Abstract 10627: Benefits of Icosapent Ethyl in Patients with Prior Peripheral Artery Disease: REDUCE-IT PAD
Bibliographic record
Abstract
Introduction: REDUCE-IT found significant benefit in 8179 statin-treated patients randomized to icosapent ethyl (IPE). Whether that benefit extends to patients with peripheral artery disease (PAD) was unknown. Methods: The primary endpoint was time to cardiovascular (CV) death, myocardial infarction (MI), stroke, coronary revascularization, or hospitalization for unstable angina. The key secondary endpoint was CV death, MI, or stroke. Total (first plus recurrent) events were also assessed. PAD was an inclusion criterion in the established CV disease cohort. Prespecified and post hoc analyses by baseline history of PAD history were performed. Results: Of 5785 (70.7%) REDUCE-IT patients enrolled with established CV disease, 688 had PAD. IPE demonstrated statistically similar risk reduction in first (interaction P [p int ]=0.58) and total (p int =0.78) primary endpoints in patients with established CV disease with or without PAD, though PAD patients had higher first (placebo: 32.8% with vs 24.5% without PAD) and total (placebo: 162.3 vs 101.7 per 1000 patient-years) event rates. The primary endpoint event rate with PAD was 26.2% with IPE vs 32.8% with placebo (HR 0.78; 95% CI 0.59, 1.03; P=0.08) and total events were 112.8 per 1000 patient-years with IPE vs 162.3 with placebo (RR 0.68; 95% CI 0.48, 0.95; P=0.03) (Figure). Primary endpoint absolute risk reductions (ARR) and numbers needed to treat (NNT) suggest benefit for patients with (ARR 6.6%; NNT 15) and without (6.1%; 16) PAD. Safety did not differ substantially by PAD history and was generally consistent with the overall study. Conclusions: In REDUCE-IT, patients with PAD were at very high risk of subsequent ischemic events. IPE provided consistent CV benefit in patients with or without PAD.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".