Effects of Icosapent Ethyl on Total Ischemic Events
Bibliographic record
Abstract
BACKGROUND: In time-to-first-event analyses, icosapent ethyl significantly reduced the risk of ischemic events, including cardiovascular death, among patients with elevated triglycerides receiving statins. These patients are at risk for not only first but also subsequent ischemic events. OBJECTIVES: Pre-specified analyses determined the extent to which icosapent ethyl reduced total ischemic events. METHODS: REDUCE-IT (Reduction of Cardiovascular Events with Icosapent Ethyl-Intervention Trial) randomized 8,179 statin-treated patients with triglycerides ≥135 and <500 mg/dl (median baseline of 216 mg/dl) and low-density lipoprotein cholesterol >40 and ≤100 mg/dl (median baseline of 75 mg/dl), and a history of atherosclerosis (71% patients) or diabetes (29% patients) to icosapent ethyl 4 g/day or placebo. The main outcomes were total (first and subsequent) primary composite endpoint events (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, coronary revascularization, or hospitalization for unstable angina) and total key secondary composite endpoint events (cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke). As a pre-specified statistical method, we determined differences in total events using negative binomial regression. We also determined differences in total events using other statistical models, including Andersen-Gill, Wei-Lin-Weissfeld (Li and Lagakos modification), both pre-specified, and a post hoc joint frailty analysis. RESULTS: In 8,179 patients, followed for a median of 4.9 years, 1,606 (55.2%) first primary endpoint events and 1,303 (44.8%) subsequent primary endpoint events occurred (which included 762 second events, and 541 third or more events). Overall, icosapent ethyl reduced total primary endpoint events (61 vs. 89 per 1,000 patient-years for icosapent ethyl versus placebo, respectively; rate ratio: 0.70; 95% confidence interval: 0.62 to 0.78; p < 0.0001). Icosapent ethyl also reduced totals for each component of the primary composite endpoint, as well as the total key secondary endpoint events (32 vs. 44 per 1,000 patient-years for icosapent ethyl versus placebo, respectively; rate ratio: 0.72; 95% confidence interval: 0.63 to 0.82; p < 0.0001). CONCLUSIONS: Among statin-treated patients with elevated triglycerides and cardiovascular disease or diabetes, multiple statistical models demonstrate that icosapent ethyl substantially reduces the burden of first, subsequent, and total ischemic events. (Reduction of Cardiovascular Events With Icosapent Ethyl-Intervention Trial [REDUCE-IT]; NCT01492361).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".