Neutrophil–lymphocyte ratio in acute ischemic stroke: Immunopathology, management, and prognosis.
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| Title: | Neutrophil–lymphocyte ratio in acute ischemic stroke: Immunopathology, management, and prognosis. |
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| Authors: | Sharma, Divyansh (AUTHOR), Spring, Kevin J. (AUTHOR), Bhaskar, Sonu Menachem Maimonides (AUTHOR) |
| Source: | Acta Neurologica Scandinavica. Nov2021, Vol. 144 Issue 5, p486-499. 14p. |
| Subjects: | Ischemic stroke, Neutrophil lymphocyte ratio, Stroke, Prognosis, Immunopathology, Sensitivity & specificity (Statistics) |
| Abstract: | There is an ongoing need for accurate prognostic biomarkers in the milieu of acute ischemic stroke (AIS) receiving reperfusion therapy. Neutrophil–lymphocyte ratio (NLR) has been implicated in emergency medicine and acute stroke setting as an important biomarker in the prognosis of patients. However, there are ongoing questions around its accuracy and translation into clinical practice given suboptimal sensitivity and specificity results, as well as varying thresholds and lack of clarity around which NLR time points are most clinically indicative. This article provides a comprehensive overview of the role of NLR in AIS patients receiving reperfusion therapy and perspectives on areas of future research. NLR may be an important biomarker in risk stratifying patients in AIS to identify and select those who are more likely to benefit from reperfusion therapy. Appropriate clinical decision‐making tools and models are required to harness the predictive value of NLR, which could be useful in identifying and monitoring high‐risk patients to guide early treatment and achieve improved outcomes. Our understanding of the role of NLR in the immunopathogenesis of AIS is also suboptimal, which hinders the ability to translate this into clinical practice. [ABSTRACT FROM AUTHOR] |
| Copyright of Acta Neurologica Scandinavica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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