Life (Feb 2021)

Blood Biomarkers to Predict Long-Term Mortality after Ischemic Stroke

  • Laura Ramiro,
  • Laura Abraira,
  • Manuel Quintana,
  • Paula García-Rodríguez,
  • Estevo Santamarina,
  • Jose Álvarez-Sabín,
  • Josep Zaragoza,
  • María Hernández-Pérez,
  • Xavier Ustrell,
  • Blanca Lara,
  • Mikel Terceño,
  • Alejandro Bustamante,
  • Joan Montaner

DOI
https://doi.org/10.3390/life11020135
Journal volume & issue
Vol. 11, no. 2
p. 135

Abstract

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Stroke is a major cause of disability and death globally, and prediction of mortality represents a crucial challenge. We aimed to identify blood biomarkers measured during acute ischemic stroke that could predict long-term mortality. Nine hundred and forty-one ischemic stroke patients were prospectively recruited in the Stroke-Chip study. Post-stroke mortality was evaluated during a median 4.8-year follow-up. A 14-biomarker panel was analyzed by immunoassays in blood samples obtained at hospital admission. Biomarkers were normalized and standardized using Z-scores. Multiple Cox regression models were used to identify clinical variables and biomarkers independently associated with long-term mortality and mortality due to stroke. In the multivariate analysis, the independent predictors of long-term mortality were age, female sex, hypertension, glycemia, and baseline National Institutes of Health Stroke Scale (NIHSS) score. Independent blood biomarkers predictive of long-term mortality were endostatin > quartile 2, tumor necrosis factor receptor-1 (TNF-R1) > quartile 2, and interleukin (IL)-6 > quartile 2. The risk of mortality when these three biomarkers were combined increased up to 69%. The addition of the biomarkers to clinical predictors improved the discrimination (integrative discriminative improvement (IDI) 0.022 (0.007–0.048), p quartile 3 was an independent predictor of mortality due to stroke. Altogether, endostatin, TNF-R1, and IL-6 circulating levels may aid in long-term mortality prediction after stroke.

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