This study aims to develop and externally validate machine learning prediction models (FORECAST-PC) to determine 90-day functional outcomes for patients suffering from acute ischemic stroke in the posterior circulation who are selected for endovascular thrombectomy (EVT)
Inclusion Criteria:
Exclusion Criteria:
Patients with PC stroke selected for EVT from three primary training centers (Lausanne University Hospital, Bern University Hospital, and Charité-Universitätsmedizin Berlin).
Unseen patients with PC stroke selected for EVT from 11 independent, world-wide comprehensive stroke centers
Lausanne, 1010, Switzerland
A Predictive Model and Scoring System for Severe Complications After Endovascular Thrombectomy
Blood Biomarkers to Predict the Prognosis of a Stroke Patient Undergoing Mechanical Thrombectomy
PROMISE: PRedictors Of Good outcoMes in Thrombectomy for Large Infarct Core Stroke Evaluation
The Prediction of Hemorrhage Transformation by Cerebral Autoregulation in AIS Patient After Endovascular Thrombectomy
Multidimensional Evaluation of Patients With Acute Ischemic Stroke Undergoing Pharmacological and Endovascular Revascularization Procedures for the Identification of Positive Prognostic Factors