Alirocumab and cardiovascular outcomes according to sex and lipoprotein(a) after acute coronary syndrome: a report from the ODYSSEY OUTCOMES study
Bibliographic record
Abstract
Background The ODYSSEY OUTCOMES trial (NCT01663402) compared the effects of the proprotein convertase subtilisin/kexin type 9 inhibitor alirocumab with placebo on major adverse cardiovascular events (MACE) in patients with recent acute coronary syndrome (ACS). Objective We assessed efficacy and safety of alirocumab versus placebo according to sex and lipoprotein(a) level. Methods This prespecified analysis compared the effects of alirocumab versus placebo on lipoproteins, MACE (coronary heart disease death, non-fatal myocardial infarction, fatal/non-fatal ischemic stroke, unstable angina requiring hospitalization), death, total cardiovascular events, and adverse events in 4762 women and 14,162 men followed for a median of 2.8 years. In post-hoc analysis, we evaluated total cardiovascular events according to sex, baseline lipoprotein(a), and treatment. Results Women were older, had higher baseline LDL-C levels (89.6 vs 85.3 mg/dL) and lipoprotein(a) (28.0 vs 19.3 mg/dL) and had more co-morbidities than men. At 4 months, alirocumab lowered LDL-C by 49.4 mg/dL in women and 54.0 mg/dL in men and lipoprotein(a) by 9.7 and 8.1 mg/dL, respectively (both p<0.0001). Alirocumab reduced MACE, death, and total cardiovascular events similarly in both sexes. In the placebo group, lipoprotein(a) was a risk factor for total cardiovascular events in women and men. In both sexes, reduction of total cardiovascular events was greater at higher baseline lipoprotein(a), but this effect was more evident in women than men (p interaction =0.08). Medication adherence and adverse event rates were similar in both sexes. Conclusions Alirocumab improves cardiovascular outcomes after ACS irrespective of sex. Summary After recent ACS, addition of alirocumab to GDMT improves outcomes consistently in women and men. Reduction of total cardiovascular events was greater at higher baseline Lp(a).
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.001 | 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".