Serum inflammatory cytokines predict 90-day outcome after endovascular treatment in acute ischemic stroke.

BACKGROUND AND OBJECTIVE: Inflammation plays a critical role in acute ischemic stroke (AIS) pathophysiology and may influence outcomes after endovascular treatment (EVT). However, the incremental prognostic value of inflammatory cytokines beyond conventional predictors remains unclear. This study aimed to investigate the association of cytokines with 90-day functional outcomes in EVT-treated AIS patients and evaluate their value in prognostic modeling. METHODS: Based on the prospective DETECT2-China registry, we included consecutive large vessel occlusion patients undergoing EVT between March 2022 and March 2025. Plasma cytokines were measured within 24 h post-EVT. The primary outcome was 90-day poor functional outcome (modified Rankin Scale [mRS] 3-6). Multivariable logistic regression identified independent predictors. Clinical, cytokine, and combined models were constructed and evaluated using receiver operating characteristic (ROC) curves, calibration, decision curve analysis (DCA), and reclassification metrics. RESULTS: Among 139 included patients, 77 (55.4%) had 90-day poor outcomes. Serum IL-6 and IL-10 levels were significantly higher in these patients. In multivariable analysis, log₂-IL-6 was an independent predictor (OR = 1.43 per doubling, 95% CI: 1.14-1.79, p = 0.002), and log2-IL-10 was significant in Adjusted Model 2 (OR = 1.86 per doubling, 95% CI: 1.02-3.36, p = 0.041). The combined model achieved superior discrimination (AUC: 0.841, 95% CI: 0.770-0.905) compared with the clinical model (AUC: 0.791, 95% CI: 0.717-0.865; p = 0.015), with good calibration and clinical net benefit. Reclassification was also improved (continuous NRI: 43.32%, p = 0.009; IDI: 7.27%, p < 0.001). CONCLUSION: Serum IL-6 is independently associated with 90-day poor outcome While incorporating cytokines into clinical models may improve prognostic estimation, these exploratory findings require validation in independent cohorts before clinical application.