as

Diabetes, GestationalFluorocarbonsEnvironmental PollutantsFemaleHumansPregnancySystematic Reviews as TopicEnvironmental PollutantsFluorocarbonsEnvironmental EpidemiologyExposureGestational Diabetes MellitusGlucosePerfluoroalkylPolyfluoroalkyl

Identifiers

PMID39411687
PMCPMC11474155

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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.