Total Cerebral Small Vessel Disease Burden Predicts the Outcome of Acute Stroke Patients after Intra-Arterial Thrombectomy

Abstract

Introduction: Various types of cerebral small vessel diseases (cSVD) markers commonly coexist. The neurological function outcome is affected by their combined effect. To investigate the effect of cSVD on intra-arterial thrombectomy (IAT), our study aimed at developing and testing a model with fusing a combination of multiple cSVD markers as total cSVD burden to predict the outcome of acute ischemic stroke (AIS) patients after IAT treatment. Methods: From October 2018 to March 2021, continuous AIS patients with IAT treatment were enrolled. We calculated the cSVD markers identified by magnetic resonance imaging. The outcomes of all patients were assessed according to the modified Rankin Scale (mRS) score at 90 days after stroke. The relationship between total cSVD burden and outcomes was analyzed by logistics regression analysis. Results: A total of 271 AIS patients were included in this study. The proportions of score 0∼4 in the total cSVD burden group (i.e., score 0, 1, 2, 3, and 4 groups) were 9.6%, 19.9%, 23.6%, 32.8%, and 14.0%, respectively. The higher the cSVD score, the more patients with a poor outcome. Heavier total cSVD burden (1.6 [1.01∼2.27]), diabetes mellitus (1.27 [0.28∼2.23]), and higher national institute of health stroke scale (NIHSS) on admission (0.15 [0.07∼0.23]) were associated with poor outcome. In the two Least Absolute Shrinkage and Selection Operator regression models, model 1 using age, duration from onset to reperfusion, Alberta stroke program early CT score (ASPECTS), NIHSS on admission, modified thrombolysis in cerebral infarction (mTICI) and total cSVD burden as variables perform well on predicting short-term outcome in area under curve (AUC) of 0.90. Model 2, including all of the variables above except cSVD, showed less predictive capability than model 1 (AUC 0.90 vs. 0.82, p = 0.045). Conclusions: The total cSVD burden score was independently associated with the clinical outcomes of AIS patients after IAT treatment and it may be a reliable predictor for poor outcomes of AIS patients after IAT treatment.