The Role of D-Dimer, Fibrinogen and C-Reactive Protein as Plasma Biomarkers in Acute Ischemic Stroke
Why this work is in the frame
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Bibliographic record
Abstract
Background: Previous studies on pathophysiology suggest a role of inflammation in atherothrombotic stroke and intracardiac thrombosis in cardioembolic stroke. We explored the magnitude of D-dimer, fibrinogen and C-reactive protein (CRP) as biomarkers in acute ischemic cerebral stroke and their relation to ischemic stroke subtypes and their impact on stroke outcome after 30 days. Methods: The study was performed on 100 patients, admitted to Neurology Department, Menoufiya University, within 24 hours of acute ischemic stroke. Patients were subjected to clinical data collection, general and neurological examination, laboratory assessment (routine and biomarkers), brain computerized tomography (CT), magnetic resonance imaging (MRI), MRA, carotid and vertebrobasilar duplex and cardiac assessment. The patients were classified according to Trial of ORG 10172 in acute stroke treatment (TOAST) classification. Severity and disability were assessed by Scandinavian stroke scale and modified Rankin scale at admission and at 30 days. Results: We found that D-dimer, fibrinogen and CRP were significantly higher in patients than in controls (P < 0.001). D-dimer and fibrinogen were higher in cardioembolic stroke while CRP was higher in atherothrombotic subtype. The biomarkers were correlated significantly with the severity and disability of stroke at onset and 30 days. Conclusions: These three biomarkers in acute ischemic stroke can be considered as non-invasive tools which add important information regarding etiology and outcome. J Neurol Res. 2015;5(6):277-282 doi: http://dx.doi.org/10.14740/jnr362w
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it