1
Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
2
Diabetes Unit, Monash Health, Clayton, Victoria, Australia
1
Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
3
Monash Women's Program, Monash Health, Clayton, Victoria, Australia
,
Georgia Soldatos
1
Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
4
Diabetes and Endocrinology Units, Monash Health, Clayton, Victoria, Australia
1
Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
4
Diabetes and Endocrinology Units, Monash Health, Clayton, Victoria, Australia
› Author AffiliationsFunding S.D.C. 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. J.A.B. is supported by a Career Development Fellowship funded by the NHMRC. H.J.T. is supported by an NHMRC Fellowship funded by the Medical Research Future Fund. The funding bodies had no role in the study design; the collection, analysis, and interpretation of the data; the writing of the report; or the decision to submit the paper for publication.
Gestational diabetes mellitus (GDM) is common and is associated with an increased risk of adverse pregnancy outcomes. However, the prevailing one-size-fits-all approach that treats all women with GDM as having equivalent risk needs revision, given the clinical heterogeneity of GDM, the limitations of a population-based approach to risk, and the need to move beyond a glucocentric focus to address other intersecting risk factors. To address these challenges, we propose using a clinical prediction model for adverse pregnancy outcomes to guide risk-stratified approaches to treatment tailored to the individual needs of women with GDM. This will allow preventative and therapeutic interventions to be delivered to those who will maximally benefit, sparing expense, and harm for those at a lower risk.
Keywords
gestational diabetes -
prediction model -
adverse pregnancy outcomes -
large-for-gestational age
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