Background: Early prediction of malignant infarction may guide treatment decisions. For patients who received endovascular treatment, the risk of malignant infarction is unknown and risk factors are unrevealed.

Aims: The objective of this study is to estimate the incidence of malignant infarction after endovascular treatment in patients with an occlusion of the anterior circulation, to identify independent risk factors, and to establish a model for prediction.

Methods: We analyzed patients who received endovascular treatment for a large vessel occlusion in the anterior circulation within 6.5 h after symptom onset, included in the Dutch MR CLEAN Registry between March 2014 and June 2016. We compared patients with and without malignant infarction. Candidate predictors were incorporated in a multivariable binary logistic regression model. The final prediction model was established using backward elimination. Discrimination and calibration were evaluated with the area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow test.

Results: Of 1445 patients, 82 (6%) developed malignant infarction. Independent predictors were lower age, higher National Institutes of Health Stroke Scale (NIHSS), lower alberta stroke program early CT score (ASPECTS), internal carotid artery occlusion, lower collateral score, longer times from onset to groin puncture, and unsuccessful reperfusion. The AUROC of a prediction model combining these features was 0.83 (95% confidence interval (CI): 0.79-0.88) and the Hosmer-Lemeshow test indicated appropriate calibration (P = 0.937).

Conclusion: The risk of malignant infarction after endovascular treatment started within 6.5 h of stroke onset is approximately 6%. Successful reperfusion decreases the risk. A prediction model combining easily retrievable measures of age, ASPECTS, collateral status, and reperfusion shows good discrimination between patients who will develop malignant infarction and those who will not.

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http://dx.doi.org/10.1177/17474930211006290DOI Listing

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