Author:
Lu Ling,Li Chanyu,Deng Jie,Luo Jianbo,Huang Chaolin
Abstract
ObjectiveGestational diabetes mellitus (GDM) has adverse effects on the health of mothers and their offspring. Currently, no known biomarker has been proven to have sufficient validity for the prediction of GDM in the first trimester of pregnancy. The aim of this study was to investigate the potential relationship between serum neutrophil gelatinase-associated lipocalin (NGAL) levels in the first trimester of pregnancy and later GDM risk and to evaluate the performance of serum NGAL as a biomarker for the prediction of GDM.MethodsThe study was conducted by recruiting participants at 8–13 weeks of gestation from The First Affiliated Hospital of Chengdu Medical College between January and June 2021; participants were followed up for oral glucose tolerance test (OGTT) screening at 24–28 gestational weeks. We examined the serum NGAL levels of all subjects in the first trimester who met the inclusion and exclusion criteria. Anthropometric, clinical, and laboratory parameters of the study subjects were obtained during the same study period. A logistic regression model was carried out to investigate the potential relationship between serum NGAL levels in the first trimester of pregnancy and later GDM risk. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to assess the discrimination and calibration of serum NGAL as a biomarker for the prediction of GDM in the first trimester of pregnancy.ResultsSerum NGAL levels in the first trimester of pregnancy were significantly higher in women who later developed GDM than in those who did not develop GDM. Serum NGAL levels in the first trimester of pregnancy were positively associated with an increased risk of GDM after adjustment for potential confounding factors. The risk prediction model for GDM constructed by using serum NGAL levels in the first trimester of pregnancy achieved excellent performance.ConclusionsMaternal serum NGAL in the first trimester of pregnancy is a potential biomarker for the prediction of GDM, which could help guide the clinical practice of antenatal care.
Funder
Chengdu Science and Technology Bureau
Subject
Endocrinology, Diabetes and Metabolism
Cited by
6 articles.
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