Ontology highlight
ABSTRACT: Objective
To characterize patients with acute ischemic stroke related to SARS-CoV-2 infection and assess the classification performance of clinical and laboratory parameters in predicting in-hospital outcome of these patients.Methods
In the setting of the STROKOVID study including patients with acute ischemic stroke consecutively admitted to the ten hub hospitals in Lombardy, Italy, between March 8 and April 30, 2020, we compared clinical features of patients with confirmed infection and non-infected patients by logistic regression models and survival analysis. Then, we trained and tested a random forest (RF) binary classifier for the prediction of in-hospital death among patients with COVID-19.Results
Among 1013 patients, 160 (15.8%) had SARS-CoV-2 infection. Male
SUBMITTER: Pezzini A
PROVIDER: S-EPMC8142879 | biostudies-literature | 2022 Jan
REPOSITORIES: biostudies-literature