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The aim was to investigate the association between plasma levels of cellular adhesion molecules (CAMs) and risk factors, subtypes, severity and short-term mortality of acute ischemic stroke (IS), and to identify a panel of biomarkers to predict short-term mortality after IS. The prospective study evaluated 132 IS patients within 24 h of their hospital admission. The baseline IS severity was assessed using the National Institutes Health Stroke Scale (NIHSS) and categorized as mild (NIHSS < 5), moderate (NIHSS 5-14) and severe (NIHSS ≥ 15). After three-month follow-up, the disability was assessed using the modified Rankin Scale (mRS); moreover, the patients were classified as survivors and non-survivors. Baseline inflammatory and anti-inflammatory cytokines and soluble CAMs were evaluated. Twenty-nine (21.9%) IS patients were non-survivors and showed higher NIHSS and soluble vascular cellular adhesion molecule 1 (sVCAM-1) than the survivors. The sVCAM-1 levels positively correlated with age, homocysteine, severity, and disability. The model #3 combining sVCAM-1 and NIHSS showed better results to predict short-term mortality with an area under the curve receiving operating characteristics (AUC/ROC) of 0.8841 [95% confidence interval (CI): 0.795-0.941] than the models with sVCAM-1 and NIHSS alone, with positive predictive value of 68.0%, negative predictive value of 91.3%, and accuracy of 86.5%. In conclusion, the combined model with baseline severity of IS and sVCAM-1 levels can early predict the prognosis of IS patients who may benefit with therapeutic measures of personalized therapy that taken into account these biomarkers. Moreover, this result suggests that VCAM-1 might be a potential target for the therapeutic strategies in IS., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

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)-α, 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-α, 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., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Acute ischemic stroke (IS) is one of the leading causes of morbidity, functional disability and mortality worldwide. The objective was to evaluate IS risk factors and imaging variables as predictors of short-term disability and mortality in IS. Consecutive 106 IS patients were enrolled. We examined the accuracy of IS severity using the National Institutes of Health Stroke Scale (NIHSS), carotid intima-media thickness (cIMT) and carotid stenosis (both assessed using ultrasonography with doppler) predicting IS outcome assessed with the modified Rankin scale (mRS) three months after hospital admission. Poor prognosis (mRS ≥ 3) at three months was predicted by carotid stenosis (≥ 50%), type 2 diabetes mellitus and NIHSS with an accuracy of 85.2% (sensitivity: 90.2%; specificity: 81.8%). The mRS score at three months was strongly predicted by NIHSS (β = 0.709, p < 0.001). Short-term mortality was strongly predicted using a neural network model with cIMT (≥ 1.0 mm versus < 1.0 mm), NIHSS and age, yielding an area under the receiving operator characteristic curve of 0.977 and an accuracy of 94.7% (sensitivity: 100.0%; specificity: 90.9%). High NIHSS (≥ 15) and cIMT (≥ 1.0 mm) increased the probability of dying with hazard ratios of 7.62 and 3.23, respectively. Baseline NIHSS was significantly predicted by the combined effects of age, large artery atherosclerosis stroke, sex, cIMT, body mass index, and smoking. In conclusion, high values of cIMT and NIHSS at admission strongly predict short-term functional impairment as well as mortality three months after IS, underscoring the importance of those measurements to predict clinical IS outcome., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The aim of the study was to define new immune-inflammatory, oxidative stress and biochemical biomarkers, which predict mortality within a period of 3 months after acute ischemic stroke (AIS). We recruited 176 healthy volunteers and 145 AIS patients, categorized as AIS survivors and non-survivors, and measured interleukin (IL)-6, high sensitivity C-reactive protein (hsCRP), ferritin, iron, total serum protein (TSP), erythrocyte sedimentation rate (ESR), white blood cells (WBC), 25 hydroxyvitamin D [25(OH)D], lipid hydroperoxides (CL-LOOH), insulin, glucose and high-density lipoprotein (HDL)-cholesterol. In patients, these biomarkers were measured within 24 h after AIS onset. We also computed two composite scores reflecting inflammatory indices, namely INFLAM index1 (sum of z scores of hsCRP+IL-6 + ferritin+ESR + WBC) and INFLAM index2 (z INFLAM index1 - z 25(OH)D - z iron + z TSP). Three months after AIS, non-survivors (n = 54) showed higher baseline levels of IL-6, hsCRP, ferritin and glucose and lower levels of HDL-cholesterol and 25(OH)D than survivors (n = 91). Non-survivors showed higher baseline ESR and lowered TSP than controls, while survivors occupied an intermediate position. Death after AIS was best predicted by increased IL-6, glucose, ferritin and CL-LOOH and lowered 25(OH)D levels. The area under the receiver operating curves computed on the INFLAM index1 and 2 scores were 0.851 and 0.870, respectively. In conclusion, activation of peripheral immune-inflammatory, oxidative and biochemical pathways is critically associated with mortality after AIS. Our results may contribute to identify new biomarker sets, which may predict post-stroke death, as well as suggest that IL-6 trans-signaling coupled with redox imbalances may be possible new targets in the prevention of short-term outcome AIS death.