Individualized Early Diagnosis and Treatment System of Gestational Diabetes Mellitus (GDM) Based on New Continuous Glucose Monitoring (CGM) Technology

Gestational diabetes mellitus (GDM), as the most common metabolic complication of pregnancy, poses a serious threat to maternal and fetal metabolic health. However, current GDM diagnosis faces several problems such as static, single-point, cumbersome to operate and delayed diagnosis, highlighting an urgent need to establish an individualized system for early prediction, diagnosis, and intervention.

This project aims to develop a mother-child cohort covering pregnancy and the perinatal period to propose early diagnostic criteria for GDM based on continuous glucose monitoring (CGM) technology, as well as developing clinically applicable AI-based tools for analyzing and interpreting CGM data, along with strategies to assist in GDM diagnosis. Furthermore, it will investigate CGM parameters and multi-omics biomarkers suitable for predicting maternal and fetal outcomes, culminating in the creation of an intelligent management platform for GDM. This project is expected to enhance the early identification rate of gestational diabetes, potentially advancing the diagnostic and therapeutic window for the condition, thereby improving both short- and long-term maternal and fetal health outcomes.