Blood Biomarkers to Predict Long-Term Mortality after Ischemic Stroke.

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 < 0.001). Moreover, endostatin > 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.

Correlation of blood biomarkers with early-onset seizures after an acute stroke event.

INTRODUCTION: Blood biomarkers have not been widely studied in stroke-related seizures. In this study, we aimed to describe clinical factors and biomarkers present during acute stroke and to analyze their association with early-onset seizures. METHODS: We retrospectively evaluated a panel of 14 blood biomarkers in 1115 patients with ischemic and hemorrhagic stroke. Biomarkers were normalized and standardized using Z scores. We also recorded stroke and epilepsy-related variables, including stroke severity (National Institute of Health Stroke Scale [NIHSS] scores), type, and causes, time from onset of stroke to occurrence of early seizures, and type of seizure. Adjusted logistic regression models were built to identify clinical variables and biomarkers independently associated with early seizures. RESULTS: Mean ±â€¯standard deviation (SD) age was 72.3 ±â€¯13.2 years, and 56.8% of the patients were men. Thirty-eight patients (3.9%) developed early seizures with a median time to onset of 1 day (interquartile range (IQR), 0-4). A higher NIHSS score (odds ratio [OR] = 1.046; 95% confidence interval (CI): 1.001-1.094; p = 0.044) and hemorrhagic stroke (OR = 2.133; 95% CI: 1.010-4.504; p = 0.047) were independently associated with a greater risk of early seizures. Independent blood biomarkers predictive of early seizures were lower levels of tumor necrosis factor receptor 1 (TNF-R1) (<0.013) (p = 0.006; OR = 3.334; 95% CI: 1.414-7.864) and higher levels of neural cell adhesion molecule (NCAM) (>0.326) (p = 0.009; OR = 2.625; 95% CI: 1.271-5.420). The predictive power of the regression model was greater when clinical variables were combined with blood biomarkers (73.5%; 95% CI: 65.1%-81.9%) than when used alone (64%; 95% CI: 55%-72.9%). CONCLUSION: Higher NCAM and lower TNF-R1 levels may help predict the occurrence of early seizures. The combined use of these biomarkers and clinical variables could be useful for identifying patients at risk of seizures. This article is part of the Special Issue "Seizures & Stroke".