Correlation between the first-trimester non-traditional lipid parameters with the risk of gestational diabetes mellitus in pregnancy.

INTRODUCTION

Gestational diabetes mellitus (GDM) is a common complication in pregnancy, linked to adverse outcomes for mothers and infants. Elevated levels of non-traditional lipid parameters have been associated with metabolic disorders. This study explores the predictive value of first-trimester non-traditional lipid parameters for GDM diagnosis at 24-28 weeks.

METHODS

A retrospective study involving 1197 patients from The Third Affiliated Hospital of Wenzhou Medical University (January 2019 - August 2023) examined the correlation between non-traditional lipid parameters and GDM using logistic regression and stratified analyses. The diagnostic performance of the lipid parameters was evaluated using the area under the curve (AUC) method. Pearson correlation analysis clarified the relationship between non-traditional lipid parameters and neonatal birth weight, as well as their association with oral glucose tolerance test (OGTT) glycemic measures.

RESULTS

Among 1197 participants, 201 were diagnosed with GDM. The GDM group exhibited significantly higher levels of non-traditional lipid parameters. Multivariate analysis identified these lipid measures, particularly Non-HDL-C with an AUC of 64.0% (95% CI: 59.6%-68.4%), as independent predictors of GDM across all models (P < 0.05), except for RC/HDL-C in model3. Most non-traditional lipid parameters demonstrated a linear relationship with GDM, with the exception of Non-HDL-C. Strong positive correlations were observed between fasting blood glucose levels and lipid ratios such as Non-HDL-C/HDL-C, LDL/HDL-C, TG/HDL-C, TC/HDL-C, and RC/HDL-C in patients with GDM. No significant differences were found in non-traditional lipid parameters among the single, double, and triple positive groups.

CONCLUSION

First-trimester non-traditional lipid parameters are significant predictors of GDM, particularly when considering fasting blood glucose levels. These parameters offer potential value for early diagnosis.