The use of blood biomarkers to predict poor outcome after acute transient ischemic attack or ischemic stroke
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Published on: September 22, 2020
William Whiteley1, Joanna Wardlaw, Martin Dennis
1Division of Clinical Neurosciences, General Hospital, University of Edinburgh, Edinburgh, UK. william.whiteley@ed.ac.uk
Background And Purpose:
The prediction of death or disability ("poor outcome") after stroke by validated clinical models might be improved by the addition of blood biomarker measurements. We investigated whether such measurements improved the classification of patients into 4 categories of predicted risk of poor outcome: very high, intermediate high, intermediate low, and very low.
Methods:
We prospectively recruited symptomatic patients within 24 hours of ischemic cerebrovascular events. We measured clinical prognostic variables in each patient. We drew blood soon after admission and measured markers of inflammation, thrombosis, cardiac strain, and cerebral damage. We assessed poor outcome at 3 months with the modified Rankin Scale and recovery of symptoms at 24 hours. We measured the association between blood marker levels and poor outcome after adjustment for stroke severity and age with multivariate logistic regression. Where these associations were statistically significant, we calculated the net reclassification index.
Results:
We recruited 270 patients with acute ischemic cerebrovascular events. At 3 months, 112 patients had a poor outcome. After adjustment for stroke severity and age, only interleukin-6 and N-terminal pro-brain natriuretic peptide were significantly associated with poor outcome. The addition of either interleukin-6 or N-terminal pro-brain natriuretic peptide to National Institutes of Health Stroke Scale and age did not improve the prediction of a poor outcome.
Conclusions:
Neither interleukin-6 nor N-terminal pro-brain natriuretic peptide had sufficient predictive power to be of clinical use to predict poor outcome after stroke. The search for better markers to improve the classification of patients across clinically relevant boundaries of predicted probabilities of outcome events needs to continue.
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