4.6 Article

Immune-inflammatory, coagulation, adhesion, and imaging biomarkers combined in machine learning models improve the prediction of death 1 year after ischemic stroke

期刊

CLINICAL AND EXPERIMENTAL MEDICINE
卷 22, 期 1, 页码 111-123

出版社

SPRINGER-VERLAG ITALIA SRL
DOI: 10.1007/s10238-021-00732-w

关键词

Stroke; NIHSS; Mortality; Inflammation; Coagulation; Adhesion molecules; Biomarkers

资金

  1. Fundacao Araucaria, Parana State, Brazil [001/2017, 09/2016, 47.396]
  2. Coordination for the Improvement of Higher Level of Education Personnel (CAPES) of Brazilian Ministry of Education [001]
  3. Institutional Program for Scientific Initiation Scholarship (PIBIC) of the National Council for Scientific and Technological Development (CNPq) of Brazil

向作者/读者索取更多资源

This study evaluated the prognostic validity of a combination of clinical, imaging, and laboratory biomarkers in predicting 1-year mortality of IS, finding that non-survivors showed significant differences in multiple indicators including IS severity, carotid intima-media thickness, coagulation factors, and inflammatory factors.
Some clinical, imaging, and laboratory biomarkers have been identified as predictors of prognosis of acute ischemic stroke (IS). The aim of this study was to evaluate the prognostic validity of a combination of clinical, imaging, and laboratory biomarkers in predicting 1-year mortality of IS. We evaluated 103 patients with IS within 24 h of their hospital admission and assessed demographic data, IS severity using the National Institutes of Health Stroke Scale (NIHSS), carotid intima-media thickness (cIMT), and degree of stenosis, as well as laboratory variables including immune-inflammatory, coagulation, and endothelial dysfunction biomarkers. The IS patients were categorized as survivors and non-survivors 1 year after admission. Non-survivors showed higher NIHSS and cIMT values, lower antithrombin, Protein C, platelet counts, and albumin, and higher Factor VIII, von Willebrand Factor (vWF), white blood cells, tumor necrosis factor (TNF)-alpha, interleukin (IL)-10, high-sensitivity C-reactive protein (hsCRP), and vascular cellular adhesion molecule 1 (VCAM-1) than survivors. Neural network models separated non-survivors from survivors using NIHSS, cIMT, age, IL-6, TNF-alpha, hsCRP, Protein C, Protein S, vWF, and platelet endothelial cell adhesion molecule 1 (PECAM-1) with an area under the receiving operating characteristics curve (AUC/ROC) of 0.975, cross-validated accuracy of 93.3%, sensitivity of 100% and specificity of 85.7%. In conclusion, imaging, immune-inflammatory, and coagulation biomarkers add predictive information to the NIHSS clinical score and these biomarkers in combination may act as predictors of 1-year mortality after IS. An early prediction of IS outcome is important for personalized therapeutic strategies that may improve the outcome of IS.

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