Selective Screening Strategies for Gestational Diabetes: A Prospective Cohort Observational Study. (22nd October 2017)

• Record Type: Journal Article
• Authors: Adam, Sumaiya; Rheeder, Paul
• Other Names: Foti Daniela Academic Editor.
• Is Part Of: Journal of diabetes research. Volume 2017(2017)
• Publication Date: 2017-10-22
• Subjects: Diabetes -- Periodicals; Diabetes -- Pathophysiology -- Periodicals; Diabetes -- Prevention -- Periodicals; Diabetes -- Etiology -- Periodicals; Diabetes -- Epidemiology -- Periodicals; Diabetes -- Pathogenesis -- Periodicals; 616.462005
• DOI: 10.1155/2017/2849346
• Languages: English
• ISSNs: 2314-6745

Abstract

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 R 2 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.