Association of late-pregnancy triglyceride-glucose index and growth differentiation factor 15 with adverse pregnancy outcomes in women with gestational diabetes mellitus

妊娠晚期甘油三酯-葡萄糖指数和生长分化因子15与妊娠期糖尿病妇女不良妊娠结局的相关性

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Abstract

BACKGROUND: Gestational diabetes mellitus (GDM) is a common metabolic disorder during pregnancy and is closely associated with adverse pregnancy outcomes (APO), such as preeclampsia, preterm birth, and macrosomia. The triglyceride-glucose (TyG) index and growth differentiation factor 15 (GDF-15) have emerged as novel biomarkers in cardiovascular and metabolic diseases. However, their potential relevance to APO in late pregnancy among women with GDM remains unclear. METHODS: A total of 275 pregnant women diagnosed with GDM between January 2024 and March 2025 were enrolled in this study. Participants were categorized into two groups based on the presence or absence of APO: GDM patients with APO and GDM patients without APO. Serum levels of GDF-15 were measured using enzyme-linked immunosorbent assay (ELISA), and the TyG index was calculated using fasting triglyceride and glucose levels. RESULTS: Compared with the GDM without APO group, patients in the GDM with APO group exhibited significantly higher serum levels of GDF-15 and TyG index (both p < 0.05). Multivariate logistic regression analysis revealed that both the TyG index (OR = 1.672, 95%CI:1.074–2.602, p < 0.05) and GDF-15 (OR = 1.002, 95%CI:1.001–1.003, p < 0.05) were independent predictors of APO. After adjusting for all potential confounders, restricted cubic spline analysis indicated a positive association between both biomarkers and the risk of APO. Furthermore, receiver operating characteristic (ROC) analysis demonstrated that the combined model incorporating TyG and GDF-15 yielded an AUC of 0.722 (95%CI:0.661–0.784), suggesting good predictive performance. CONCLUSION: Elevated TyG index and GDF-15 levels in late pregnancy are potential predictive biomarkers for APO in women with GDM. Combined assessment of these markers may enhance clinical risk stratification and inform targeted management strategies.

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