REVERSAL OF THE ANTI-PLATELET EFFECTS OF ASPIRIN AND CLOPIDOGREL
Bibliographic record
Abstract
Objectives Guidelines recommend stopping aspirin and clopidogrel 7–10 days before surgery to allow time for replacement of permanently inhibited platelets by newly released uninhibited platelets. The purpose of this study was to determine the rate of offset of the anti-platelet effects of aspirin and clopidogrel after stopping treatment and the proportion of untreated donor platelets that are required to reverse their anti-platelet effects. Methods Cohort 1 consisted of 15 healthy subjects who received aspirin 81 mg/d or clopidogrel 75 mg/d for 7 days and underwent serial blood sampling until platelet function testing results normalised. Cohort 2 consisted of 36 healthy subjects who received aspirin 325 mg/d, clopidogrel 75 mg/d, aspirin 81 mg/d plus clopidogrel 75 mg/d or no treatment for 7 days and underwent a single blood sampling. Results In cohort 1, Arachidonic acid (AA)-induced light transmission aggregation (LTA) returned to baseline levels in all subjects within 4 days of stopping aspirin, coinciding with partial recovery of plasma thromboxane B 2 concentrations. ADP-induced LTA did not return to baseline levels until 10 days after stopping clopidogrel. In cohort 2, AA-induced LTA in patient treated with aspirin reached control levels after mixing with 30% untreated donor platelets whereas ADP-induced LTA in patients treated with clopidogrel reached control levels only after the addition of 90% or more donor platelets. Conclusions Platelet aggregation recovers within 4 days of stopping aspirin but clopidogrel must be stopped for 10 days to achieve a normal aggregatory response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".