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Abstract
Introduction Gestational diabetes (GDM) is a common yet highly heterogeneous condition. The ability to calculate the absolute risk of adverse pregnancy outcomes for an individual woman with GDM would allow preventative and therapeutic interventions to be delivered to women at high-risk, sparing women at low-risk from unnecessary care. The Prediction for Risk-Stratified care for women with GDM (PeRSonal GDM) study will develop, validate and evaluate the clinical utility of a prediction model for adverse pregnancy outcomes in women with GDM.
Methods and analysis We undertook formative research to conceptualise and design the prediction model. Informed by these findings, we will conduct a model development and validation study using a retrospective cohort design with participant data collected as part of routine clinical care across three hospitals. The study will include all pregnancies resulting in births from 1 July 2017 to 31 December 2018 coded for a diagnosis of GDM (estimated sample size 2430 pregnancies). We will use a temporal split-sample development and validation strategy. A multivariable logistic regression model will be fitted. The performance of this model will be assessed, and the validated model will also be evaluated using decision curve analysis. Finally, we will explore modes of model presentation suited to clinical use, including electronic risk calculators.
Ethics and dissemination This study was approved by the Human Research Ethics Committee of Monash Health (RES-19–0000713 L). We will disseminate results via presentations at scientific meetings and publication in peer-reviewed journals.
Trial registration details Systematic review proceeding this work was registered on PROSPERO (CRD42019115223) and the study was registered on the Australian and New Zealand Clinical Trials Registry (ACTRN12620000915954); Pre-results.
- diabetes in pregnancy
- obstetrics
- public health
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Footnotes
ST and HJT are joint senior authors.
Twitter @DrShamilCooray, @jacanab, @JavierZa67, @borjamfernandez, @JoAllotey, @thangaratinam, @HelenaTeede
Contributors Conceptualisation: SDC, GS, JB, ST, HJT. Funding acquisition: SDC, JZ, ST, HJT. Investigation: SDC, JB, GS, JZ, BFF, JA, ST, HJT. Project administration: SDC, ST, HJT. Resources: SDC, ST, HJT. Supervision: JB, GS, JZ, ST, HJT. Validation: SDC, JZ, BFF, JA, ST, HJT. Visualisation: SDC, HJT. Writing – original draft: SDC, BFF, JZ, HJT. Writing – review and editing: SDC, JB, GS, JZ, BFF, JA, ST, HJT.
Funding SDC is supported by a National Health and Medical Research Council (NHMRC) Postgraduate Scholarship, a Diabetes Australia Research Program NHMRC Top-up Scholarship, the Australian Academy of Science’s Douglas and Lola Douglas Scholarship and an Australian Government Department of Education and Training Endeavour Research Leadership Award. JB is supported by a Career Development Fellowship funded by the NHMRC. HJT is supported by an NHMRC Fellowship funded by the Medical Research Future Fund. BFF is supported by CIBER (Biomedical Research Network in Epidemiology and Public Health), Madrid, Spain. The funding bodies had no role in the study design, the collection, analysis and interpretation of the data, the writing of the report nor the decision to submit the paper for publication.
Competing interests SDC reports grants from the National Health and Medical Research Council (NHMRC), Diabetes Australia, the Australian Academy of Science and the Australian Government Department of Education and Training during the conduct of the study; JB reports grants from the NHMRC during the conduct of the study; BFF reports grants from CIBER (Biomedical Research Network in Epidemiology and Public Health, Madrid, Spain) during the conduct of the study and HJT reports grants from the NHMRC and the Medical Research Future Fund during the conduct of the study; no other relationships or activities that could appear to have influenced the submitted work.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
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