Clinical Pathology Abstracts, 3/17

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Tools for early antenatal prediction of gestational diabetes in obese women

All obese pregnant women are categorized as being equally high risk for gestational diabetes, even though the majority of them do not develop the disorder. Women with gestational diabetes mellitus (GDM) require more intensive antenatal care to achieve optimal blood glucose control and to identify other common complications, including fetal macrosomia and large-for-gestational-age (LGA) infants. A prediction tool to help stratify disease risk would allow clinicians to identify women at risk for GDM early in pregnancy so they can receive targeted intervention. The authors conducted a study to develop a simple, robust, and easily accessible GDM prediction tool to facilitate early intervention for obese women with the highest risk. They measured 21 biomarkers of biological relevance to GDM and a targeted metabolome of 158 metabolites in early pregnancy from 1,303 obese women as part of their prediction models. This prospective cohort was from the UPBEAT trial (UK Better Eating and Activity Trial), a multi-center trial of a complex dietary and physical intervention strategy designed to prevent GDM in obese women and LGA in their offspring. Twenty-six percent of women in the UPBEAT trial developed GDM. The authors used statistical modeling to combine clinical variables and biomarkers to develop prediction tools. A stepwise logistic regression model based on the clinical and anthropometric variables of age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, and waist:height and neck:thigh ratios, provided an area under the curve of 0.71 (95 percent confidence interval [CI], 0.68–0.74). This increased to 0.77 (95 percent CI, 0.73–0.80) when the authors added the candidate biomarkers HbA1c, random glucose, fructosamine, triglycerides, adiponectin, and sex hormone binding globulin. Of interest, the addition of targeted nuclear magnetic resonance metabolites did not improve the model’s accuracy. The authors concluded that their model will help identify women at low risk for developing GDM and improve intervention in high-risk women most likely to benefit from treatment.

White SL, Lawlor DA, Briley AL, et al. Early antenatal prediction of gestational diabetes in obese women: development of prediction tools for targeted intervention. PLoS ONE. 2016;11(12):e0167846. doi:10.1371/journal.pone.0167846.

Correspondence: Dharmintra Pasupathy at Dharmintra.Pasupathy@kcl.ac.uk