The Prediction modelling for Risk-Stratified care for women with Gestational Diabetes (PeRSonal GDM) study: Calculating the individualised risk of adverse outcomes for women with gestational diabetes.

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Background 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 would allow preventative and therapeutic interventions to be delivered to women at high-risk, sparing women at low-risk from unnecessary care. Research Aims 1. To examine the outcomes of GDM in the context of current care. 2. To develop a prediction model for adverse pregnancy outcomes in women with GDM. Participants All pregnancies within the existing Monash Health maternity outcomes database with a birth recorded from 1 January 2016 to 31 December 2018. All analysis will be conducted using non-identifiable data. Methods Epidemiologic questions will be examined with logistic regression analysis. A multivariable prediction model will be developed using clinical characteristics routinely available at the time of GDM diagnosis. Recent methodologic advances aimed at developing clinical meaningful and implementable models will be utilised. Expected Outcomes Obesity, excess gestational weight gain and ethnicity are significant contributors to adverse pregnancy outcome in women with GDM in this real-world population-based dataset. A method for stratifying women with GDM by risk of adverse pregnancy outcomes will be developed.