Trade-off of myocardial infarction vs. bleeding types on mortality after acute coronary syndrome: lessons from the Thrombin Receptor Antagonist for Clinical Event Reduction in Acute Coronary Syndrome (TRACER) randomized trial
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: Dual antiplatelet therapy reduces non-fatal ischaemic events after acute coronary syndrome (ACS) but increases bleeding to a similar extent. We sought to determine the prognostic impact of myocardial infarction (MI) vs. bleeding during an extended follow-up period to gain insight into the trade-off between efficacy and safety among patients after ACS. METHODS AND RESULTS: In 12 944 patients with non-ST-segment elevation ACS from the Thrombin Receptor Antagonist for Clinical Event Reduction in Acute Coronary Syndrome (TRACER) trial, we investigated the relative impact of MI and bleeding occurring >30 days post-ACS and subsequent all-cause mortality. Bleeding was graded according to Bleeding Academic Research Consortium (BARC) criteria. MI was associated with a five-fold increase in mortality. BARC type 2 and 3, but not type 1, bleeding had a significant impact on mortality. MI was associated with a greater risk of mortality compared with BARC 2 [relative risk (RR) 3.5; 95% confidence interval (CI) 2.08-4.77; P < 0.001] and BARC 3a bleeding (RR 2.23; 95% CI 1.36-3.64; P = 0.001), and a risk similar to BARC 3b bleeding (RR 1.37; 95% CI 0.81-2.30; P = 0.242). Risk of death after MI was significantly lower than after BARC 3c bleeding (RR 0.22; 95% CI 0.13-0.36; P < 0.001). MI and bleeding had similar time-associations with mortality, which remained significant for several months, still being higher early after the event. CONCLUSION: In patients treated with antiplatelet therapy after ACS, both MI and bleeding significantly impacted mortality with similar time-dependency. Although BARC 2 and 3a bleeding were less prognostic for death than MI, the risk of mortality was equivalent between BARC 3b bleeding and MI, and was higher following BARC 3c bleeding.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it