Alirocumab and Cardiovascular Outcomes in Patients With Previous Myocardial Infarction: Prespecified Subanalysis From ODYSSEY OUTCOMES
Bibliographic record
Abstract
Background After acute coronary syndrome (ACS), patients with a previous myocardial infarction (MI) may be at particularly high risk for major adverse cardiovascular events (MACE) and death. We studied the effects of the PCSK9 inhibitor alirocumab in patients with recent ACS according to previous history of MI. Methods The ODYSSEY OUTCOMES trial compared alirocumab with placebo, beginning 1 to 12 months after ACS with median 2.8-year follow-up. The primary MACE outcome comprised death from coronary heart disease, nonfatal MI, fatal or nonfatal ischemic stroke, and hospitalization for unstable angina. Of 18,924 patients, 3633 (19.2%) had previous MI. Results Patients with previous MI were older, more likely male, with more cardiovascular risk factors and previous events. With placebo, 4-year risks of MACE and death were higher among those with vs without previous MI (20.5% vs 8.9%, P < 0.001; 7.4% vs 3.4%, P < 0.001, respectively). Alirocumab reduced the risk of events regardless of the presence or absence of a history of MI (MACE, adjusted hazard ratio [aHR] 0.90, 95% confidence interval [CI], 0.78-1.05 vs 0.82, 0.73-0.92; P interaction = 0.34; death, aHR 0.84; 95% CI, 0.64-1.08 vs 0.87, 0.72-1.05; P interaction = 0.81). Estimated absolute risk reductions with alirocumab were numerically greater with vs without previous MI (MACE, 1.91% vs 1.42%; death, 1.35% vs 0.41%). Conclusions A previous history of MI places patients with recent ACS at high risk for recurrent MACE and death. Alirocumab reduced the relative risks of these events consistently in patients with or without previous MI but with numerically greater absolute benefit in the former subgroup. ( ODYSSEY OUTCOMES: NCT01663402)
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".