Predictive and diagnosis models of stroke from hemodynamic signal monitoring.

This work presents a novel and promising approach to the clinical management of acute stroke. Using machine learning techniques, our research has succeeded in developing accurate diagnosis and prediction real-time models from hemodynamic data. These models are able to diagnose stroke subtype with 30 min of monitoring, to predict the exitus during the first 3 h of monitoring, and to predict the stroke recurrence in just 15 min of monitoring.

Tocilizumab-Associated Reversible Cerebral Vasoconstriction: A Case Report.

Objectives: To report a case of reversible cerebral vasoconstriction syndrome (RCVS) possibly precipitated by tocilizumab.

Background: Immunosuppressant drugs are a rare cause of reversible cerebral vasoconstriction, a syndrome characterized by segmental vasospasm. However, although it is considered a reversible process that resolves within 3 months, the cerebral vasoconstriction over time may lead to severe complications such as strokes.

Predictors of unknown cancer in patients with ischemic stroke.

Stroke is the second most frequent neurologic finding in postmortem studies of cancer patients. It has also been described as the first expression of an occult cancer. We have studied patients diagnosed with cancer after an ischemic stroke (IS) and we analyze differences with non-tumor patients.