First Trimester Triglyceride-Glucose Index and Lipid Profile as Predictive Factors in the Diagnosis of Late-Onset Preeclampsia: Can We Prevent It?

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Abstract

Objectives: This study aimed to evaluate whether first-trimester metabolic markers—including the triglyceride-glucose (TyG) index and lipid-related ratios (TG/HDL-c, LDL-c/HDL-c, and TyG/BMI)—could predict the development of late-onset preeclampsia, and to assess their associations with birthweight and birth length. Methods: A retrospective cohort study was conducted on 306 pregnant women (153 with late-onset PE and 153 normotensive controls). Demographic and clinical data, including maternal lipid profiles, TyG index, and other biochemical markers, were collected during the first trimester. Statistical analyses, including Mann–Whitney, two-sided t-tests, and receiver operating characteristic curves (ROC), were performed to assess the predictive value of the TyG index and other ratios in predicting late-onset PE. Results: Significant differences between the PE and control groups were observed in delivery method, birthweight, and birthlength (p < 0.05). ROC analysis revealed that the TyG index had an area under the curve (AUC) of 0.79, with a sensitivity of 69.3% and specificity of 75.8%. The TyG index was inversely associated with birthweight (ρ = −0.288) and gestational age at delivery (ρ = −0.218), while positively correlating with systolic blood pressure (ρ = 0.441). Conclusions: The TyG index, along with TG/HDL and LDL-c/HDL ratios, demonstrated predictive value for late-onset PE. These findings suggest that elevated TyG index levels may contribute to adverse pregnancy outcomes such as intrauterine growth restriction and preterm delivery. First-trimester lipid profiles and the TyG index may serve as valuable markers for early prediction of late-onset PE.

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Bulbul, C. B., & Yakistiran, B. (2025). First Trimester Triglyceride-Glucose Index and Lipid Profile as Predictive Factors in the Diagnosis of Late-Onset Preeclampsia: Can We Prevent It? Diagnostics, 15(24). https://doi.org/10.3390/diagnostics15243141

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