Machine learning based outcome prediction of large vessel occlusion of the anterior circulation prior to thrombectomy in patients with wake-up stroke.
Journal:
Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
Published Date:
Aug 1, 2024
Abstract
PURPOSE: Outcome prediction of large vessel occlusion of the anterior circulation in patients with wake-up stroke is important to identify patients that will benefit from thrombectomy. Currently, mismatch concepts that require MRI or CT-Perfusion (CTP) are recommended to identify these patients. We evaluated machine learning algorithms in their ability to discriminate between patients with favorable (defined as a modified Rankin Scale (mRS) score of 0-2) and unfavorable (mRS 3-6) outcome and between patients with poor (mRS5-6) and non-poor (mRS 0-4) outcome.