Biomarkers to improve functional outcome prediction after ischemic stroke: Results from the SICFAIL, STRAWINSKI, and PREDICT studies

Author:

Montellano Felipe A123ORCID,Rücker Viktoria1,Ungethüm Kathrin14,Penalba Anna5,Hotter Benjamin678ORCID,Giralt Marina9,Wiedmann Silke110,Mackenrodt Daniel12,Morbach Caroline1112,Frantz Stefan11,Störk Stefan1112,Whiteley William N13,Kleinschnitz Christoph14,Meisel Andreas678,Montaner Joan51516ORCID,Haeusler Karl Georg2,Heuschmann Peter U1417

Affiliation:

1. Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-Universität (JMU) Würzburg, Würzburg, Germany

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

3. Interdisciplinary Center for Clinical Research, University Hospital Würzburg, Würzburg, Germany

4. Institute of Medical Data Science, University Hospital Würzburg, Würzburg, Germany

5. Neurovascular Research Laboratory, Vall d’Hebron Institute of Research, Universitat Autònoma de Barcelona, Barcelona, Spain

6. Department of Neurology and Experimental Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany

7. Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany

8. NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Berlin, Germany

9. Department of Biochemistry, Vall d’Hebron University Hospital, Barcelona, Spain

10. Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany

11. Department Clinical Research & Epidemiology, Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany

12. Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany

13. Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK

14. Department of Neurology and Center for Translational Neuroscience and Behavioural Science (C-TNBS), University Hospital Essen, Essen, Germany

15. Stroke Research Program, Instituto de Biomedicina de Sevilla/Hospital Universitario Virgen del Rocío/Consejo Superior de Investigaciones Científicas/University of Seville, Seville, Spain

16. Department of Neurology, Hospital Universitario Virgen Macarena, Seville, Spain

17. Clinical Trial Center Würzburg, University Hospital Würzburg, Würzburg, Germany

Abstract

Background and aims: Acute ischemic stroke (AIS) outcome prognostication remains challenging despite available prognostic models. We investigated whether a biomarker panel improves the predictive performance of established prognostic scores. Methods: We investigated the improvement in discrimination, calibration, and overall performance by adding five biomarkers (procalcitonin, copeptin, cortisol, mid-regional pro-atrial natriuretic peptide (MR-proANP), and N-terminal pro-B-type natriuretic peptide (NT-proBNP)) to the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) and age/NIHSS scores using data from two prospective cohort studies (SICFAIL, PREDICT) and one clinical trial (STRAWINSKI). Poor outcome was defined as mRS > 2 at 12 (SICFAIL, derivation dataset) or 3 months (PREDICT/STRAWINSKI, pooled external validation dataset). Results: Among 412 SICFAIL participants (median age 70 years, quartiles 59–78; 63% male; median NIHSS score 3, quartiles 1–5), 29% had a poor outcome. Area under the curve of the ASTRAL and age/NIHSS were 0.76 (95% CI 0.71–0.81) and 0.77 (95% CI 0.73–0.82), respectively. Copeptin (0.79, 95% CI 0.74–0.84), NT-proBNP (0.80, 95% CI 0.76–0.84), and MR-proANP (0.79, 95% CI 0.75–0.84) significantly improved ASTRAL score’s discrimination, calibration, and overall performance. Copeptin improved age/NIHSS model’s discrimination, copeptin, MR-proANP, and NT-proBNP improved its calibration and overall performance. In the validation dataset (450 patients, median age 73 years, quartiles 66–81; 54% men; median NIHSS score 8, quartiles 3–14), copeptin was independently associated with various definitions of poor outcome and also mortality. Copeptin did not increase model’s discrimination but it did improve calibration and overall model performance. Discussion: Copeptin, NT-proBNP, and MR-proANP improved modest but consistently the predictive performance of established prognostic scores in patients with mild AIS. Copeptin was most consistently associated with poor outcome in patients with moderate to severe AIS, although its added prognostic value was less obvious.

Funder

Interdisziplinäres Zentrum für Klinische Forschung, Universitätsklinikum Würzburg

Bundesministerium für Bildung und Forschung

Deutsche Forschungsgemeinschaft

Publisher

SAGE Publications

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