Immunoinflammatory biomarkers as predictors of hemorrhagic transformation in acute ischemic stroke patients after endovascular thrombectomy - Bao, Li; Wang, Yuhang; He, Shuang (Frontiers in Neurology, 2025)
BackgroundHemorrhagic transformation (HT) and symptomatic intracranial hemorrhage (sICH) are common complications of endovascular thrombectomy (EVT) in acute ischemic stroke (AIS) patients. The role of peripheral immune inflammation in HT after EVT is unclear. This study aimed to evaluate the relationship between immune inflammatory factor levels and HT and sICH occurrence, and to develop predictive models.MethodsWe included 81 AIS patients who underwent EVT. Peripheral blood samples were collected immediately post-EVT to measure immunoinflammatory markers. Least absolute shrinkage and selection operator (LASSO) regression was used to select variables, and backward stepwise multivariable logistic regression identified independent predictors and predictive models for HT and sICH. The models’ discrimination was assessed using the area under the receiver operating characteristic curve (AUC), and calibration was evaluated using the Hosmer–Lemeshow test. Logistic regression models were used to evaluate the impact of HT or sICH on 90-day functional outcomes and mortality.ResultsThe HT rate was 39.51% (32/81), and the sICH rate was 17.07% (14/81). Multivariate analysis revealed that HT after EVT was significantly associated with collateral score [OR 0.27 (95% CI 0.13–0.52), p < 0.001], arteriosclerosis etiology [OR 0.11 (95% CI 0.02–0.46), p = 0.006], puncture to recanalization time [OR 3.72 (95% CI 1.07–14.59), p = 0.04], and levels of IL-6 [OR 7.33 (95% CI 2.1–31.07), p = 0.003; AUC 0.696 (95% CI 0.593–0.799)]. sICH was independently related to direct aspiration (DA) techniques [OR 0.07 (95% CI 0.09–0.35), p = 0.004] and neutrophil-to-albumin ratio (NAR) values [OR 5.69 (95% CI 1.16–37.24), p = 0.044; 0.676 (95% CI 0.550–0.803)]. Both predictive models for HT [AUC 0.898 (95% CI 0.831–0.965)] and sICH [AUC 0.925 (0.853–0.997)] exhibited good discrimination and calibration.ConclusionIL-6 and NAR are potential biomarkers for predicting HT and sICH in AIS patients after EVT. This study developed simple and effective predictive models for HT and sICH based on immunoinflammatory factors. Future research should explore the spatiotemporal effects of immune inflammation on prognosis in AIS patients undergoing EVT.