Abstract 13043: LDL-C, Lp(a) and Hs-CRP Each Predict Future Cardiovascular Events After ACS on High-Intensity Statin Therapy. An Analysis of the ODYSSEY OUTCOMES Trial
Bibliographic record
Abstract
Background: Atherosclerotic cardiovascular disease (ASCVD) risk has been jointly associated with levels of LDL cholesterol (LDL-C), lipoprotein [Lp](a)] and the inflammatory marker high-sensitivity C reactive protein (hsCRP). It is unclear whether and to what extent each of these biomarkers predict ASCVD risk after acute coronary syndrome (ACS), particularly in the era of intensive LDL-C lowering. Recent analysis of 3 trials in stable ASCVD patients with hypertriglyceridemia suggested that hsCRP may be a stronger predictor for recurrent events than LDL-C; however, only 52% received high-intensity statin. Methods: The ODYSSEY OUTCOMES trial enrolled post-ACS patients not at goal for atherogenic lipoproteins a median of 2.6 months after ACS and on treatment with maximum tolerated (89% high-intensity) atorvastatin or rosuvastatin. Absolute risk of major adverse cardiovascular events (MACE, the primary composite outcome of coronary heart disease death, nonfatal myocardial infarction, fatal/nonfatal ischemic stroke or unstable angina hospitalization) and all-cause death were analyzed as a function of baseline LDL-C, hs-CRP, and Lp(a) values in patients randomized to the placebo arm via natural cubic splines from Poisson regression models, adjusted for age, sex, diabetes, BMI, current smoking, and the other 2 predictor variables. Results: Among 9149 evaluable patients, median (Q1-Q3) LDL-C, hsCRP, and Lp(a) were 81 (71-97) mg/dL, 1.7 (0.8-3.9) mg/L, and 21.4 (6.6-60.1) mg/dL, respectively. For each parameter, a higher baseline value was associated with a substantial increase in risk of MACE ( Figure , all spline p<0.0001). LDL-C and hsCRP were associated with all-cause death (p<0.0001), but not Lp(a) (p>0.05). Conclusion: In ACS patients receiving intensive statin therapy and not at goal for atherogenic lipoproteins, LDL-C, hs-CRP, and Lp(a) were independent predictors of MACE. LDL-C and hsCRP were independent predictors of all-cause death.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".