Distinct trajectory patterns of neutrophil-to-albumin ratio predict clinical outcomes after endovascular therapy in large vessel occlusion stroke

中性粒细胞与白蛋白比值的不同变化轨迹模式可预测大血管闭塞性卒中患者血管内治疗后的临床结局

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Abstract

OBJECTIVE: To investigate the dynamic characteristics and prognostic value of neutrophil-to-albumin ratio (NAR) in patients with acute large vessel occlusion ischemic stroke (LVO-AIS) undergoing endovascular therapy (EVT). METHODS: In this retrospective cohort study, we consecutively enrolled 299 patients with anterior circulation LVO-AIS who underwent EVT between January 2018 and February 2024. NAR was measured at admission, day 1, and day 3 after EVT. The primary outcome was poor functional outcome at 90 days (modified Rankin Scale score 3-6). Secondary outcomes included symptomatic intracranial hemorrhage (sICH), malignant cerebral edema (MCE), and in-hospital mortality (IHM). Multivariable logistic regression and restricted cubic spline regression were used to analyze the association between NAR and functional outcomes. Latent class trajectory modeling (LCTM) was applied to identify NAR evolution patterns, and propensity score matching (PSM) was performed to balance baseline characteristics between different trajectory groups, followed by conditional logistic regression to assess their association with clinical outcomes. RESULTS: At 90-day follow-up, 197 patients (65.9%) had poor outcomes. The predictive value of NAR increased over time, with day 3 NAR showing the best predictive performance (poor outcome: AUC = 0.79; sICH: AUC = 0.70; MCE: AUC = 0.75; IHM: AUC = 0.81). Multivariable analysis showed that for each unit increase in day 3 NAR, the risk of 90-day poor outcome increased 2.81-fold (95% CI: 1.96-4.03, p < 0.001). LCTM analysis identified two distinct NAR evolution patterns: continuously increasing (31.1%) and peak-then-decline (68.7%). After PSM (63 patients per group), compared with the continuously increasing trajectory, the peak-then-decline trajectory was associated with significantly lower risks of poor functional outcome (OR = 0.38, 95% CI: 0.17-0.86, p = 0.020), sICH (OR = 0.38, 95% CI: 0.17-0.86, p = 0.020), MCE (OR = 0.25, 95% CI: 0.10-0.61, p = 0.002), and IHM (OR = 0.13, 95% CI: 0.04-0.42, p < 0.001). CONCLUSION: NAR trajectory patterns independently predict clinical outcomes after EVT for LVO-AIS. Dynamic monitoring of NAR, particularly on day 3 post-procedure, may facilitate early risk stratification and development of targeted intervention strategies, providing a new biomarker tool for precision stroke management.

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