Multiomics-based Prediction Model for GDM

Overview

A prospective cohort study was conducted to :1. explore the relative biomarkers of related with the occurence and development; 2. develop a multiotimics prediction model for GDM.

Gestational diabetes mellitus (GDM) is one of the most complications during pregnancy and it is associated with many adverse outcomes especially when the pregnant women can't control blood glucose well. With economy develop rapidly, the occurence of GDM is about 15-20%. Recently, the research on GDM has gone into the molecular level, which is beneficial to diagnosis and treatment on GDM. Besides, the cost of hospitalization and treatment for adverse outcomes caused by GDM have caused a certain burden to pregnant women, their families and the whole country. Lifestyle management has the first-line for treatment on GDM, however, the situation of self-management on GDM isn't satisfactory. Therefore, our study aims to explore a model to predict GDM in advance and reduce the adverse outcomes and economy associated with GDM. The study plan to enroll 60 participants with hisk-risk of GDM and 40 normal participants. They are required sign the inform consent after deciding to participate the research. Furthermore, during early pregnancy (8-13 weeks), middle pregnancy (24-27 3 weeks) and late pregnancy (32-36 weeks), 6-8 weeks after delivery, blood, feces, urine, saliva samples were collected, and continuous blood glucose monitoring system were equipped, human component testing was performed. Follow up was performed to collect the first stool sample of the mother after delivery and faecal samples from the first to the fifth time after birth (the first five times within one week after birth, including hospitalization and discharge) .

Conditions

Eligibility

Locations (1)

Outcomes

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