P4204Applicability of the COMPASS trial in a Danish all-comers coronary angiography cohort: an analysis of the Western Denmark heart registry
Bibliographic record
Abstract
Background: In the COMPASS trial, combined aspirin and rivaroxaban treatment reduced ischemic events in patients with stable coronary artery disease or peripheral artery disease. Purpose: To examine the external applicability of the COMPASS trial by estimating the proportion of COMPASS-eligible patients among patients undergoing coronary angiography, and to compare outcome rates of COMPASS-eligible and non-eligible patients. Methods: We applied the COMPASS inclusion and exclusion criteria with few modifications to patients undergoing coronary angiography in Western Denmark between 2004–2011. We used the COMPASS primary (composite of cardiovascular death, stroke, or myocardial infarction) and secondary outcomes. We computed event rates as well as crude and adjusted incidence rate ratios among COMPASS-eligible and non-eligible patients. Results: A total of 80,071 patients underwent coronary angiography, of which 31,381 met the exclusion criteria leaving a final study population of 48,690 patients. Among these, 13,063 (26.8%) patients were COMPASS-eligible, while the remaining were COMPASS non-eligible as they did not meet inclusion criteria. The primary and secondary outcome rates were substantially higher among COMPASS-eligible than non-eligible patients (Table 1).
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".