Association between triglyceride-glucose index in early pregnancy and risk of preeclampsia: a multicenter retrospective cohort study

Abstract

Background

Previous evidence has indicated that insulin resistance may be an early pathological state of preeclampsia (PE). As a novel biomarker, the triglyceride glucose (TyG) index can reflect the level of insulin resistance in the body. The present study aimed to investigate the association between the TyG index and risk of PE.

Methods

This study included 41,694 singleton pregnant women, comprising 2,308 PE patients and 39,386 healthy controls from three tertiary hospitals from January 2019 to June 2024. Datas were retrospectively collected via medical record review. The TyG index was measured before 20 weeks of gestation, and participants were grouped via the TyG index quartiles. The primary outcome was PE, and the secondary outcomes were preterm birth and low birth weight (LBW). Multivariable logistic regression was used to calculate the odds ratios (ORs) for the TyG index quartiles compared to the lowest quartile for the primary and secondary outcomes. Subgroup analyses were conducted to evaluate the effect of age, body mass index (BMI), parity and TyG test week on these associations. The predictive efficacy of the TyG index for PE was assessed using receiver operating characteristic (ROC) curve analysis.

Results

After adjusting for confounders, compared to TyG index Q1, a higher TyG index was positively associated with PE (TyG index Q3 OR = 1.23, 95% confidence interval (CI): 1.06–1.43, P = 0.0067; TyG index Q4 OR = 1.31, 95% CI: 1.11–1.53, P = 0.0011) and preterm birth (TyG index Q4 OR = 1.18, 95% CI: 1.01–1.37, P = 0.0376), negatively associated with LBW (TyG index Q3 OR = 0.84, 95% CI: 0.74–0.97, P = 0.0147). In Model I, a significant association was observed between higher TyG quartiles and preterm birth (P = 0.0472 for Q3 and P = 0.0000 for Q4), but this association was not significant in Model II after adjusting for confounders. Subgroup analyses revealed that age, pre-pregnancy BMI, parity and test week did not influence these associations (interaction P > 0.05). The area under the ROC curve (AUC) for the predictive model was 0.596 (95% CI: 0.584–0.608), with a sensitivity of 65.4% and a specificity of 49.6%.

Conclusion

The present findings suggested that the TyG index associated with a high risk of PE. Clinical evaluation incorporating the TyG index during early pregnancy may help in screening for patients at high risk of PE.

Background

Preeclampsia (PE) is a severe complication of pregnancy with an incidence of 5 ~ 8% [1]. PE is clinically characterized by the emergence of hypertension and proteinuria following the 20th week of gestation [2]. This condition poses significant risks to both maternal and neonatal health, potentially resulting in adverse outcomes such as preterm delivery, restricted fetal growth, neonatal asphyxia, placental abruption, and maternal death [3]. Timely detection and appropriate management of PE are critical to ensuring the health and safety of both pregnant individuals and their offspring. The exact etiology of PE remains unclear, and researchers have been working to identify maternal blood biomarkers that can predict the onset of PE, such as soluble fms-like tyrosine kinase 1 (sFlt-1) [4] and placental growth factor (PlGF) [5]. However, the effectiveness of these biomarkers still needs validation. Despite advances in obstetric care, there remains a significant clinical gap in the early prediction and prevention of PE.

Insulin resistance (IR), as part of metabolic syndrome, is reported to be one of the early pathological states in hypertensive disorders of pregnancy [6]. This pathological state may exist even before the clinical symptoms of PE appear after 20 weeks of gestation [7]. While physiological IR in normal pregnancy is beneficial for fetal nutrition supply and growth [8], excessive IR can have harmful effects on both maternal and fetal health, including an elevated risk of PE [7]. In recent years, the triglyceride-glucose (TyG) index, derived from fasting plasma levels of triglycerides and glucose, has gained recognition as a robust marker for detecting IR and related metabolic abnormalities. Due to its ease of measurement, the TyG index has become a popular topic and is widely applicable in clinical practice. Researches have demonstrated that the TyG index is linked to an increased risk of gestational diabetes mellitus [9, 10], cardiovascular disease [11, 12], and metabolic syndrome [13]. Nevertheless, there is limited literature exploring the association between the TyG index and PE. A recent retrospective analysis has shown that among pregnant women with normal glucose tolerance, a higher TyG index correlates with an elevated risk of PE. Furthermore, the integration of the TyG index with glycated hemoglobin levels demonstrates potential predictive significance for identifying PE [14]. Another retrospective study has also reported similar results [15]. However, a recent prospective cohort study revealed that no significant association was found between the TyG index and the risk of PE [10]. Previous studies on the TyG index and PE have some limitations, such as small sample size [10, 15], insufficient control of confounding factors [15], and the acquisition of the TyG index in the mid-to-late stages of pregnancy after the diagnosis of PE [14]. These limitations reduce the generalizability of the findings and may fail to capture early pathological changes that occur before clinical symptoms manifest. By focusing on early pregnancy TyG measurements and the stratification of TyG index based on quartiles, the present study aimed to overcome these limitations and provide a more comprehensive understanding of the role of IR in the development of PE.

This study leverages large-scale, multicenter clinical data to examine the relationship between the TyG index during early pregnancy and the risk of PE. Multivariable logistic regression analysis was performed to evaluate the utility of the TyG index in predicting PE risk while accounting for various potential confounding factors. Subgroup analyses were conducted, stratified by maternal age, body mass index (BMI), parity and TyG index test week, to assess whether these variables modify the association between the TyG index and PE. The predictive efficacy of the TyG index for PE was assessed using receiver operating characteristic (ROC) curve analysis. Unlike prior studies, this investigation utilized the TyG index measured before 20 weeks of gestation and analyzed its association with PE after stratifying the TyG index, offering novel perspectives on PE prediction. The present findings may assist clinical practitioners in offering early monitoring, preventive measures, and treatment strategies for pregnant individuals with elevated TyG index values in early pregnancy, potentially improving overall pregnancy outcomes.

Methods

Design and participants

This retrospective cohort analysis encompassed women with singleton pregnancies who visited Obstetrics and Gynecology Hospital of Fudan University, Huangpu Branch (Center 1) and Yangpu Branch (Center 2) and the First People’s Hospital of Chenzhou (Center 3) from January 2019 to June 2024. Clinical data and assessments were collected and evaluated during the participants’ first visit which was defined as the initial prenatal visit, typically occurring between 12 and 20 weeks of gestation. Variability in gestational weeks at TyG testing was due to differences in when women initiated prenatal care. To address this variability, a sensitivity analysis restricting the sample to those tested within a narrower gestational window (< 14 weeks and 14 ~ 20 weeks) was conducted to ensure consistency in the timing of measurements.

All participants delivered at the hospital where they received care, with all clinical and laboratory data being retrieved from the Hospital Information System (HIS) and Laboratory Information System (LIS). The inclusion criteria for this study were as follows: (1) age ≥ 20 years; (2) singleton pregnancy; and (3) visits and deliveries at one of the participating centers. The following criteria were applied for exclusion: (1) first triglyceride and fasting glucose measurements taken after 20 weeks of gestation; (2) twin or multiple pregnancies; (3) pre-existing hypertension; (4) comorbidities such as type 1 diabetes mellitus or type 2 diabetes mellitus, hyperlipidemia or metabolic syndrome diagnosed before pregnancy; kidney disease, heart diseases, or other internal or surgical diseases; and (5) incomplete clinical or laboratory data. Ultimately, 41,694 pregnant women were included in the present study, including 2,308 women with PE and 39,386 women without PE. The study process diagram is depicted in Fig. 1.

Fig. 1

Flowchart illustrating the participant selection process

The study received ethical approval from the Medical Ethics Committees of the Obstetrics and Gynecology Hospital of Fudan University and the First People’s Hospital of Chenzhou. It was conducted in accordance with the principles set forth in the Declaration of Helsinki (as revised in Fortaleza, Brazil, October 2013). All participants provided broad informed consent upon their first visit.

Variables and measurements

The TyG index served as the exposure variable of interest. Clinical and laboratory data was gathered from pregnant women prior to 20 weeks of gestation. Venous blood samples were obtained after a minimum fasting period of 8 h, and the subsequent laboratory parameters were analyzed using an automated hematology analyzer: triglycerides (mg/dL), total cholesterol (TC, mg/dL), fasting plasma glucose (FPG, mg/dL), alanine transaminase (ALT, U/L), uric acid (UA, µmol/L), and creatinine (µmol/L). The TyG index was computed using the formula: TyG = ln[triglycerides (mg/dL) × fasting glucose (mg/dL) / 2]. Participants were categorized into quartiles based on their TyG index values.

The selection of confounders was guided by a combination of literature review and univariate analysis. Variables that showed significant associations (P < 0.001) in univariate analyses were adjusted in Model II. All included confounders had variance inflation factors (VIF) less than 5, indicating no significant multicollinearity issues. Confounding variables included age, BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP), aspirin use, antihypertensive medication use, history of hypertension, tobacco use, alcohol consumption, in vitro fertilization (IVF), ALT, UA, creatinine, TC, FPG, test week, adverse pregnancy history, and educational level. BMI was computed by dividing pre-pregnancy weight (kg) by the square of height (m²) and was classified into two categories: underweight or normal (< 24 kg/m²) and overweight (≥ 24 kg/m²). Age was categorized as normal (< 35 years) and advanced (≥ 35 years). BMI and age cutoffs were determined based on clinical relevance and World Health Organization (WHO) classifications [16]. Adverse pregnancy history was defined as prior PE, miscarriage, or other significant obstetric complications. Education levels were categorized into postgraduate, bachelor’s degree or above, college diploma, high school, and less than junior high school.

Outcomes and measurements

The main outcome assessed in this study was PE. The diagnostic criteria for PE were based on the 2020 guidelines established by the American College of Obstetricians and Gynecologists (ACOG) [17]. PE was diagnosed when a patient with normal blood pressure prior to pregnancy developed systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg after 20 weeks of gestation, along with proteinuria (+ or higher) or a 24-hour urine protein level exceeding 300 mg. PE was also diagnosed if any of the following characteristics were present without proteinuria: platelet count < 100 × 10⁹/L, liver function impairment (serum transaminases > 2 times the upper limit of normal), renal function impairment (serum creatinine > 1.1 mg/dL or > 2 times the upper limit of normal), pulmonary edema, new-onset headache unexplained by other causes, or visual disturbances.

The secondary outcomes included low birth weight (LBW) and preterm birth. LBW was defined by the WHO as a birth weight of less than 2500 g [16], while preterm birth was characterized as delivery occurring before 37 weeks of gestation, in accordance with WHO guidelines [18]. For women with regular menstrual cycles, fetal gestational age was determined based on the first day of the last menstrual period. In cases of irregular menstrual cycles, early pregnancy ultrasound was utilized to estimate gestational age.

Statistical analysis

Baseline characteristics of the study population were described according to the TyG index quartiles (Q1-Q4). Continuous variables were expressed as means ± standard deviations, while categorical variables were reported as percentages. To assess differences in covariates among participants, continuous variables were compared using weighted t-tests, and categorical variables were evaluated using weighted chi-square tests.

Multivariable logistic regression analyses was applied to investigate the association between the TyG index and the primary and secondary pregnancy outcomes. The findings were reported as odds ratios (ORs) accompanied by 95% confidence intervals (CIs). The lowest TyG index quartile (TyG Q1) served as the reference group. Model I did not adjust for any covariates, while Model II adjusted for age, BMI, SBP, DBP, aspirin use, antihypertensive medication use, history of hypertension, tobacco use, alcohol consumption, parity, IVF, ALT, UA, creatinine, TC, test week, adverse pregnancy history, and education levels.

To further understand the relationship between the TyG index and the risk of PE, subgroup analyses were conducted by stratifying participants according to age (< 35 years or ≥ 35 years), BMI (< 24 kg/m² or ≥ 24 kg/m²), parity (primiparous or multiparous), and test week (< 14 weeks or 14 ~ 20 weeks) to determine the impact of these variables on the outcomes. Likelihood ratio tests were used to assess interactions between subgroups.

Additionally, to evaluate the predictive performance of the TyG index for PE, ROC curves were plotted. Predictive models were established with PE as the dependent variable and the TyG index, maternal SBP and DBP as independent variables. The area under the curve (AUC) was calculated. We not only assessed the predictive ability of the TyG index alone for PE but also compared the predictive performance of the “SBP and DBP alone” versus the “combination of the TyG index with SBP and DBP” for PE.

The statistical analyses were conducted using IBM SPSS (version 21.0, IBM, Armonk, NY) and R statistical packages (R Foundation, version 4.4.1). A significance level of P < 0.05 was employed for determining statistical significance. The retrospective cohort study followed the guidelines outlined in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) and the Reporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) checklists [19, 20].

Results

Baseline characteristics

Table 1 summarizes the baseline characteristics of the study participants grouped by the TyG index quartiles. According to strict inclusion and exclusion criteria, 41,694 singleton pregnant participants were enrolled in the present study, including 2,308 PE patients and 39,386 healthy pregnant women. The mean TyG level and its standard deviation (SD) were measured as 7.86 ± 0.18, 8.24 ± 0.08, 8.51 ± 0.08, and 8.96 ± 0.24 for quartile 1, quartile 2, quartile 3 and quartile 4 respectively. As shown in Table 1, cases with any missing clinical data were excluded, accounting for the difference in the sample sizes for other variables from the total number of cases in the primary outcome analysis. Overall, the number of participants in each group was balanced. Differences between groups were statistically significant, except for LBW, hypertension history, and tobacco use. The incidence of PE across different TyG index groups ranged from 3.81 to 8.14%. The risk of PE increased with higher TyG index values. Similarly, maternal age, BMI, SBP, DBP, IVF, preterm birth, tobacco, alcohol consumption, adverse pregnancy history, triglycerides, TC, UA, ALT, and FPG all increased with higher TyG index values (P < 0.001).

Table 1 Baseline characteristics of participants

Association between the TyG index and PE

As shown in Table 2, the TyG index was stratified into quartiles, with the lowest quartile (TyG index Q1) serving as the reference. Multivariate regression analysis results revealed that, in Model I, compared to TyG index Q1, participants of TyG index Q3 and TyG index Q4 had a higher risk of PE and preterm birth (OR > 1) and a lower risk of LBW (OR < 1). However, in Model II, compared to TyG index Q1, only participants in TyG index Q3 and TyG index Q4 showed a significant increased risk of PE by 23% (95% CI: 1.06–1.43, P = 0.0067) and 31% (95% CI: 1.11–1.53, P = 0.0011) respectively. In Model II, compared to TyG index Q1, participants in TyG index Q4 showed a significant increased risk of preterm birth by 18% (95% CI: 1.01–1.37, P = 0.0376). Conversely, participants in TyG index Q3 had a 16% reduced risk of LBW (95% CI: 0.74–0.97, P = 0.0147). Figure 2 illustrates the relationship between TyG index quartiles and PE after adjusting for confounding factors.

Table 2 Risk of primary and secondary outcomes

Fig. 2

The overall relationship between the TyG index and the risk of PE based on TyG index quartiles. Age, pre-pregnancy BMI, parity, SBP, DBP, aspirin, depressor, hypertension history, tobacco, alcohol, IVF, ALT, UA, creatinine, TC, FPG, test week, adverse pregnancy history and education levels were adjusted

Subgroup analyses

To better explore the association between the TyG index and PE risk, subgroup analyses were conducted. As detailed in Table 3, subgroup analyses based on maternal age, BMI, parity, and test week demonstrated consistent association between TyG index quartiles and PE across all strata. After multivariable adjustment for potential confounders, interaction tests indicated no significant effect modification by these variables on the TyG index-PE association (all interaction P > 0.05). Figure 3 visually depicts the stratified dose-response relationships across the analyzed subgroups.

Table 3 Subgroup analysis of the TyG index and preeclampsia

Fig. 3

Stratified fitting curves among different subgroups. The results of the subgroup analyses were adjusted for age (A), pre-pregnancy BMI (B), parity (C), and test week (D). PE, preeclampsia; TyG, triglyceride-glucose index; Q, quartile; CI, confidence interval

ROC curve analyses of TyG index in predicting PE

As shown in Fig. 4, the results of the ROC curve analysis indicated that when the TyG index was used alone as a diagnostic marker for PE, the AUC was 0.596 (95% CI: 0.584–0.608), with a sensitivity of 65.4% and a specificity of 49.6%. When the TyG index was combined with SBP and DBP, the AUC increased to 0.736 (95% CI: 0.725–0.747), surpassing the AUC of 0.729 (95% CI: 0.718–0.740) obtained from using SBP and DBP. The sensitivity decreased from 69.3 to 63.3%, while the specificity increased from 64.6 to 72.4%.

Fig. 4

(A) ROC curve of TyG index for predicting the development of PE. (B) ROC curve of TyG index combined with SBP and DBP compared to maternal SBP and DBP alone for predicting the development of PE. TyG, triglyceride-glucose index; PE, preeclampsia; ROC, receiver operating characteristic; AUC, the area under the curve; CI, confidence interval; SBP, systolic blood pressure; DBP, diastolic blood pressure

Discussion

PE represents a serious pregnancy-related complication that carries considerable risks for both maternal and neonatal health, potentially leading to severe adverse outcomes. Previous studies have shown that physiological IR in normal pregnancy is beneficial for fetal nutrition supply and growth [8] but that excessive IR can lead to adverse maternal and fetal outcomes, such as PE [7]. As a part of metabolic syndrome, IR may be an early pathological state in hypertensive disorders of pregnancy [6]. This pathological state exists before clinical symptoms of PE appear. Nevertheless, while some patients with IR progress to develop PE, others do not, indicating that the exact relationship and mechanism by which IR impacts PE remain unclear. There is a lack of large-scale clinical studies to further validate these associations. The present study analyzed clinical and laboratory data from three large tertiary hospitals to explore the relationship between the TyG index and PE, uncovering a significant positive correlation between the TyG index and PE risk. Even after accounting for all potential confounding variables, a higher TyG index was consistently and significantly linked to an increased risk of PE. Specifically, women in the highest TyG index quartile demonstrated a 31% greater risk of developing PE compared to those in the lowest quartile. A similar positive association was observed between the highest TyG index quartile and preterm birth. Conversely, an inverse relationship was noted between the TyG index and LBW. Subgroup analyses further revealed that maternal age, BMI, and parity did not significantly modify these associations, underscoring the robustness and reliability of the findings. The AUC for the predictive model was 0.596, with a sensitivity of 65.4% and a specificity of 49.6%.

The TyG index, a biochemical marker that integrates the effects of blood triglycerides and glucose, has been shown to exhibit high sensitivity in detecting IR in individuals [21]. While prior researches have predominantly concentrated on its association with cardiovascular diseases [22, 23], fewer studies have investigated its relationship with hypertensive disorders during pregnancy. Notably, Pan et al. demonstrated that the TyG index is strongly associated with the development of gestational hypertension [24]. A recent retrospective study has discovered that in women with normal glucose tolerance during pregnancy, an elevated TyG index is associated with an increased risk of PE, and the combination of the TyG index and glycated hemoglobin levels has predictive value for PE [14]. Another study highlighted the TyG index’s potential predictive value for PE, preterm birth, and macrosomia, indicating its possible utility as a surrogate marker for these adverse pregnancy outcomes [15]. However, a recent prospective cohort study revealed that no significant association was found between the TyG index and the risk of PE [10]. The recent study had a relatively small sample size, with only 41 cases of PE. In contrast, this study included a large sample size of 41,694 participants comprising 2,308 PE patients and 39,386 healthy controls from multiple centers. This substantial increase in sample size allowed us to overcome potential biases and provided more robust and reliable results. Secondly, in this study, PE is the primary outcome of interest. Detailed analysis was conducted based on the TyG index quartiles to assess its association with PE. After adjusting for over ten confounding factors, this study showed that higher TyG indices were significantly associated with an increased risk of PE compared to lower TyG indices. Furthermore, this study employed sophisticated statistical methods, including multivariable logistic regression and subgroup analyses, to control for various confounders. By using these rigorous analytical techniques, we aimed to provide a clearer picture of the relationship between the TyG index and PE risk.

After accounting for confounding factors, the present study identified that only the third quartile (Q3) of the TyG index was associated with a reduced risk of LBW (OR = 0.84, 95% CI: 0.74–0.97, P = 0.0147). In contrast, no significant association was observed for the second (Q2) and fourth (Q4) quartiles. The relationship between the TyG index and neonatal birth weight has been inconsistent across previous studies [15]. While one study reported a positive correlation between the TyG index and macrosomia [25], another investigation found that the TyG index served as an independent risk factor for LBW [24]. Moreover, a protective effect against LBW was observed in Q3 compared to Q1, suggesting that moderate IR, as represented by mid-range TyG values, may be beneficial for fetal growth, potentially through mechanisms such as optimized glucose and lipid metabolism [8, 26]. In contrast, excessive IR, which was observed in higher TyG quartiles, could impair placental function and fetal nutrition, leading to adverse outcomes, such as LBW or preterm birth [27, 28]. This study suggested that different levels of the TyG index may result in contrasting outcomes and should be interpreted objectively in clinical settings when estimating neonatal birth weight.

The results of the ROC curve analysis showed that when the TyG index was used alone as a diagnostic marker for PE, the AUC was 0.596, indicating that it may not be sufficient as an independent diagnostic criterion for PE. This result may be attributed to the highly heterogeneous nature of PE, where IR is just one of many contributing factors, alongside other factors such as endothelial dysfunction and inflammatory responses. Although the AUC of the TyG index did not reach the conventional diagnostic threshold of 0.7, we believe it still holds potential clinical significance. The further analysis revealed that when the TyG index was combined with SBP and DBP alone, the AUC increased to 0.736, surpassing the AUC of 0.729 obtained from using SBP and DBP alone. Therefore, we suggest that the TyG index can serve as an auxiliary screening tool, and when used in conjunction with traditional indicators such as blood pressure, it can enhance the accuracy of risk stratification for PE.

The underlying mechanisms through which the TyG index impacts the development and progression of PE may be linked to the IR it reflects. IR is a marker of hyperglycemia, dyslipidemia, and obesity. In pregnant women, hyperglycemia, dyslipidemia, and obesity are risk factors for PE [29, 30]. IR may contribute to vascular endothelial cell injury by stimulating the release of nitric oxide (NO), which in turn can worsen endothelial dysfunction [31, 32]. Inflammatory mediators, such as tumor necrosis factor-alpha (TNF-α) and leptin, are secreted in increased amounts in the adipose tissues and placentas of individuals with IR [33]. Both endothelial dysfunction and inflammation can promote the development of PE. Moreover, excessive IR during pregnancy can lead to lipid metabolism disorders, increased oxidative stress, and placental dysfunction, ultimately contributing to the onset and progression of PE [34, 35]. Recent investigations have demonstrated that excessive IR activates the sympathetic nervous system, leading to increased vascular resistance and enhanced distal glomerular sodium reabsorption. These effects ultimately contribute to endothelial dysfunction and the subsequent development of gestational hypertension or PE [24].

The present study revealed the association between the TyG index in early pregnancy and the risk of PE. The stratified fitting curves suggested that TyG levels before 14 weeks have a more significant association with PE compared to the test week between 14 and 20 weeks. Thus, TyG levels during early pregnancy may have greater clinical significance. Clinical monitoring based on specific TyG quartiles in early pregnancy may facilitate risk stratification for PE, enabling appropriate preventive measures such as lifestyle changes and the use of low-dose aspirin for high-risk patients. These interventions are anticipated to lower the risk of adverse pregnancy outcomes for both mothers and their infants.

Strengths and limitations

A key strength of this study was the utilization of large-scale, multicenter clinical and laboratory data, which improved the generalizability of the findings. Additionally, the robustness of the results was further confirmed through multiple sensitivity analyses and subgroup evaluations. Additionally, the exposure factor in the present study was based on routine laboratory measurements available in most hospitals, making it easily accessible and clinically applicable. The TyG index provides a more accurate reflection of maternal IR, offering significant clinical value for the prediction and management of PE. Nevertheless, the current study was not without its limitations. First, while the present findings provide important insights, the retrospective design may have introduced biases such as selection bias and recall bias. Prospective studies are needed to validate the present findings and establish causality more definitively. Second, the present study only analyzed the association between the TyG index in early pregnancy and PE, without considering TyG changes in mid and late pregnancy. This omission may have introduced bias, given that TyG values may fluctuate throughout pregnancy. Future studies should standardize TyG measurement times to better evaluate its predictive value. Third, the study excluded individuals diagnosed with type I diabetes mellitus, type II diabetes mellitus, or metabolic syndrome prior to pregnancy. While this exclusion aimed to minimize the potential influence of metabolic factors on the TyG index, it may have limited the generalizability of the findings. Lastly, although adjustments were made for numerous potential confounders based on prior research and clinical expertise, certain unmeasured factors, such as dietary patterns and physical activity levels, were not fully evaluated within the current cohort, potentially introducing residual confounding.

Conclusion

The present study demonstrated that a higher TyG index in early pregnancy is independently associated with an elevated risk of PE, irrespective of maternal age, BMI, TyG index test week prior to 20 weeks, and parity. As a straightforward and easily accessible marker of IR, the TyG index may hold promise as a supplementary tool for early risk stratification of PE. Nevertheless, prospective studies are warranted to confirm its predictive value and establish optimal clinical thresholds for its application.