Inflammation and Insulin Resistance-Derived Indicator Predicts Adverse Cardiovascular Outcomes in Heart Failure Patients Undergoing Percutaneous Coronary Intervention

Abstract

Background Inflammation and insulin resistance play important roles in the initiation and progression of heart failure and coronary artery disease. However, there’s lack of indicator related to inflammation and insulin resistance to predict the prognosis of that population. This study aims to evaluate the potential value of C-reactive protein-triglyceride glucose index (CTI) in heart failure patients undergoing percutaneous coronary intervention (PCI). Methods 2797 PCI-treated patients with heart failure at Beijing Fuwai Hospital between 1st January 2016 and 31st December 2018 were retrospectively enrolled in current study. The primary endpoint was major adverse cardiac and cerebrovascular events at 12-month follow-up, defined as a composite of all-cause death, non-fatal myocardial infarction and stroke. Restricted cubic spline was applied to determine the cut-off value of CTI and examine the dose-response relationship between the CTI and the primary endpoint. Multivariate Cox proportional hazards models were used to evaluate the predictive value of CTI for the adverse cardiovascular outcomes and the results were expressed as hazard ratio with 95% confidence interval. The receiver-operating characteristics and decision curve analysis were plotted to comprehensively evaluate the predictive accuracy and clinical use of the CTI when adding it into the baseline model used to predict the prognosis of that population. Finally, subgroup analysis was conducted to evaluate the interaction between the traditional cardiovascular risk factor and CTI-related cardiovascular outcomes. The calculation method of CTI was as followed: ln[triglyceride(mg/dl) × fasting blood glucose(mg/dl)/2] + 0.412 × ln (C-reactive protein). Results Among the 2797 PCI-treated patients with heart failure, 131 experienced MACCEs. Restricted cubic spline model showed that the CTI was significantly associated with the risk of adverse cardiovascular outcomes within 12 months (P for nonlinearity < 0.001), with a best cut-off value of 9.47. After adjusting for various confounders, the CTI remained independently associated with the incidence of endpoints (hazard ratio 1.41; 95%CI 1.13–1.77; P < 0.01) while the TyG index was not. Furthermore, Kaplan-Meier analysis demonstrated a higher incidence of endpoints (hazard ratio 1.55; 95%CI 1.11–2.16; Log rank P = 0.011) and all-cause death (hazard ratio 2.16; 95%CI 1.16–3.99; Log rank P = 0.015) in enrolled patients with high CTI (CTI ≥ 9.47). Adding the CTI into the baseline model used to predict the adverse outcomes improved the predictive ability for the endpoints (increase in C-statistic value from 0.685 to 0.694; NRI 0.217, 95% confidence interval 0.050–0.385, P = 0.011; IDI 0.003, 95% confidence interval 0.001–0.007, P = 0.049). Subgroup analysis showed that there existed an interaction between CTI and hypertension for the prediction of endpoints (P for interaction = 0.046). Conclusions Elevated CTI is associated with an increased risk of adverse cardiovascular outcomes in heart failure patients undergoing PCI, indicating the potential use of the CTI in the risk stratification and prognosis prediction of that population.