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Gestational diabetes: development of an early risk prediction tool to facilitate opportunities for prevention
Helena J Teede1, Cheryce L Harrison, Wan T Teh
1Jean Hailes Foundation for Women's Health, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria, Australia. Helena.Teede@monash.edu
Background And Aim:
In the setting of advancing maternal age, escalating obesity and increasing Gestational Diabetes Mellitus (GDM) rates, we aimed to develop a novel risk prediction tool to identify high-risk women in early pregnancy, specifically to facilitate targeted antenatal prevention of GDM.
Methods:
In this retrospective, observational study, first-trimester data collected routinely by midwifery staff in 4276 women attending a large tertiary hospital in 2007/2008 was analysed to examine predictive factors for GDM. GDM was diagnosed with a 28-week oral glucose tolerance test. The data set included a derivation group (n=2880, from 2007 deliveries) and a validation group (n = 1396, from 2008). Multivariate analysis generated a scoring system.
Results:
GDM was significantly correlated with a number of factors: past history of GDM, increasing maternal age and body mass index, Asian descent and family history of diabetes. Validation group clinical scores achieved a sensitivity of 61.3% and specificity of 71.4% for differentiating women according to their risk of developing GDM.
Conclusions:
Risk factors for GDM are easily identified at the first-trimester midwifery hospital booking visit. A risk prediction tool, derived from risk factors in early pregnancy, identifies women at high risk of GDM. This represents a novel approach to facilitate targeted early intervention with the potential to prevent development of, or ameliorate, GDM.
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