Cai Meizhi, Jiang Xuan, Xu Xinyi, Zhao Sidi, Sun Yue, Yang Yushuo, Yang Ping, Fang Chen, Huang Yifan
Clinical Nutrition Division, The Second Affiliated Hospital of Soochow University, No.1055 San Xiang Road, Suzhou, 215000, Jiangsu, China.
School of Public Health, Suzhou Medical College of Soochow University, No.199 Ren Ai Road, Suzhou, 215000, Jiangsu, China.
Cardiovasc Diabetol. 2025 May 2;24(1):189. doi: 10.1186/s12933-025-02744-2.
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.
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.
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).
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.
早期识别妊娠期糖尿病(GDM)风险个体对于减轻其对母婴健康的不良影响至关重要。本研究旨在评估心脏代谢指数(CMI)、全身炎症反应指数(SIRI)和血清脂联素水平对GDM的预测价值。
本研究在中国苏州进行,共纳入1660名孕妇。在妊娠12周时收集基线临床数据,包括血糖水平、血脂谱和血细胞计数。在妊娠24至28周期间诊断GDM。进行逻辑回归和受试者工作特征(ROC)曲线分析,以评估CMI、SIRI和脂联素与GDM的关联及预测性能。
与非GDM参与者相比,GDM患者在基线时的CMI和SIRI值显著更高,血清脂联素水平更低。在未调整和调整模型中,CMI和SIRI升高以及脂联素水平降低均与GDM风险较高独立相关(所有P<0.05)。与CMI(AUC=0.825)、SIRI(AUC=0.802)和脂联素(AUC=0.724)的个体模型相比,包含所有三种生物标志物的复合模型的曲线下面积(AUC)更高,为0.918。
CMI、SIRI和血清脂联素与GDM风险独立相关,它们的组合为早期GDM预测提供了一种有前景的多生物标志物策略。需要进一步研究在不同人群中验证这些发现。