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

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 un

SUBMITTER: Zheng T 

PROVIDER: S-EPMC6642502 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature