Systemic immune-inflammation index as a novel biomarker for predicting surgical site infection in people living with HIV: a multicenter, retrospective cohort study.

PURPOSE: The Systemic Immune-Inflammation Index (SII) shows promise as a biomarker to assess immune status and inflammation, but its utility in predicting surgical site infections (SSIs) among HIV-infected patients remains underexplored. To evaluate SII's predictive value for SSI risk in HIV-positive surgical patients in China, suggesting an effective clinical tool for this population.

METHODS

This multicenter retrospective cohort study included HIV-infected patients with fractures from three hospitals. Baseline data on demographics, HIV metrics, comorbidities, and surgical details were collected. Univariate and multivariate logistic regression analyses examined the relationship between preoperative SII and postoperative SSIs, adjusting for potential confounders like age, gender, CD4 count, viral load, and comorbidities.

RESULTS

Of 338 HIV patients, 36 (10.65%) developed postoperative SSIs. SSI patients had significantly higher SII levels. Bivariate logistic regression analysis showed that HIV viral load, open fracture, albumin, CD4, CD4/CD8 ratio and SII were risk factors for surgical site infection in HIV-positive patients. Multivariate analysis confirmed SII as an independent predictor of SSI (OR = 3.28, 95% CI = 2.07-5.54). SII showed good discriminatory performance (AUC = 0.810) and performed better than the CD4/CD8 ratio (AUC = 0.689), which was included as a representative immune-status marker. Subgroup analyses validated SII's stability across patient subsets. Further, smooth curve fitting and RCS analysis showed that there was still a linear correlation between SII and surgical site infection in different subgroups of CD4 and HIV viral load (P for nonlinear > 0.05).

CONCLUSIONS

The SII may serve as a clinically accessible and cost-effective biomarker for identifying HIV-infected patients at increased risk of SSI. Incorporating preoperative SII assessment could support perioperative risk stratification and management. This novel approach has implications for optimizing patient care for HIV-positive surgical populations.