Relation of High Lipoprotein (a) Concentrations to Platelet Reactivity in Individuals with and Without Coronary Artery Disease
Bibliographic record
Abstract
INTRODUCTION: Lipoprotein (a) [Lp(a)] is a risk factor for coronary artery disease (CAD). To the best of our knowledge, this is the first study addressing the relationship between Lp(a) and platelet reactivity in primary and secondary prevention. METHODS: assay. Platelet reactivity was also induced by arachidonic acid and collagen-epinephrine (C-EPI) and assessed by Multiplate™, platelet function analyzer™ 100 (PFA-100), and light transmission aggregometry (LTA) assays. Secondary objectives included the assessment of the primary endpoint in individuals with or without CAD. RESULTS: Overall, 294 (74.2%) individuals had Lp(a) < 50 mg/dL [median (IQR) 13.2 (5.8-27.9) mg/dL] and 102 (25.8%) had Lp(a) ≥ 50 mg/dL [82.5 (67.6-114.5) mg/dL], P < 0.001. Univariate analysis in the entire population revealed no differences in ADP-induced platelet reactivity between individuals with Lp(a) ≥ 50 mg/dL (249.4 ± 43.8 PRU) versus Lp(a) < 50 mg/dL (243.1 ± 52.2 PRU), P = 0.277. Similar findings were present in individuals with (P = 0.228) and without (P = 0.669) CAD, and regardless of the agonist used or method of analysis (all P > 0.05). Finally, multivariable analysis did not show a significant association between ADP-induced platelet reactivity and Lp(a) ≥ 50 mg/dL [adjusted OR = 1.00 [(95% CI 0.99-1.01), P = 0.590]. CONCLUSION: In individuals with or without CAD, Lp(a) ≥ 50 mg/dL was not associated with higher platelet reactivity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".