• Heng Ni, Bin Wang, Yu Hang, Sheng Liu, Zhen-Yu Jia, Hai-Bin Shi, and Lin-Bo Zhao.
• Department of Interventional Radiology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China.
• World Neurosurg. 2023 Mar 1; 171: e752e759e752-e759.

ObjectiveThe predictors of futile recanalization in patients with intracranial atherosclerosis (ICAS)-related stroke are not understood. This study aimed to identify the predictors of futile recanalization after endovascular treatment (EVT) in patients who experience an acute stroke caused by ICAS-related occlusion.MethodsWe retrospectively reviewed the data of patients with ICAS-related stroke who underwent EVT from January 2018 to July 2021. Futile recanalization was defined as functional dependence (modified Rankin scale 3-6) despite successful reperfusion (modified Thrombolysis in Cerebral Infarction score of 2 b/3). Multivariate logistic regression analysis was used to determine the risk factors associated with futile recanalization. The receiver operating characteristic curve was used to examine the predictive value of the risk prediction model for futile recanalization.ResultsOf the 87 patients enrolled, futile recanalization was observed in 32 (36.8%). Multivariate logistic analysis showed that older age (OR, 1.05; 95% CI, 1.01-1.10; P = 0.026), a higher National Institutes of Health Stroke Scale (NIHSS) score on admission (OR, 1.25; 95% CI, 1.08-1.45; P = 0.003), and poor collaterals (OR, 5.49; 95% CI, 1.70-17.79; P = 0.004) were independently associated with futile recanalization after EVT in patients with ICAS-related stroke. The receiver operating characteristic curve showed that the model in combination with age, admission NIHSS score, and collateral status could accurately predict futile recanalization in these patients (areas under the curve, 0.85; 95% CI, 0.76-0.92; P < 0.001).ConclusionsOlder age, higher NIHSS score on admission, and poor collaterals are predictors of futile recanalization in patients with ICAS-related stroke.Copyright © 2022 Elsevier Inc. All rights reserved.

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