Abstract
BACKGROUND: Early identification of individuals at risk for gestational diabetes mellitus (GDM) is essential for mitigating its adverse effects on both maternal and foetal health. This study aimed to evaluate the predictive value of the cardiometabolic index (CMI), systemic inflammation response index (SIRI), and serum adipsin levels for GDM. METHODS: A total of 1660 pregnant women were enrolled in this study conducted in Suzhou, China. Baseline clinical data, including blood glucose levels, lipid profiles, and blood cell counts, were collected at 12 weeks of gestation. GDM was diagnosed between 24 and 28 weeks of gestation. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the associations and predictive performance of CMI, SIRI, and adipsin for GDM. RESULTS: Compared with non-GDM participants, those with GDM exhibited significantly higher CMI and SIRI values and lower serum adipsin levels at baseline. Increased CMI and SIRI, as well as reduced adipsin levels, were independently associated with a higher risk of GDM in both unadjusted and adjusted models (all P < 0.05). The composite model incorporating all three biomarkers achieved a higher area under the curve (AUC) of 0.918 compared with the individual models for CMI (AUC = 0.825), SIRI (AUC = 0.802), and adipsin (AUC = 0.724). CONCLUSIONS: CMI, SIRI, and serum adipsin are independently associated with GDM risk, and their combination provides a promising multi-biomarker strategy for early GDM prediction. Further studies are needed to validate these findings in diverse populations.