Dual antiplatelet therapy (PEGASUS) vs. dual pathway (COMPASS): a head-to-head in vitro comparison
Bibliographic record
Abstract
Dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 inhibitor is prescribed for 1-year after myocardial infarction. Two clinical strategies are considered at 1-year: continuation of DAPT or “Dual Pathway” (DP), using aspirin and rivaroxaban. No head-to-head comparative studies exist. In our in-vitro study, 24 samples of donor blood were treated with clinically proven concentrations of 5 antithrombotic regimens: aspirin, ticagrelor, rivaroxaban, DAPT, and DP. Thrombosis was analyzed using the Total Thrombus Analysis System (T-TAS) to measure both antiplatelet and anticoagulant effects. Flow cytometry was performed to quantify platelet activation. DAPT was the most potent antiplatelet regimen, delaying thrombus onset (p < .0001) and reducing thrombogenicity (p < .0001), relative to control. DP did not delay thrombus formation relative to aspirin alone (p = .69). DP was the most potent anticoagulant regimen, delaying thrombus onset (p < .0001) and reducing thrombogenicity (p < .0001), relative to control. DP showed synergistic antithrombotic effects by delaying thrombus onset (p < .0001) and reducing thrombogenicity (p = .0003), relative to rivaroxaban alone. Flow cytometry showed only DAPT (p = .0023) reduced platelet activation. DP treatment demonstrated synergistic antithrombotic effects over rivaroxaban alone, but no additional antiplatelet synergism over 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".