Association of metabolic score for insulin resistance and preeclampsia: a multicenter cohort study

Background: The metabolic score for insulin resistance (METS-IR) is a novel indicator used to assess insulin resistance. Previous studies have shown that it is associated with an increased risk of hypertension. However, its relationship with preeclampsia (PE) remains unclear. This study aims to investigate the association between METS-IR and PE. Methods: A total of 39,693 singleton pregnant women from three hospitals in China between January 2018 and June 2024 were included in the study. Data were collected through the hospital information system, and METS-IR was calculated using the following formula: ln([HDL-C (mg/dL)] × [2 × fasting glucose (mg/dL)] + TG (mg/dL) × BMI (kg/m²)). ROC curve analysis was used to evaluate the predictive performance of METS-IR and identify an optimal threshold . Participants were grouped based on METS-IR quartiles and this threshold value. Smooth curve fitting, multivariable logistic regression models, and subgroup analyses were conducted to evaluate the association between METS-IR and PE. Results: The results showed a nonlinear dose-response relationship between METS-IR and PE. The area under the ROC curve (AUC) was 0.649, with an optimal cutoff value of 38.644. After adjusting for potential confounders, higher METS-IR levels were significantly associated with increased risk of PE. Compared with the lowest quartile (Q1), the odds ratios (ORs) for PE in the Q2, Q3, and Q4 groups were 1.19 (95% CI: 1.00-1.42), 1.75 (95% CI: 1.48-2.05), and 2.44 (95% CI: 2.09-2.84), respectively. When stratified by the threshold, METS-IR ≥ 38.6 was significantly associated with both PE (OR= 1.90, 95% CI: 1.72-2.11) and preterm birth (OR= 1.14, 95% CI: 1.0-1.27) compared to METS-IR < 38.6. Subgroup analyses indicated that the association remained consistent across different age, test week, and parity. Conclusion: METS-IR is significantly and positively associated with the risk of PE and demonstrates moderate predictive ability. It may serve as a useful tool for early identification of pregnant women at high risk for PE in clinical practice.