StrokeCog-15 Is an Efficient Neuropsychological Battery to Screen for Cognitive Impairment in Chronic Stroke.

Background: Poststroke cognitive impairment can significantly impact functional outcomes and quality of life. While comprehensive neuropsychological evaluations are valuable in characterizing this impairment, their time-intensive nature is not always feasible. Thus, we set out to develop a brief cognitive battery that is sensitive to poststroke cognitive impairment.

Machine learning models of plasma proteomic data predict mood in chronic stroke and tie it to aberrant peripheral immune responses.

Post-stroke depression is common, long-lasting and associated with severe morbidity and death, but mechanisms are not well-understood. We used a broad proteomics panel and developed a machine learning algorithm to determine whether plasma protein data can predict mood in people with chronic stroke, and to identify proteins and pathways associated with mood. We used Olink to measure 1,196 plasma proteins in 85 participants aged 25 and older who were between 5 months and 9 years after ischemic stroke.

Monocyte chemoattractant protein-1 predicts outcome and vasospasm following aneurysmal subarachnoid hemorrhage.

Object: Despite efforts to elucidate both the molecular mechanism and the clinical predictors of vasospasm after aneurysmal subarachnoid hemorrhage (ASAH), its pathogenesis remains unclear. Monocyte chemoattractant protein-1 (MCP-1) is a chemokine that has been firmly implicated in the pathophysiology of vasospasm and in neural tissue injury following focal ischemia in both animal models and human studies. The authors hypothesized that MCP-1 would be found in increased concentrations in the blood and cerebrospinal fluid (CSF) of patients with ASAH and would correlate with both outcome and the occurrence of vasospasm.