Changes in Immune‐Inflammation Status and Acute Ischemic Stroke Prognosis in Prospective Cohort
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Inflammation is a critical risk factor for poor outcomes in cerebral infarction. Prior studies focused primarily on baseline inflammation status, neglecting dynamic longitudinal changes. We try to investigate the association between immune-inflammation status alterations and stroke prognosis, and evaluated three systemic biomarkers' predictive efficacy. METHODS: In this prospective cohort study of ischemic stroke patients, C-reactive protein-albumin-lymphocyte (CALLY), Systemic Immune-Inflammation Index (SII), and Systemic Inflammation Response Index (SIRI) were assessed. Immune-inflammation changes were measured between baseline and a second survey. The primary outcome was death or major disability (modified Rankin Scale score ≥ 3) after stroke onset. Prognostic performance for poor outcomes was evaluated at baseline. The association was calculated by Cox proportional hazard models. RESULTS: Elevated baseline CALLY correlated with reduced poor outcome risk (OR 0.33, 95% CI 0.20-0.53), while higher SII and SIRI indicated increased risk (SII OR 2.54, 95% CI 1.61-4.06; SIRI OR 2.37, 95% CI 1.47-3.87). Adding these markers to conventional risk factors significantly improved prediction, with CALLY showing the greatest enhancement (C-statistic 0.882 vs. 0.862; p = 0.004; NRI = 29.68%; IDI = 0.39%). Compared to stable mild status, progression to severe status increased poor outcome risk, while recovery to mild status reduced risk (CALLY OR 14.2, 95% CI 2.31-64.27; SII OR 1.27, 95% CI 1.01-7.10; SIRI OR 4.10, 95% CI 1.61-10.71). High inflammatory indices and significant changes predicted poor outcomes. CONCLUSIONS: CALLY demonstrated superior predictive ability for ischemic stroke outcomes versus SII/SIRI. Both baseline levels and dynamic changes in immune-inflammation status significantly correlated with prognosis, suggesting these biomarkers could valuably predict outcomes and guide intervention.
DOI: 10.1002/acn3.70252
Authors: Songfang Chen, Wenting Huang, Yitian Liu, Xuan Chen, Buyu Ke, Qian Shen, Hanyu Cai, Jing Sun, Yan Li, Yungang Cao, Beilei Hu, Keyang Chen
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,100
Award: G7414574006
OpenAlex ID: W4416676601
