Poster Presentation Australasian Diabetes in Pregnancy Society Annual Scientific Meeting 2016

Does a validated GDM Insulin prediction model work in women from different ethnic backgrounds?   (#112)

Robyn A Barnes 1 , Tang Wong 1 2 , Glynis P Ross 1 3 , Bin B Jalaludin 4 5 , Lesley MacDonald-Wicks 6 , Carmel Smart 6 , Clare Collins 6 , Jeff Flack 1 2
  1. Diabetes Centre, Bankstown-Lidcombe Hospital, Bankstown, NSW, Australia
  2. Faculty of Medicine , University of NSW, Sydney, NSW, Australia
  3. Faculty of Medicine, University of Sydney, Sydney, NSW, Australia
  4. Epidemiology, Healthy People and Places Unit, South Western Sydney Local Health District, Sydney, NSW, Australia
  5. School of Public Health and Community Medicine, University of NSW, Sydney, NSW, Australia
  6. Faculty of Health and Medicine, The University of Newcastle, Newcastle, NSW, Australia

Background: Ethnicity is associated with differing abnormal glucose profiles and percentage insulin use in women with Gestational Diabetes Mellitus (GDM). We previously developed a model for predicting therapy type in women with GDM – Medical Nutrition Therapy (MNT) only versus MNT+Insulin (MNT+I) therapy (1).

Aim: To test how our Therapy Prediction Model performed in women with GDM from different ethnic backgrounds. 

Methods: We analysed de-identified prospectively collected data (1993-2014), for women diagnosed with GDM according to 1991 GDM Ad Hoc Working Party, thence 1998 ADIPS criteria. (2,3) in our multi-ethnic high-risk cohort. The model includes seven dichotomous predictors of therapy type: maternal age >30 years, family history of diabetes, pre-pregnancy obesity (BMI ≥30 kg/m2), prior GDM, early diagnosis of GDM (<24 weeks gestation), Oral Glucose Tolerance Test (OGTT) fasting BGL ≥5.3 mmol/L, and HbA1c at GDM diagnosis ≥5.5%. A receiver operator curve (ROC) of sensitivity plotted against 1-specificity was constructed based on number of predictors present (0-7) versus therapy outcome for each of the four main ethnicities in our database – European, Middle Eastern, South-East Asian and South Asian. These were compared to the ROC constructed from the pooled data of all ethnicities.

Results: A total of 3144 of 3317 women had complete data for these four ethnicities. Insulin use was highest in women of Middle Eastern background and lowest amongst South-East Asian women. Compared to Europeans, South East Asian women had significantly lower mean OGTT fasting glucose, whilst South Asian women had significantly higher mean HbA1c and both had higher mean OGTT 2hr glucose (see Table).

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Conclusions: In this cohort, the GDM prediction model was similarly predictive of therapy type in all ethnicities, but least for women of South Asian background. This is despite significant differences in insulin use and glucose dynamics between most ethnicities.

Acknowledgements:

We wish to thank all the Diabetes Educators who have collected data and maintained the database.

 

  1. Barnes R, Wong T, Ross G, Jalaludin B, Wong V, Collins C, MacDonald-Wicks L, Smart C, Flack J (2016) A Novel Validated Model For the Prediction of Insulin Therapy Initiation and Adverse Perinatal Outcomes in Women with Gestational Diabetes Mellitus. Diabetologia In Press.
  2. Martin FIR for the Ad Hoc Working Party (1991). The diagnosis of gestational diabetes. Med J Aust 155:112.
  3. Hoffman L, Nolan, C, Wilson, JD, Oats JJN, Simmons D (1998) Gestational diabetes mellitus management guidelines. The Australasian Diabetes In Pregnancy Society. Med J Aust 169:93-97.