Inflammatory and stress markers predicting pneumonia, outcome, and etiology in patients with stroke: Biomarkers for predicting pneumonia, functional outcome, and death after stroke

Benjamin Hotter, Sarah Hoffmann, Lena Ulm, Joan Montaner, Alejandro Bustamante, Christian Meisel, Andreas Meisel, Benjamin Hotter, Sarah Hoffmann, Lena Ulm, Joan Montaner, Alejandro Bustamante, Christian Meisel, Andreas Meisel

Abstract

Objective: Prognosis of stroke is negatively affected by complications, in particular stroke-associated pneumonia (SAP). We hypothesized that inflammatory and stress biomarkers predict SAP during hospitalization and outcome 3 months after stroke.

Methods: We pooled the clinical data of 2 acute stroke studies with identical assessment: the STRoke Adverse outcome is associated WIth NoSoKomial Infections (STRAWINSKI) and PREDICT studies. Measurement of biomarkers (ultrasensitive procalcitonin [PCTus]; midregional pro-adrenomedullin; midregional pro-atrial natriuretic peptide [MRproANP]; ultrasensitive copeptin [CPus]; C-terminal pro-endothelin) was performed from serum samples drawn on the first 4 days of hospital admission.

Results: The combined cohort consists of 573 cases with available backup samples to perform the analysis. SAP was associated with increased admission and maximum levels of all biomarkers. Furthermore, all biomarkers were associated with death and correlated with functional outcome 3 months after stroke. The multivariate logistic regression model retained ultrasensitive CPus and PCTus beyond clinical risk factors for predicting SAP, improving the receiver operating characteristic area under the curve (AUC) from 0.837 to 0.876. In contrast, the biomarkers did not improve the prediction of death and functional outcome in the multivariate model. Cardioembolic strokes were significantly associated with higher values of all biomarkers, whereas discrimination was best for MRproANP (AUC = 0.811 for maximum value).

Conclusions: The tested biomarkers are associated with SAP and poor functional outcome. However, these biomarkers only slightly improve prediction of SAP and do not improve long-term outcome prediction over clinical parameters. MRproANP showed the best discrimination for identifying cardioembolic stroke, warranting further studies to confirm our finding.

Clinical trial registration: clinicaltrials.gov NCT01264549 and NCT01079728.

Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

Figures

Figure 1. ROC for prediction of SAP…
Figure 1. ROC for prediction of SAP or death 90 days after stroke for admission (A and C) and maximum biomarker levels (B and D)
AUC = area under the curve; CTproET = C-terminal pro-endothelin; MRproADM = midregional pro-adrenomedullin; MRproANP = midregional pro-ANP; PCTus = ultrasensitive procalcitonin; SAP = stroke-associated pneumonia.
Figure 2. Admission and maximum MRproANP levels…
Figure 2. Admission and maximum MRproANP levels for patients without vs with cardioembolic stroke (A and B), as well as ROC for prediction of cardioembolic stroke for admission (C) and maximum biomarker levels (D)
AUC = area under the curve; CTproET = C-terminal pro-endothelin; MRproADM = midregional pro-adrenomedullin; MRproANP = midregional pro-ANP; PCTus = ultrasensitive procalcitonin.

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Source: PubMed

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