Giorgio Colangelo, Marc Ribo, Estefanía Montiel, Didier Dominguez, Marta Olivé-Gadea, Marian Muchada, Álvaro Garcia-Tornel, Manuel Requena, Jorge Pagola, Jesús Juega, David Rodriguez-Luna, Noelia Rodriguez-Villatoro, Federica Rizzo, Belén Taborda, Carlos A Molina, Marta Rubiera
BACKGROUND: Predicting stroke recurrence for individual patients is difficult, but individualized prediction may improve stroke survivors' engagement in self-care. We developed PRERISK: a statistical and machine learning classifier to predict individual risk of stroke recurrence. METHODS: We analyzed clinical and socioeconomic data from a prospectively collected public health care-based data set of 41 975 patients admitted with stroke diagnosis in 88 public health centers over 6 years (2014-2020) in Catalonia-Spain...
March 28, 2024: Stroke; a Journal of Cerebral Circulation