Biomarker Analysis from the Compass Claudication Study – Rivaroxaban for Intermittent Claudication
Bibliographic record
Abstract
IntroductionA prospective, randomized, multicenter study compared rivaroxaban 2.5 mg twice daily plus aspirin 100 mg once daily against aspirin 100 mg once daily alone in patients with peripheral artery disease and intermittent claudication. The study demonstrated that rivaroxaban plus aspirin improved total walking distance. A better comprehension of coagulation and inflammatory biomarkers could serve as a prognostic indicator and inform clinical decision-making.MethodsThis is a subsequent biomarker analysis, including 36 patients from both arms and plasma from healthy controls. We used human plasma for comparison purposes of the baseline biomarkers for normality testing. Plasma levels of biomarkers relating to coagulation activation (DD, vWF, thrombin generation potential (TGP), fibrinolysis (PAI-1, TAFI) and inflammation (CRP) were assessed at baseline (day 0) and measured after 24 weeks.ResultsSamples from 16 patients allocated to the aspirin plus rivaroxaban group and 20 from the aspirin alone group were collected. No significant differences were observed in biomarkers between patients receiving rivaroxaban plus aspirin and those receiving aspirin alone.ConclusionThere were no differences in coagulation or inflammatory biomarkers in patients with intermittent claudication treated with either rivaroxaban plus aspirin or aspirin alone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".