Evidence map›Paper›PMID 39725433›Full record

ArticleBMJ open2024

StUdy of Gestational diabetes And Risk using Electronic Data (SUGARED): a population-based cohort study-study protocol.

Deborah Randall, Ibinabo Ibiebele, Tanya Nippita, Siranda Torvaldsen, Jonathan M Morris, Felicity Gallimore, Tessa L Weir, Sarah Glastras

Abstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Bariatric Surgery, Gestational Diabetes and Perinatal Outcomes: A Population-Based Study.BJOG : an international journal of obstetrics and gynaecology · 2026
    Article
  2. Article
  3. 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

8 authors.

Deborah RandallReproduction and Perinatal Centre - Northern Precinct, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Ibinabo IbiebeleReproduction and Perinatal Centre - Northern Precinct, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0001-6024-2958
Tanya NippitaReproduction and Perinatal Centre - Northern Precinct, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Siranda TorvaldsenReproduction and Perinatal Centre - Northern Precinct, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia Siranda.torvaldsen@sydney.edu.au.ORCID http://orcid.org/0000-0003-0795-669X
Jonathan M MorrisReproduction and Perinatal Centre - Northern Precinct, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Felicity GallimoreReproduction and Perinatal Centre - Northern Precinct, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Tessa L WeirKolling Institute, Northern Sydney Local Health District, St Leonards, New South Wales, Australia.
Sarah GlastrasKolling Institute, Northern Sydney Local Health District, St Leonards, New South Wales, Australia.ORCID http://orcid.org/0000-0002-9317-1348

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe incidence of gestational diabetes mellitus (GDM) in Australia has tripled in the last 20 years. Consequently, over 40 000 pregnancies are now diagnosed as 'higher risk' each year. This has increased antenatal surveillance and obstetric intervention, often in the form of delivery earlier than 39 weeks gestation. The StUdy of Gestational diabetes And Risk using Electronic Data (SUGARED) project aims to use large population-based and routinely collected linked health data to (1) personalise risk prediction of adverse pregnancy outcomes for women undergoing glucose tolerance testing, (2) guide optimal birth timing for women with diet-controlled GDM and (3) examine variation in GDM management and pregnancy outcomes in New South Wales (NSW), Australia. METHODS AND ANALYSIS: This retrospective cohort study using linked, routinely collected health data includes all women who gave birth from January 2016 to December 2020 in NSW. The cohort will include approximately 475 000 pregnancies, with >70 000 diagnosed with GDM. The study will link birth data to hospital data and birth/death registry data. In addition, clinical pathology results and detailed clinical information from a subset of public hospital pregnancies in 13 of 15 area health services will be linked. To address the three main aims, we will use statistical methods including logistic regression and K-fold cross-validation for risk prediction, a propensity-score matching 'target trial' method to examine birth timing, and multilevel modelling to examine hospital variation. ETHICS AND DISSEMINATION: Ethics approval for the study has been granted by the NSW Population and Health Services Research Ethics Committee. We will communicate evidence generated from SUGARED to the local health districts and their clinicians, as well as potentially optimising dissemination using existing digital infrastructure.

Indexed as

Diabetes, GestationalPredictive Learning ModelsPregnancy OutcomeRisk AssessmentDelivery, ObstetricFemaleGlucose Tolerance TestHospitals, PublicHumansIncidenceInformation Storage and RetrievalLogistic ModelsMultilevel AnalysisNew South WalesObservational Studies as TopicPregnancyDiabetes in pregnancyEPIDEMIOLOGYOBSTETRICSPregnant WomenSTATISTICS & RESEARCH METHODS

Identifiers

PMID39725433
PMCPMC11683978

What OpenQuestion holds

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LicenceCC BY
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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.