Icosapent ethyl reduces cardiovascular risk across apolipoprotein b and fasting triglyceride rich lipoprotein levels
Bibliographic record
Abstract
Abstract Background/Introduction Increased apolipoprotein B (ApoB) levels due to triglyceride rich lipoproteins (TRLs) are associated with increased cardiovascular risk, even when low-density lipoprotein cholesterol (LDL-C) levels are well controlled. In the REDUCE-IT cardiovascular outcomes trial, icosapent ethyl (IPE) showed cardiovascular risk reduction in patients with residual elevated triglycerides (TGs) persisting on statin therapy, but the impact of IPE on cardiovascular risk reduction across ApoB and TRL-cholesterol (TRL-C) strata is unclear. Purpose To study the impact of IPE on major adverse cardiovascular events (MACE) stratified by ApoB and fasting TRL-C. Methods REDUCE-IT was an international, double-blind, placebo-controlled study of 8,179 participants receiving statin therapy with established cardiovascular disease or age ≥ 50 years with diabetes and ≥ 1 additional risk factor, fasting TG level of 1.52 to 5.63 mmol/L (135 to 499 mg/dL) and LDL-C level of 1.06 to 2.59 mmol/L (41 to 100 mg/dL). Patients were randomized to receive 2 grams twice daily of IPE or matching placebo. Relationships between quartiles of baseline ApoB concentration, baseline fasting TRL-C and risk for first and total MACE were analyzed. Results Baseline ApoB and fasting TRL-C concentrations were available in 8,107 (99.1%) and 8,157 (99.7%) participants, respectively. Median baseline ApoB concentration was 0.82 g/L (IQR: 0.72 – 0.93 g/L) [82.0 mg/dL (IQR: 72.0 – 93.0 mg/dL)] and median baseline fasting TRL-C concentration was 0.80 mmol/L (IQR: 0.69 – 0.95 mmol/L) [31.0 mg/dL (IQR: 26.6 – 36.8 mg/dL)]. From the first through fourth baseline quartiles of ApoB, IPE resulted in significant reductions in MACE, HR 0.72 (95% CI 0.58, 0.88), HR 0.73 (95% CI 0.59, 0.89), HR 0.76 (95% CI 0.63, 0.91), and HR 0.80 (95% CI 0.66, 0.97), respectively (all P ≤ 0.02) (Figure 1). The first quartile of fasting TRL-C had a borderline reduction in MACE (HR 0.82, 95% CI 0.67, 1.00) (P = 0.05) (Figure 2), in contrast to significant reductions above the 25th percentile, HR 0.74 (95% CI 0.60, 0.90), HR 0.79 (95% CI 0.65, 0.96), and HR 0.68 (95% CI 0.56, 0.82), from the second through fourth quartiles, respectively (all P ≤ 0.02). Conclusion IPE significantly reduced MACE across all quartiles of baseline ApoB and TRL-C concentrations above the 25th percentile.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".