Prognostic Influence of Increased C-Reactive Protein and Fibrinogen Levels in Ischemic Stroke
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The prognostic influences of fibrinogen and C-reactive protein (CRP) levels and their relations in ischemic stroke have not been well described. The aim of this study was to investigate and compare the 1-year prognostic influences of fibrinogen and CRP levels on outcome in ischemic stroke. METHODS: Fibrinogen and CRP were determined within 24 hours after stroke and related to 1-year outcome in 128 patients with first-ever ischemic stroke. The Kaplan-Meier technique was applied in survival analysis. Multiple logistic regression analysis was used to evaluate the associations between risk factors and outcome. RESULTS: The probabilities of death or new vascular event were 21.1%, 27.9%, and 51.7% (P:=0.0172, chi(2) for trend), respectively, in patients stratified by tertiles of fibrinogen (<3.78, 3.78 to 6.17, and >6.17 g/L). The probabilities of a primary end point were 12.1%, 29.7%, and 54.8% (P:=0.0004), respectively, after stratification of patient data by tertiles of CRP level (<5, 5 to 33, and >33 mg/L). In multiple logistic regression analysis, higher CRP levels (odds ratio, 2.39; 95% CI, 1.28 to 4.49; P:=0.0066) and stroke severity on the Canadian Neurological Stroke Scale (odds ratio, 2.37; 95% CI, 1.01 to 5.58; P:=0.0472) were independently associated with death or new vascular event. CONCLUSIONS: Increased levels of CRP are associated with a worse outcome in patients with ischemic stroke. The increased risk associated with elevated CRP levels is independent of the prognostic influence of fibrinogen.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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