Simple SummaryIschemic stroke represents one of the leading causes of death and disability worldwide. The identification of new prognostic factors and biomarkers for patients’ risk stratification could reduce the burden of disease. In this perspective, given the possibility of non-invasively collecting the extracellular vesicles and characterizing them on the basis of parental surface markers, we verified whether extracellular vesicles could represent an interesting prognostic biomarker in ischemic stroke. We found that specific extracellular vesicle subtypes are associated with stroke severity and both short- and long-term outcomes.The possibility of characterizing the extracellular vesicles (EVs) based on parental cell surface markers and their content makes them a new attractive prognostic biomarker. Thus, our study aims to verify the role of EVs as relevant prognostic factors for acute and mid-term outcomes in ischemic stroke. Forty-seven patients with acute ischemic stroke were evaluated at admission (T0), immediately after recanalization treatment or after 2 h in non-treated patients (T1) and after one week (Tw) using the National Institutes of Health Stroke Scale (NIHSS), and after 3 months using the Modified Rankin Scale (mRS). Total count and characterization of EVs were assessed by Nanosight analysis and flow cytometry. The relationships between stroke outcomes and EV count were assessed through multivariable negative binomial regression models. We found that the amount of platelet-derived EVs at admission was positively associated with the severity of ischemic stroke at the onset as well as with the severity of mid-term outcome. Moreover, our study revealed that T-cell-derived EVs at admission were positively related to both early and mid-term ischemic stroke outcomes. Finally, T-cell-derived EVs at T1 were positively related to mid-term ischemic stroke outcome. The present study suggests that specific EV subtypes are associated with stroke severity and both short- and long-term outcomes. EVs could represent a valid tool to improve risk stratification in patients with ischemic stroke and post-recanalization treatment monitoring.