Selective screening strategies for gestational diabetes : a prospective cohort observational study
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Date
Authors
Adam, Sumaiya
Rheeder, Paul
Journal Title
Journal ISSN
Volume Title
Publisher
Hindawi Publishing
Abstract
AIM. We aimed to develop a prediction model for the diagnosis of gestational diabetes and to evaluate the performance of published
prediction tools on our population. METHODS. We conducted a cohort study on nondiabetic women < 26 weeks gestation at a level 1
clinic in Johannesburg, South Africa. At recruitment, participants completed a questionnaire and random basal glucose and HbA1c
were evaluated. A 75 g 2-hour OGTT was scheduled between 24–28 weeks gestation, as per FIGO guidelines. A score was derived
using multivariate logistic regression. Published scoring systems were tested by deriving ROC curves. RESULTS. In 554 women, RBG,
BMI, and previous baby ≥ 4000 g were significant risk factors included for GDM, which were used to derive a nomogram-based
score. The logistic regression model for prediction of GDM had R2 0.143, Somer’s Dxy rank correlation 0.407, and Harrell’s
c-score 0.703. HbA1c did not improve predictive value of the nomogram at any threshold (e.g,. at probability > 10%, 25.6% of
cases were detected without the HbA1c, and 25.8% of cases would have been detected with the HbA1c). The 9 published scoring
systems performed poorly. CONCLUSION. We propose a nomogram-based score that can be used at first antenatal visit to identify
women at high risk of GDM.
Description
Keywords
Diagnosis, Women, Johannesburg, South Africa, GDM, Hyperglycemia, Glucose, Prevalence, Mellitus, Early pregnancy, African population, Risk factors
Sustainable Development Goals
Citation
Adam, S & Rheeder, P 2017, 'Selective screening strategies for gestational diabetes : a prospective cohort observational study', Journal of Diabetes Research, vol. 2017, no. 284346, pp. 1-9.