StUdy of Gestational diabetes And Risk using Electronic Data (SUGARED): a population-based cohort study—study protocol
Introduction The 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 ear...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2024-12-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/14/12/e087248.full |
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| Summary: | Introduction The 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. |
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| ISSN: | 2044-6055 |