Cardiovascular Outcomes With Icosapent Ethyl by Baseline Low‐Density Lipoprotein Cholesterol: A Secondary Analysis of the REDUCE‐IT Randomized Trial
Bibliographic record
Abstract
Background The efficacy of icosapent ethyl among patients with very well‐controlled baseline low‐density lipoprotein cholesterol (LDL‐C) is unknown. Methods In this post hoc analysis of the REDUCE‐IT (Reduction of Cardiovascular Events With Icosapent Ethyl–Intervention Trial) randomized clinical trial, statin‐treated patients with high cardiovascular risk, elevated triglycerides (135–499 mg/dL), and baseline LDL‐C of 41 to 100 mg/dL were included. Patients were randomized to icosapent ethyl (2 g twice daily) or placebo and then post hoc stratified by baseline LDL‐C (<55 mg/dL versus ≥55 mg/dL). The primary composite end point included cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, coronary revascularization, or unstable angina. Results Among 8175 patients with baseline LDL‐C data, 7117 (87.1%) had LDL‐C ≥55 mg/dL and 1058 (12.9%) had LDL‐C <55 mg/dL. In patients with LDL‐C <55 mg/dL, the rate of the primary composite end point was lower in the icosapent ethyl group (16.2% versus 22.8%) than in the placebo group (hazard ratio [HR], 0.66 [95% CI, 0.50–0.87]; absolute risk reduction, 6.6%; P =0.003). Among patients with LDL‐C ≥55 mg/dL, a primary composite end point event occurred in a lower proportion of patients in the icosapent ethyl group (17.4% versus 21.9%) than in the placebo group (HR, 0.76 [95% CI, 0.69–0.85]; absolute risk reduction, 4.5%; P <0.0001). No significant interaction was observed between baseline LDL‐C and treatment group ( P for interaction=0.40). Findings were consistent among secondary cardiovascular end points and in sensitivity analyses. Conclusions Among statin‐treated patients with elevated triglycerides and high cardiovascular risk, icosapent ethyl reduced the rate of cardiovascular end points irrespective of baseline LDL‐C, including among eligible patients with optimal LDL‐C control. 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".