Association between non-insulin-based insulin resistance indices and cardiovascular events in patients undergoing percutaneous coronary intervention: a retrospective study

Increasing evidence suggested that IR, as the major characteristic of type 2 DM, has a major role in the pathogenesis of CVD [31]. Currently, growing evidence also suggests that elevated IR can initiate and contribute to the development of CVD, as well as predict cardiovascular events in patients with pre-existing CVD [32‐34]. More importantly, although remarkable advancements have been made in clinical practice, such as timely PCI and medication treatment, the incidence of CVD in general population continues to rise, and the long-term cardiovascular events, like restenosis in stents, heart failure, stroke and cardiac death, remain high. Therefore, there is an urgent need to identify the IR promptly and accurately, with an expectation of improving primary and secondary prevention through establishing effective cardiovascular risk stratification. While the hyperinsulinemic-euglycemic clamp is regarded as the gold-standard method of assessing IR [12], its complexity limits its application in clinical practice and epidemiological investigation. Consequently, several reliable and valid alternatives for non-insulin-based IR assessment have been developed [13‐17]. However, to date, the relationship between IR and cardiovascular outcomes of patients undergoing PCI have not been well elucidated. Thus, this study was designed to explore the association of METS-IR with MACCEs and compare the predictive abilities of the four IR indices for MACCEs in elderly or female patients undergoing PCI.

Data from a study of 1092 ACS patients undergoing PCI suggested that patients with the upper quartile of TyG index had an increased risk of MACCEs within 1 year after PCI (hazard ratio (HR): 1.53, 95% CI: 1.00−2.06, P = 0.003) [9]. Another study by Xiong et al., which included 633 consecutive patients with type 2 DM undergoing PCI and followed up for 18.83-month, found that TyG index independently predicted the major adverse cardiac events (HR: 1.80, 95% CI: 1.26−2.57, P = 0.001). Furthermore, the inclusion of TyG index in basic risk model significantly improved the predictive performance [35]. Evidence from the Korean population indicated that TyG-BMI index was superior to TyG index for IR prediction [36]. The TyG-BMI index has also demonstrated a robust and independent association with ischemic stroke [37]. However, the inconsistent results were found in a rural Chinese cohort study involving 14,595 participants. The study suggested that the relative risk (95% CI) for stroke with per 1.0-SD increment in TyG index was 1.23 (1.15−1.32) and in TyG-BMI index was 1.17 (1.09−1.26) (both P < 0.05), and the C-statistics (95% CIs) for predicting stroke were 0.614 (0.606−0.621) for TyG index and 0.598 (0.590−0.606) for the TyG-BMI index, respectively [25]. Furthermore, a study by Yunke et al. involving 317 participants revealed that TG/HDL-C ratio could independently predict cardiovascular events [38]. Two other studies also demonstrated that the TG/HDL-C ratio was an effective biomarker for evaluating the severity of CAD [22, 39]. However, there are inconsistent findings regarding the priority between TyG index and TG/HDL-C ratio.

More recently, the METS-IR has been proposed as a more promising and reliable indicator for evaluating IR and predicting cardiovascular outcomes [13]. Mounting evidence suggests that METS-IR is positively associated with the severity of CAD and has a better predictive ability than the other three indices [22, 39]. These findings are consistent with our own findings, as only METS-IR showed a positive correlation with MACCEs in both female and elderly patients in the subgroup analyses (Fig. 2). The positive association of METS-IR with MACCEs remains robust in elderly and female patients (Tables 4 and 5), but not in the overall population. There are several possible reasons for the findings. Firstly, age is a well-known risk factor for CAD, and elderly individuals with CAD are more likely to experience cardiovascular events [40]. Secondly, the elderly patients in our study had a higher proportion of multi-vessel (2- and 3-vessel) disease, higher BMI, higher prevalence of DM, and longer length of stents. Regarding the sex-specific difference, female patients in our study were much older than male patients (63.24 ± 10.04 vs. 58.67 ± 11.28). Thirdly, the prospective effect of estrogen on circulating and endocrine systems may diminish or disappear for females in menopausal transition or postmenopausal period [41, 42]. Aging women, especially those in the menopausal transition or postmenopausal period, are more likely to have increased abdominal fat accumulation and a higher prevalence of metabolic dysfunction, such as dyslipidemia, IR, and chronic low-grade inflammation [41, 43]. Several previous studies have also reported a more pronounced association of IR with cardiovascular events in females compared to males, which is consistent with our results [34, 44]. Moreover, differences in endothelial function between elderly and younger patients may contribute to the observed results. Age-related arterial stiffness and endothelial dysfunction can impact treatment response and long-term outcomes in elderly patients [45]. Additionally, chronic low-grade inflammation is common in elderly or perimenopausal women, which may increase the risk of MACCEs [43]. Finally, elderly and female CAD patients often have a higher burden of comorbidities and coexisting conditions, such as hypertension, DM, abdominal obesity, and chronic kidney disease [46], which can interact with CAD and influence treatment outcomes.

Furthermore, a prospective cohort study of 6489 adults suggested that the highest quintile and per 1.0-SD increasement in METS-IR were highly correlated with a higher risk of CVD incidence (HR: 1.80, 95% CI: 1.24−2.61, P < 0.01; HR: 1.17, 95% CI: 1.05−1.31, P < 0.01, respectively) [47]. These inconsistent results may be attributed to the heterogeneity of the included population and study design. Therefore, there is an urgent need to conduct our study to provide additional evidence on whether non-insulin IR indices can predict cardiovascular outcomes in patients undergoing PCI.

The association between these indices and MACCEs in patients undergoing PCI with at least one DES may be explained, at least in part, by the following mechanisms. First, involvement of IR in the pathogenesis of CAD: high circulating insulin concentrations can reduce the production of nitric oxide via the activation of serum and glucocorticoid kinase 1, leading to decreased nitric oxide concentration. This, in turn, can result in matrix protein deposition and fibrosis [48]. Second, the metabolic impairment of lipid and glucose induced by IR: IR can lead to the overproduction of reactive oxide species through the activation of signaling pathways, such as the protein kinase C pathway and the nuclear factor (NF)­κB pathway. These pathways can trigger cardiovascular events [49]. Third, the ectopic synthesis of angiotensinogen and the inappropriate activation of the RAAS caused by IR contribute to fluid retention and high blood pressure [10, 11]. Finally, impact of insulin on thrombosis and platelet aggregation: insulin can impair fibrinolysis by increasing the circulating concentration of plasminogen activator inhibitor 1. This can lead to a pro-thrombotic state and promote platelet aggregation in the cardiovascular system [50].

In this study, we explored the correlation of METS-IR with MACCEs and respectively assessed the predictive ability of the four IR indices for MACCEs in CAD patients undergoing PCI. While we found no positive association between these IR indices and MACCEs in overall population, and no additional predictive performance was observed, our results suggest that both METS-IR and TyG-BMI index could serve as effective and reliable predictors for MACCEs in elderly patients (age ≥ 60 years) and female patients with CAD undergoing PCI. These findings have far-reaching significance for secondary prevention and risk stratification in these patient populations. However, there are several limitations that should be acknowledged. Firstly, the lack of follow-up time in the dataset prevented us from conducting the time-to-event analysis, which may underestimate the association between IR and MACCEs. Secondly, due to the observational nature of the study, obtain dynamic data on the four IR indices during the follow-up period were unavailable. Having longitudinal data could have added value to the risk stratification of MACCEs. Therefore, future prospective, large-scale, multicenter randomized controlled trials are needed to address this limitation. Thirdly, the dataset did not provide information on hypoglycemic treatment, which could potentially introduce bias in the analysis. Additionally, the lack of data on patients’ dietary habits is another notable limitation, as diet could be a crucial confounder. Including detailed dietary assessments in future studies would be helpful to a more comprehensive understanding of the association between IR and MACCEs and enhance the validity of the results. Finally, despite adjusting for many potential confounders, there may still be residual or unmeasured confounders that could influence the observed associations, such as sleep duration and physical activities. Future studies should consider incorporating these factors to further improve the accuracy and validity of the results.