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Patients who have experienced a first cerebral ischemic event are at increased risk of recurrent stroke. There is strong evidence that low-level inflammation as measured by high sensitivity C-reactive protein (hs-CRP) is a predictor of further ischemic events. Other mechanisms implicated in the pathogenesis of stroke may play a role in determining the risk of secondary events, including oxidative stress and the adaptive response to it and activation of neuroprotective pathways by hypoxia, for instance through induction of erythropoietin (EPO). This study investigated the association of the levels of CRP, peroxiredoxin 1 (PRDX1, an indicator of the physiological response to oxidative stress) and EPO (a neuroprotective factor produced in response to hypoxia) with the risk of a second ischemic event. Eighty patients with a diagnosis of lacunar stroke or transient ischemic attack (TIA) were included in the study and a blood sample was collected within 14 days from the initial event. Hs-CRP, PRDX1, and EPO were measured by ELISA. Further ischemic events were recorded with a mean follow-up of 42 months (min 24, max 64). Multivariate analysis showed that only CRP was an independent predictor of further events with an observed risk (OR) of 1.14 (P = 0.034, 95% CI 1.01-1.29). No association was observed with the levels of PRDX1 or EPO. A receiver operating curve (ROC) determined a cut-off CRP level of 3.25 μg/ml, with a 46% sensitivity and 81% specificity. Low-level inflammation as detected by hs-CRP is an independent predictor of recurrent cerebrovascular ischemic events.
Pubmed ID: 32733466
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Software package used for interactive, or batched, statistical analysis in social science, health sciences and marketing. Software platform offers advanced statistical analysis, a library of machine-learning algorithms, text analysis, open-source extensibility, integration with big data and deployment into applications.Versions that were produced by SPSS Inc. before the IBM acquisition (Versions 18 and earlier) would be given origin or publisher of SPSS Inc. in Chicago.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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