Platelet Quiescence in Patients With Acute Coronary Syndrome Undergoing Coronary Artery Bypass Graft Surgery
Bibliographic record
Abstract
Background The optimal antiplatelet strategy for patients with acute coronary syndromes who require coronary artery bypass surgery remains unclear. While a more potent antiplatelet regimen will predispose to perioperative bleeding, it is hypothesized that through “platelet quiescence,” ischemic protection conferred by such therapy may provide a net clinical benefit. Methods and Results We compared patients undergoing coronary artery bypass surgery who were treated with a more potent antiplatelet inhibition strategy with those with a less potent inhibition through a meta‐analysis. The primary outcome was all‐cause mortality after bypass surgery. The analysis identified 4 studies in which the antiplatelet regimen was randomized and 6 studies that were nonrandomized. Combining all studies, there was an overall higher mortality with weaker strategies compared with more potent strategies (odds ratio, 1.38; 95% CI, 1.03–1.85; P =0.03). Conclusions Our findings support the concept of platelet quiescence, in reducing mortality for patients with acute coronary syndrome requiring coronary artery bypass surgery. This suggests the routine up‐front use of potent antiplatelet regimens in acute coronary syndrome, irrespective of likelihood of coronary artery bypass graft.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".