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Effects of Glycated Serum Protein, Homocysteine, and Cystatin-C Levels on Pregnancy Outcomes in Patients with Gestational Diabetes Mellitus

Overview
Journal Pak J Med Sci
Specialty General Medicine
Date 2024 Mar 28
PMID 38544999
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Abstract

Objective: To explore the effects of serum glycated serum protein (GSP), homocysteine (Hcy) and cystatin-C (Cys-C) levels on pregnancy outcomes in patients with gestational diabetes mellitus (GDM).

Methods: Retrospective selection of 247 pregnant women who underwent normal prenatal examinations in The Yan'an People's Hospital from January 2020 to May 2022 were included in this retrospective study. Among them, 119 were pregnant women with diabetes (GDM-group) and 128 were pregnant women with normal blood glucose (Normal-group). The levels of serum GSP, HCY, CYS-C, and incidence of adverse pregnancy outcomes were compared between the two groups. The clinical value of levels of serum GSP, Hcy, and Cys-C in predicting adverse pregnancy outcomes were analyzed.

Results: Compared with the Normal-group, the overall incidence of adverse pregnancy outcomes, serum GSP, Hcy, and Cys-C levels in the GDM-group were significantly higher (<0.05). Logistic regression analysis showed that the levels of GSP, Hcy, and Cys-C were independent risk factors for adverse pregnancy outcomes in the GDM-group (<0.05). Receiver operating characteristic (ROC) curve showed that the area under the curve (AUC) for diagnosing adverse pregnancy outcomes in pregnant women with GDM using serum GSP, Hcy, and CysC levels alone were 0.817, 0.843, and 0.775, respectively. The AUC of the three indicators combined was 0.921, indicating that this combination has a good predictive value for diagnosing adverse outcomes in GDM-complicated pregnancies.

Conclusions: GDM is associated with a high risk of adverse pregnancy outcomes. Levels of serum GSP, Hcy, and Cys-C are higher in patients with GDM. The higher the levels of GSP, Hcy, and Cys-C, the greater the risk of adverse pregnancy outcomes. Combining these three indicators can effectively predict maternal pregnancy outcomes.

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