Association of systemic immune-inflammation index with severity in acute ischemic stroke patients: a cross-sectional study

Abstract

Objective: To investigate the association between the Systemic Immune-Inflammation Index (SII) and the severity of acute ischemic stroke (AIS), as measured by the National Institutes of Health Stroke Scale (NIHSS), and to explore its potential as a predictive marker for clinical outcomes. Methods: We used the data of 1723 AIS patients in the Stroke Center of Quzhou People’s Hospital from September 2016 to September 2022 for a cross-sectional study. SII was calculated as platelet count × neutrophil count divided by lymphocyte count. Stroke severity was classified as mild (NIHSS < 8) or severe (NIHSS ≥ 8). Multivariable logistic regression and subgroup analyses were performed to evaluate the relationship between SII levels and NIHSS scores, adjusting for confounders such as age, sex, and comorbidities. Nonlinear associations and threshold effects were further assessed using smooth curve fitting. Results: Elevated SII levels were independently associated with higher stroke severity (OR: 1.04, 95% CI: 1.01–1.07). A nonlinear relationship was identified, with a critical range of SII/100 values (2.4–7.8) demonstrating the strongest correlation with NIHSS scores. Patients in the highest SII quartile (Q4) exhibited a 3.46-fold increase in odds of severe stroke compared to those in the lowest quartile (Q1) (p < 0.001). Subgroup analyses confirmed the robustness of these findings across diverse demographic and clinical profiles. Conclusion: SII is a robust biomarker for predicting stroke severity in AIS patients. The observed nonlinear relationship highlights its potential utility in identifying critical inflammatory thresholds for risk stratification and personalized therapeutic interventions.