Role of thromboelastography in predicting stroke risk after endovascular treatment for symptomatic intracranial atherosclerotic stenosis.

BACKGROUND

Endovascular treatment (EVT) is among the first line therapies for symptomatic intracranial atherosclerotic stenosis (sICAS) patients, while post-EVT stroke hinders its efficacy. Thromboelastography (TEG), shows promise in predicting stroke events, yet research gaps exist regarding the role of TEG in post-EVT sICAS patients. This study adopts a retrospective case-control research method to explore the effectiveness of TEG in predicting stroke events after EVT.

METHODS

Patients receiving EVT and a dual antiplatelet regimen for sICAS between September 1, 2020, and April 30, 2023, at Xuanwu Hospital, Capital Medical University, Beijing, were enrolled in this study. TEG parameters were measured 7 days after dual antiplatelet regimen. Post-EVT strokes are defined as newly onset neurologic impairment and radiology changes after surgery. Multivariable logistic regression models were constructed to predict postoperative stroke occurrence.

RESULTS

A total of 561 patients remained eligible for analysis, including 29 (5.2%) and 18 (3.2%) patients experienced ischemic strokes and hemorrhagic strokes after EVT. Multivariable analysis showed that ADP%, a TEG parameter, was an independent predictor for post-EVT ischemic events (OR = 0.642, 95% CI 0.425-0.971, P = 0.036). Logistic regression model that includes TEG parameters shows better predictive performance (ROC-AUC = 0.74) than the model including only baseline information (ROC-AUC = 0.70).

CONCLUSIONS

In people with sICAS, 25% decreased ADP% may be associated with higher post-EVT ischemic stroke risk. The integration of TEG parameters may enhance the accuracy of predicting post-EVT ischemic stroke.