A simple model to predict risk of gestational diabetes mellitus from 8 to 20 weeks of gestation in Chinese women

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Title: A simple model to predict risk of gestational diabetes mellitus from 8 to 20 weeks of gestation in Chinese women
Authors: Zheng, Tao
Ye, Weiping
Wang, Xipeng
Li, Xiaoyong
Zhang, Jun
Little, Julian
Zhou, Lixia
Zhang, Lin
Date: 2019-07-19
Abstract: Abstract Background Gestational diabetes mellitus (GDM) is associated with adverse perinatal outcomes. Screening for GDM and applying adequate interventions may reduce the risk of adverse outcomes. However, the diagnosis of GDM depends largely on tests performed in late second trimester. The aim of the present study was to bulid a simple model to predict GDM in early pregnancy in Chinese women using biochemical markers and machine learning algorithm. Methods Data on a total of 4771 pregnant women in early gestation were used to fit the GDM risk-prediction model. Predictive maternal factors were selected through Bayesian adaptive sampling. Selected maternal factors were incorporated into a multivariate Bayesian logistic regression using Markov Chain Monte Carlo simulation. The area under receiver operating characteristic curve (AUC) was used to assess discrimination. Results The prevalence of GDM was 12.8%. From 8th to 20th week of gestation fasting plasma glucose (FPG) levels decreased slightly and triglyceride (TG) levels increased slightly. These levels were correlated with those of other lipid metabolites. The risk of GDM could be predicted with maternal age, prepregnancy body mass index (BMI), FPG and TG with a predictive accuracy of 0.64 and an AUC of 0.766 (95% CI 0.731, 0.801). Conclusions This GDM prediction model is simple and potentially applicable in Chinese women. Further validation is necessary.
URL: https://doi.org/10.1186/s12884-019-2374-8
http://hdl.handle.net/10393/39452
CollectionLibre accès - Publications // Open Access - Publications
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