The Predictive Effects of Atherogenic Indices and Remnant Cholesterol on Gestational Diabetes Mellitus Risk.

PURPOSE: This study aimed to investigate the predictive effects of atherogenic indices and remnant cholesterol on the risk of GDM.

PATIENTS AND

METHODS

This observational study was conducted based on the Hospital's clinical information system. A total of 6619 participants including 2054 GDM patients and 4565 controls were obtained. Serum lipid data, including triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels were collected. Atherogenic indices including TG/HDL-C, TC/HDL-C, and LDL-C/HDL-C, and remnant cholesterol were regarded as independent variables, and GDM was regarded as the dependent variable. Logistic regression analyses, nomogram analysis, decision curve analysis (DCA), and restricted cubic spline (RCS) analysis were applied to explore the impact of atherogenic indices and remnant cholesterol on GDM.

RESULTS

The prevalence of GDM was 31.03% in this study. In comparison to the 1st quartile, the 4th quartile levels of atherogenic indices and remnant cholesterols were significantly associated with increased risks of gestational diabetes mellitus (GDM). The odds ratios (OR) for these associations were as follows: OR = 1.66 (95% CI: 1.41, 1.96) for TG/HDL-C; OR = 1.47 (95% CI: 1.24, 1.73) for TC/HDL-C; OR = 1.47 (95% CI: 1.24, 1.73) for LDL-C/HDL-C; and OR = 1.39 (95% CI: 1.18, 1.64) for remnant cholesterol. The DCA results confirmed the reliable clinical utility of GDM prediction by atherogenic indices and remnant cholesterol. The RCS regression analysis revealed the nonlinear relationships between the atherogenic indices, remnant cholesterol and GDM.

CONCLUSION

This study revealed the potential predictive effects of atherogenic indices and remnant cholesterol on GDM. These findings underscore the potential of routine lipid testing as a cost-effective strategy for the early identification and management of GDM in clinical settings.