Objective To explore the association between levels of peripheral blood systemic immune-inflammatory indicators in early pregnancy and the risk of gestational diabetes mellitus (GDM).

Methods A total of 348 pregnant women in early pregnancy who underwent regular prenatal examinations and established medical records were enrolled as subjects. According to whether they developed GDM, the participants were divided into GDM group (n=76) and non-GDM group (n=272). General characteristics, glycemic parameters and peripheral blood systemic immune-inflammatory indices were compared between two groups. The predictive value of peripheral blood systemic immune-inflammatory indicators for GDM was analyzed using receiver operating characteristic (ROC) curves and binary Logistic regression analysis.

Results Among 348 pregnant women in early pregnancy, 76 were diagnosed with GDM, with an incidence rate of 21.84%. The gestational weight gain, hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), fasting insulin (FINS) and homeostasis model assessment-insulin resistance (HOMA-IR) were significantly higher in the GDM group than those in the non-GDM group (P < 0.05). The monocyte-to-lymphocyte ratio (MLR), systemic im-mune-inflammation index (SII), systemic inflammation response index (SIRI) and C-reactive protein (CRP) levels were significantly elevated in the GDM group compared with the non-GDM group (P < 0.05). Increased levels of MLR, SII, SIRI, aggregate index of systemic inflammation (AISI) and CRP were all independent risk factors for GDM in early pregnancy (P < 0.05). The areas under the curve (AUC) of MLR, SII, SIRI, AISI and CRP levels alone and their combination for detecting the risk of GDM in the first trimester of pregnancy were 0.918, 0.932, 0.700, 0.918, 0.767 and 0.995, respectively. The combined detection of each index had the highest predictive value.

Conclusion The elevated levels of MLR, SII, SIRI, AISI and CRP in peripheral blood during the first trimester of pregnancy are associated with an increased risk of GDM, and the combined detection of the above indicators has higher predictive value for the occurrence of GDM.