Blood-based biomarkers are associated with different ischemic stroke mechanisms and enable rapid classification between cardioembolic and atherosclerosis etiologies

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Abstract

Stroke is a top leading cause of death, which occurs due to interference in the blood flow of the brain. Ischemic stroke (blockage) accounts for most cases (87%) and is further subtyped into cardioembolic, atherosclerosis, lacunar, other causes, and cryptogenic strokes. The main value of subtyping ischemic stroke patients is for a better therapeutic decision-making process. The current classification methods are complex and time-consuming (hours to days). Specific blood-based biomarker measurements have promising potential to improve ischemic stroke mechanism classification. Over the past decades, the hypothesis that different blood-based biomarkers are associated with different ischemic stroke mechanisms is increasingly investigated. This review presents the recent studies that investigated blood-based biomarker characteristics differentiation between ischemic stroke mechanisms. Different blood-based biomarkers are specifically discussed (b-type natriuretic peptide, d-dimer, c-reactive protein, tumor necrosis factor-α, interleukin-6, interleukin-1β, neutrophil–lymphocyte ratio, total cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein and apolipoprotein A), as well as the different cut-off values that may be useful in specific classifications for cardioembolic and atherosclerosis etiologies. Lastly, the structure of a point-of-care biosensor device is presented, as a measuring tool on-site. The information presented in this review will hopefully contribute to the major efforts to improve the care for stroke patients.

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Harpaz, D., Seet, R. C. S., Marks, R. S., & Tok, A. I. Y. (2020, October 9). Blood-based biomarkers are associated with different ischemic stroke mechanisms and enable rapid classification between cardioembolic and atherosclerosis etiologies. Diagnostics. Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/diagnostics10100804

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