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Development, validation and clinical utility of a risk prediction model for adverse pregnancy outcomes in women with gestational diabetes: The PeRSonal GDM model

Shamil D. Cooray, Jacqueline Boyle, Georgia Soldatos, John Allotey, Holly Wang, Borja M. Fernández‐Félix, Javier Zamora, Shakila Thangaratinam, Helena Teede

2022EClinicalMedicine29 citationsDOIOpen Access PDF

Abstract

Background: The ability to calculate the absolute risk of adverse pregnancy outcomes for an individual woman with gestational diabetes mellitus (GDM) would allow preventative and therapeutic interventions to be delivered to women at high-risk, sparing women at low-risk from unnecessary care. We aimed to develop, validate and evaluate the clinical utility of a prediction model for adverse pregnancy outcomes in women with GDM. Methods: A prediction model development and validation study was conducted on data from a observational cohort. Participants included all women with GDM from three metropolitan tertiary teaching hospitals in Melbourne, Australia. The development cohort comprised those who delivered between 1 July 2017 to 30 June 2018 and the validation cohort those who delivered between 1 July 2018 to 31 December 2018. The main outcome was a composite of critically important maternal and perinatal complications (hypertensive disorders of pregnancy, large-for-gestational age neonate, neonatal hypoglycaemia requiring intravenous therapy, shoulder dystocia, perinatal death, neonatal bone fracture and nerve palsy). Model performance was measured in terms of discrimination and calibration and clinical utility evaluated using decision curve analysis. Findings: statistic 0.68; 95% CI 0.64 to 0.72) when temporally validated. Decision curve analysis demonstrated that the model was useful across a range of predicted probability thresholds between 0.15 and 0.85 for adverse pregnancy outcomes compared to the alternatives of managing all women with GDM as if they will or will not have an adverse pregnancy outcome. Interpretation: The PeRSonal GDM model comprising of routinely available clinical data shows compelling performance, is transportable across time, and has clinical utility across a range of predicted probabilities. Further external validation of the model to a more disparate population is now needed to assess the generalisability to different centres, community based care and low resource settings, other healthcare systems and to different GDM diagnostic criteria. Funding: This work is supported by the Mothers and Gestational Diabetes in Australia 2 NHMRC funded project #1170847.

Topics & Concepts

MedicineGestational diabetesPregnancyObstetricsBody mass indexCohortGestational ageCohort studyShoulder dystociaPediatricsGestationInternal medicineGeneticsBiologyGestational Diabetes Research and ManagementPreterm Birth and ChorioamnionitisPregnancy and preeclampsia studies