Researchers from across Monash University and Monash Health are set to develop a mobile app to aid pregnant women with gestational diabetes, and their doctors, estimate their risk of adverse pregnancy outcomes.
Gestational diabetes is increasingly common, affecting up to 18 per cent of pregnancies in Australia. With this condition also comes an inherent risk. It may increase the risk of the birth of a large-for-gestational age baby which may be associated with poor long-term health, as well as preeclampsia that can threaten the lives of both mother and baby.
Thanks to funding from a recent $2.55 million Medical Research Future Fund grant to improve healthy lifestyle in preconception, pregnancy and postpartum, as well as translating targeted lifestyle support strategies into healthcare, undertaking health economics analyses and influencing guidelines and policy to improve lifestyle, health, quality of life and wellbeing of Australian mothers, babies and children, this new app is just one of the risk prediction tools which will identify pregnant women at high risk of adverse lifestyle related outcomes. It aims to calculate the absolute risk of adverse pregnancy outcomes as a percentage for individual women, to empower them and their healthcare professionals to make better decisions around the use of preventative and therapeutic interventions.
Researchers from the Monash Centre for Health Research and Implementation said there is a real opportunity to bring a precision medicine approach to this significant public health problem.
“Locally almost one in five pregnancies is affected by gestational diabetes. However, current diagnostic criteria identify a diverse population and there is a broad continuum of risk of adverse pregnancy outcomes for individual affected women,” said Dr Shamil Cooray, PhD Candidate from the Monash Centre for Health Research and Implementation and Endocrinologist at Monash Health.
“Our systematic review has shown there is an unmet clinical need for a clinical risk calculator for women with gestational diabetes, as published prediction models show none are suitable for clinical application.
“The ability to calculate the absolute risk of adverse pregnancy outcomes for individual women would positively impact affected women and their families by supporting shared and robust decision-making.
“We also hope that eventually this knowledge could be used to deliver treatment personalised to the patient, rather than making the treatment fit the patient as is the case with our current one-size-fits-all approach,” said Dr Cooray.
The app aims to transform the developed prediction model into a clinical tool that can be used to improve clinical care at Monash Health using readily available clinical characteristics such as maternal age, past obstetric history, ethnicity and Body Mass Index.
The development team has so far used data from more than 2,700 affected pregnancies and is made up of Endocrinologists, Obstetricians, Biostatisticians and International Prediction Modelling experts.
Monash Partners Academic Health Science Centre has supported this project as part of the Monash Healthcare Innovation Summer Scholarships. This scheme connects undergraduate and Masters students from across disciplines with clinicians who seek a technological solution to clinical problems. Students and clinicians will work together for 12 weeks to evaluate concepts for new technologies and create proof-of-concept prototypes.