Lu YT, Chen CP, Sun FJ, Chen YY, Wang LK, Chen CY. Associations between first-trimester screening biomarkers and maternal characteristics with gestational diabetes mellitus in Chinese women.
Front Endocrinol (Lausanne) 2024;
15:1383706. [PMID:
39175575 PMCID:
PMC11339418 DOI:
10.3389/fendo.2024.1383706]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 07/26/2024] [Indexed: 08/24/2024] Open
Abstract
Background
Gestational diabetes mellitus (GDM) can result in adverse maternal and neonatal outcomes. Predicting those at high risk of GDM and early interventions can reduce the development of GDM. The aim of this study was to examine the associations between first-trimester prenatal screening biomarkers and maternal characteristics in relation to GDM in Chinese women.
Methods
We conducted a retrospective cohort study of singleton pregnant women who received first-trimester aneuploidy and preeclampsia screening between January 2019 and May 2021. First-trimester prenatal screening biomarkers, including pregnancy-associated plasma protein A (PAPP-A), free beta-human chorionic gonadotropin, and placental growth factor (PLGF), along with maternal characteristics, were collected for analysis in relation to GDM. Receiver operating characteristic (ROC) curve and logistic regression analyses were used to evaluate variables associated with GDM.
Results
Of the 1452 pregnant women enrolled, 96 developed GDM. PAPP-A (5.01 vs. 5.73 IU/L, P < 0.001) and PLGF (39.88 vs. 41.81 pg/mL, P = 0.044) were significantly lower in the GDM group than in the non-GDM group. The area under the ROC curve of combined maternal characteristics and biomarkers was 0.73 (95% confidence interval [CI] 0.68-0.79, P < 0.001). The formula for predicting GDM was as follows: P = 1/[1 + exp (-8.148 + 0.057 x age + 0.011 x pregestational body mass index + 1.752 x previous GDM history + 0.95 x previous preeclampsia history + 0.756 x family history of diabetes + 0.025 x chronic hypertension + 0.036 x mean arterial pressure - 0.09 x PAPP-A - 0.001 x PLGF)]. Logistic regression analysis revealed that higher pregestational body mass index (adjusted odds ratio [aOR] 1.03, 95% CI 1.01 - 1.06, P = 0.012), previous GDM history (aOR 9.97, 95% CI 3.92 - 25.37, P < 0.001), family history of diabetes (aOR 2.36, 95% CI 1.39 - 4.02, P = 0.001), higher mean arterial pressure (aOR 1.17, 95% CI 1.07 - 1.27, P < 0.001), and lower PAPP-A level (aOR 0.91, 95% CI 0.83 - 1.00, P = 0.040) were independently associated with the development of GDM. The Hosmer-Lemeshow test demonstrated that the model exhibited an excellent discrimination ability (chi-square = 3.089, df = 8, P = 0.929).
Conclusion
Downregulation of first-trimester PAPP-A and PLGF was associated with the development of GDM. Combining first-trimester biomarkers with maternal characteristics could be valuable for predicting the risk of GDM.
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