Early antenatal prediction of gestational diabetes in obese women: development of prediction tools for targeted intervention

White, S. L. et al. (2016) Early antenatal prediction of gestational diabetes in obese women: development of prediction tools for targeted intervention. PLoS ONE, 11(12), e0167846. (doi: 10.1371/journal.pone.0167846) (PMID:27930697) (PMCID:PMC5145208)

[img]
Preview
Text
135916.pdf - Published Version
Available under License Creative Commons Attribution.

1MB

Abstract

All obese women are categorised as being of equally high risk of gestational diabetes (GDM) whereas the majority do not develop the disorder. Lifestyle and pharmacological interventions in unselected obese pregnant women have been unsuccessful in preventing GDM. Our aim was to develop a prediction tool for early identification of obese women at high risk of GDM to facilitate targeted interventions in those most likely to benefit. Clinical and anthropometric data and non-fasting blood samples were obtained at 15+0–18+6 weeks’ gestation in 1303 obese pregnant women from UPBEAT, a randomised controlled trial of a behavioural intervention. Twenty one candidate biomarkers associated with insulin resistance, and a targeted nuclear magnetic resonance (NMR) metabolome were measured. Prediction models were constructed using stepwise logistic regression. Twenty six percent of women (n = 337) developed GDM (International Association of Diabetes and Pregnancy Study Groups criteria). A model based on clinical and anthropometric variables (age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, waist:height and neck:thigh ratios) provided an area under the curve of 0.71 (95%CI 0.68–0.74). This increased to 0.77 (95%CI 0.73–0.80) with addition of candidate biomarkers (random glucose, haemoglobin A1c (HbA1c), fructosamine, adiponectin, sex hormone binding globulin, triglycerides), but was not improved by addition of NMR metabolites (0.77; 95%CI 0.74–0.81). Clinically translatable models for GDM prediction including readily measurable variables e.g. mid-arm circumference, age, systolic blood pressure, HbA1c and adiponectin are described. Using a ≥35% risk threshold, all models identified a group of high risk obese women of whom approximately 50% (positive predictive value) later developed GDM, with a negative predictive value of 80%. Tools for early pregnancy identification of obese women at risk of GDM are described which could enable targeted interventions for GDM prevention in women who will benefit the most.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Nelson, Professor Scott and Welsh, Professor Paul and Sattar, Professor Naveed
Authors: White, S. L., Lawlor, D. A., Briley, A. L., Godfrey, K. M., Nelson, S. M., Oteng-Ntim, E., Robson, S. C., Sattar, N., Seed, P. T., Vieira, M. C., Welsh, P., Whitworth, M., Poston, L., and Pasupathy, D.
College/School:College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing
Journal Name:PLoS ONE
Publisher:Public Library of Science
ISSN:1932-6203
ISSN (Online):1932-6203
Copyright Holders:Copyright © 2016 White et al.
First Published:First published in PLoS ONE 11(12): e0167846
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
509251Improving pregnancy outcome in obese women (UK Better Eating and Activity Trial - UPBEAT)Naveed SattarNational Institute for Health Research (NIHR)RP-PG-0407-10452RI CARDIOVASCULAR & MEDICAL SCIENCES
629851The UPBEAT RCT mother-child study. Stratifying and treating obese pregnant women to prevent adverse pregnancy, perinatal and longer term outcomesPaul WelshMedical Research Council (MRC)MR/L002477/1RI CARDIOVASCULAR & MEDICAL SCIENCES