Jiangang Guo, Xinghai Wang, Hailiang Xu, Chunhui Ye, Jialiang Huang, Xiaoyun Zeng
Both HbA1c and SII are correlated with ISR risk in ASO patients, and the risk increases with higher levels of these markers. A predictive model integrating SII and HbA1c had good performance and generalizability, facilitating early identification of high-risk ISR patients.
OBJECTIVE: To analyze the association between systemic immune-inflammation index (SII), glycated hemoglobin (HbA1c) levels and the risk of in-stent restenosis (ISR) in patients with arteriosclerosis obliterans (ASO) after stent implantation.
METHODS: A retrospective study was conducted on ASO patients (n=129) who underwent stent implantation at the Affiliated Hospital of Guilin Medical University between January 2021 and December 2023. Patients were categorized into ISR (n=71) and non-ISR (n=86) groups based on ISR status at 1-year follow-up. Propensity score matching (PSM, 1:1) was used to balance baseline characteristics. Logistic regression and restricted cubic spline (RCS) models were used to evaluate the SII-ISR relationship. An external validation cohort comprising 72 ASO patients from the same center, recruited between January 2024 and December 2024, was used to verify the generalizability of the established predictive model.
RESULTS: After PSM, the ISR group exhibited significantly higher HbA1c and SII levels compared to the non-ISR group (P < 0.05). Multivariate logistic regression showed that elevated HbA1c and SII were independently associated with increased ISR risk (P < 0.05). RCS models revealed linear dose-response relationships between SII (Ptotal trend=0.037, Pnonlinear=0.427), HbA1c (Ptotal trend=0.023, Pnonlinear=0.099), and ISR risk. The combination of SII and HbA1c enhanced model predictive performance (AUC=0.705, 95% CI: 0.599-0.811) with good calibration. External validation confirmed the model's predictive ability, with an AUC of 0.718 (95% CI: 0.594-0.841).
CONCLUSION: Both HbA1c and SII are correlated with ISR risk in ASO patients, and the risk increases with higher levels of these markers. A predictive model integrating SII and HbA1c had good performance and generalizability, facilitating early identification of high-risk ISR patients.