Association between the composite nutritional index TCBI and ISR

Background In-stent restenosis (ISR) is a frequent and clinically significant complication after percutaneous coronary intervention (PCI) and substantially affects long-term patient outcomes. Its underlying mechanisms are multifactorial and remain incompletely understood. The triglyceride-total cholesterol-body weight index (TCBI) has recently emerged as a novel marker of nutritional and metabolic status. However, its association with the risk of ISR has not been fully elucidated. This study aimed to investigate the value of the TCBI for predicting ISR in patients who underwent PCI. Methods From January 2022 to January 2024, a total of 454 patients who underwent PCI were enrolled and classified into a stent-narrowing group or a stent-nonnarrowing group according to follow-up coronary angiography (CAG) findings. Baseline clinical and laboratory variables were collected, and the TCBI, atherogenic index of plasma (AIP), atherosclerosis coefficient (AC), residual cholesterol (RC) and triglyceride-glucose (TyG) level were calculated using standard formulas. Univariate and multivariate logistic regression analyses were conducted to identify factors associated with ISR. Receiver operating characteristic (ROC) curves were generated, and the area under the curve (AUC) was used to compare the predictive performance of the nutritional and metabolic indices in the overall population. Restricted cubic spline modeling and segmented regression were further applied to characterize the dose–response relationship between TCBI and ISR. Mediation analysis was performed to explore potential metabolic and inflammatory mediators. Subgroup analyses were performed to assess the robustness and consistency of the association between the TCBI and ISR across clinically relevant strata. Results ROC analysis demonstrated that the TCBI had the highest predictive performance for ISR (AUC = 0.718, 95% CI: 0.665–0.771), outperforming the AIP, AC, RC and TyG. Elevated TCBI was independently associated with an increased risk of ISR according to both unadjusted and multivariable-adjusted logistic regression models. Restricted cubic spline and piecewise regression confirmed a nonlinear association between TCBI and ISR risk. Mediation analysis indicated that the relationship between the TCBI and ISR was partially mediated by metabolic and inflammatory factors, particularly uric acid (UA) levels and white blood cell (WBC) count. Subgroup analyses revealed that the association between the TCBI and ISR remained robust and consistent across different clinical characteristics, with no significant effect modification observed. Conclusion AC, RC, AIP, TyG and TCBI were associated with elevated ISR risk, with TCBI having the strongest predictive value. These findings highlight TCBI as a promising metabolic–nutritional marker for ISR risk stratification and emphasize the need for further refinement of the TCBI index to enhance its utility in cardiovascular risk assessment.