Predicting Poor Outcome Before Endovascular Treatment in Patients With Acute Ischemic Stroke.

ABSTRACT: Background: Although endovascular treatment (EVT) has greatly improved outcomes in acute ischemic stroke, still one third of patients die or remain severely disabled after stroke. If we could select patients with poor clinical outcome despite EVT, we could prevent futile treatment, avoid treatment complications, and further improve stroke care. We aimed to determine the accuracy of poor functional outcome prediction, defined as 90-day modified Rankin Scale (mRS) score ≥5, despite EVT treatment. Methods: We included 1,526 patients from the MR CLEAN Registry, a prospective, observational, multicenter registry of ischemic stroke patients treated with EVT. We developed machine learning prediction models using all variables available at baseline before treatment. We optimized the

SUBMITTER: Ramos LA 

PROVIDER: S-EPMC7593486 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature