Abstract 10291: Elevated C-Reactive Protein Level Amplifies the Association of Lipoprotein(a) With Cardiovascular Risk and Risk Reduction With Alirocumab After Acute Coronary Syndrome
Bibliographic record
Abstract
Background: In the ODYSSEY OUTCOMES trial (NCT01663402) the PCSK9 inhibitor alirocumab [ALI] reduced the risk of cardiovascular events [CVE] after acute coronary syndrome [ACS] in patients [pts] with elevated atherogenic lipoproteins despite optimized statin treatment, an effect modified by baseline levels of lipoprotein [Lp](a). Levels of the inflammatory biomarker high-sensitivity C-reactive protein [hsCRP] are associated with risk after ACS. In this post hoc analysis, we determined whether Lp(a)-associated risk of CVE after ACS and reduction in that risk with ALI are modified by concurrent hsCRP levels. Methods: 18,924 pts were randomized to ALI or placebo [PBO] 1-12 months after ACS and followed for median 2.8 years. Baseline Lp(a) and hsCRP were available in 18,290 pts. CVE [CV death, non-fatal MI, stroke, unstable angina or heart failure hospitalization, ischemia-driven coronary revascularization, peripheral artery events, and venous thromboembolism] were evaluated by baseline quartile of Lp(a) and by hsCRP dichotomized at 0.2 mg/dL. Results: Median (Q1-Q3) baseline Lp(a) was 21.3 (6.7-59.6) mg/dL. In 10,323 pts with baseline hsCRP<0.2 mg/dL ( Fig top ) risk of CVE in the PBO group increased modestly in Lp(a) Q4 (P trend =0.0592). Overall treatment hazard ratio [HR] was 0.91 without significant trend across Lp(a) quartiles. In 7967 pts with baseline hsCRP≥0.2 mg/dL ( Fig bottom ) risk of CVE in the PBO group was elevated and increased across Lp(a) quartiles (P trend <0.0001). Overall treatment HR was 0.82 and decreased across Lp(a) quartiles (P trend =0.0003). Conclusion: Elevated hsCRP amplifies the relationship of Lp(a) with risk of CVE after ACS and the reduction in that risk with alirocumab. Funding: Sanofi, Regeneron Pharmaceuticals
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".