Impact of Icosapent Ethyl on Cardiovascular Risk Reduction in Patients With Heart Failure in REDUCE‐IT
Bibliographic record
Abstract
Background Patients with heart failure (HF) are at high risk for atherosclerotic cardiovascular disease. Studies of atherothrombotic treatments in this population have been disappointing to date. Icosapent ethyl reduced the risk of atherosclerotic cardiovascular disease among a broad array of statin‐treated patients at elevated risk for atherosclerotic cardiovascular disease. Whether the treatment benefits of icosapent ethyl are consistent among those with HF is unknown. Methods and Results REDUCE‐IT (Reduction of Cardiovascular Events With Icosapent Ethyl–Intervention Trial) randomized 8179 participants, including 1446 (17.7%) patients with a history of HF (icosapent ethyl, N=703; and placebo, N=743). The primary end point was a composite of cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, coronary revascularization, or unstable angina. We used Cox regression to estimate the risk of outcomes of participants with and without HF. We estimated the placebo‐controlled change in triglycerides and hs‐CRP (high‐sensitivity C‐reactive protein) from baseline to 2 years. Among 1446 patients with HF, median age was 63.0 years, median body mass index was 31.0 kg/m 2 , and more were men (69.3%). Icosapent ethyl reduced triglycerides (median reduction, 33.5 mg/dL, or 15.4%; P <0.0001) and hs‐CRP (35.1%; P <0.0001) compared with placebo, similar to patients without HF ( P ‐interaction>0.90). The treatment effect on the primary end point in patients with HF history (hazard ratio [HR], 0.87; 95% CI, 0.70–1.08) was consistent with the effects observed in patients without HF history (HR, 0.73; 95% CI, 0.65–0.81) ( P ‐interaction=0.13). Conclusions In REDUCE‐IT, icosapent ethyl provided similar improvements in triglyceride levels and hs‐CRP as well as similar cardiovascular risk reduction in patients with and without HF. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01492361.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".