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Article Abstract
Aims: This study aimed to investigate the association between the systemic immune-inflammation index (SII) and prognosis trajectories in ischemic stroke(IS).
Methods: Patients from two tertiary hospitals in Suzhou were included in this study. SII was calculated as neutrophils×platelets/lymphocytes, and patients were categorized into quartiles based on SII values. Latent class growth modeling (LCGM) was employed to describe the trajectories of modified Rankin Scale (mRS) at different time points.Logistic regression models were used to evaluate the association between SII quartiles and prognosis trajectories at multiple time points (14 days, 1 month, 3 months, 6 months)and prognostic trajectories.
Results: Patients in the highest quartile (Q4) of SII had a significantly higher risk of adverse outcomes compared to those in the lowest quartile (Q1). A three-group model was identified as the optimal trajectory model for stroke prognosis. SII was associated with 4.06-fold increased odds (95% CI: 1.64-10.08) of unfavorable prognosis trajectories. Per standard deviation increase in the logarithmic SII, the odds of unfavorable prognosis trajectories were 1.64 (95% CI: 1.18-2.29).
Conclusions: Baseline SII is significantly associated with unfavorable outcome trajectories across multiple time points in IS. These findings highlight the potential value of SII as a predictive biomarker for sequential prognosis in stroke patients.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12344814 | PMC |
| http://dx.doi.org/10.1080/17520363.2025.2540760 | DOI Listing |
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