Response to aspirin in healthy individuals
Bibliographic record
Abstract
Variable biological effect of aspirin is suggested to be related to pharmacological resistance. The incidence of this so-called "resistant" state varies with the study population and the assay used. We determined performance features of five assays used to assess aspirin effects in non-smoking healthy volunteers not taking any drug known to interfere with platelet function. Blood and urine samples were obtained immediately before and after 8-10 days of aspirin 80 mg intake. Forty-five participants 19-59 years old were enrolled. The sensitivity (SE), specificity (SP), and optimal cut-off (CO) value to detect the effect of aspirin were: light transmission aggregometry (LTA) with 1.6 mM arachidonic acid (AA) - SE 100%, SP 95.9%, CO 20%; LTA with adenosine diphosphate (ADP) 10 microM - SE 84.4%, SP 77.8%, CO 70%; VerifyNow Aspirin - SE 100%, SP 95.6%, CO 550 ARU; platelet count drop - SE 82.2%, SP 86,7%, CO 55%; TEG((R)) - SE 82,9%, SP 75,8%, CO 90%; and urinary 11-dehydrothromboxane B(2) levels (11-dHTB(2)) - SE 62.2%, SP 82.2%, CO 60 pg/ml. AA-induced LTA and the VerifyNow assay reliably detected aspirin intake in all subjects; there was wide overlap in pre- and post- aspirin results with ADP-induced LTA, platelet count drop, TEG((R)) and urinary 11-dHTB(2) assays. These results suggest that some of the variability in the reported incidence of "aspirin resistance" is unrelated to aspirin intake but related to inherent limitations of some assays to detect aspirin mediated effects or to underlying platelet reactivity variability independent of aspirin-mediated cyclooxygenase-1 inhibition.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".