A novel biomarker panel index improves risk stratification after ischemic stroke

Author:

Bicvic Antonela12ORCID,Scherrer Natalie1,Schweizer Juliane1,Fluri Felix34,Christ-Crain Mirjam5,De Marchis Gian Marco6ORCID,Luft Andreas R1,Katan Mira1

Affiliation:

1. Department of Neurology, University Hospital of Zurich, Zurich, Switzerland

2. Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

3. Department of Neurology, SRO Gesundheitszentrum, Bad Wimpfen, Germany

4. Department of Neurology, University Hospital Würzburg, Würzburg, Germany

5. Department of Endocrinology, University Hospital of Basel, Basel, Switzerland

6. Department of Neurology, University Hospital of Basel and University of Basel, Basel, Switzerland

Abstract

Background: We investigated 92 blood biomarkers implicated in the pathophysiological pathways of ischemic injury, inflammation, hemostasis, and regulation of vascular resistance to predict post-stroke mortality. Aim: Based on the most promising markers, we aimed to create a novel Biomarker Panel Index (BPI) for risk stratification. Methods: In this prospective study, we measured 92 biomarkers in 320 stroke patients. The primary outcome measure was mortality within 90 days. We estimated the association of each biomarker using logistic regression adjusting for multiple testing. The most significant 16 biomarkers were used to create the BPI. We fitted regression models to estimate the association and the discriminatory accuracy of the BPI with mortality and stroke etiology. Results: Adjusted for demographic and vascular covariates, the BPI remained independently associated with mortality (odds ratio (OR) 1.68, 95% confidence interval (CI): 1.29–2.18) and cardioembolic stroke etiology (OR 1.38, 95% CI: 1.10–1.74), and improved the discriminatory accuracy to predict mortality (area under the receiver operating characteristic curve (AUC) 0.93, 95% CI: 0.89–0.96) and cardioembolic stroke etiology (AUC 0.70, 95% CI: 0.64–0.77) as compared to the best clinical prediction models alone (AUC 0.89, 95% CI: 0.84–0.94 and AUC 0.66, 95% CI: 0.60-0.73, respectively). Conclusions: We identified a novel BPI improving risk stratification for mortality after ischemic stroke beyond established demographic and vascular risk factors. Furthermore, the BPI is associated with underlying cardioembolic stroke etiology. These results need external validation.

Publisher

SAGE Publications

Subject

Cardiology and Cardiovascular Medicine,Neurology (clinical)

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