Week‐Long High‐Maintenance Dose Clopidogrel Regimen Achieves Better Platelet Aggregation Inhibition than a Standard Loading Dose before Percutaneous Coronary Intervention: Results of a Double‐Blind, Randomized Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Adequate platelet inhibition before percutaneous coronary intervention (PCI) reduces periprocedural and long-term ischemic complications. Reduced response to clopidogrel has been associated with subsequent major adverse cardiovascular events. Strategies to optimize platelet inhibition pre-PCI are under investigation. This study evaluated the effect on platelet aggregation of four different dosing regimens of clopidogrel given before elective PCI in a randomized, prospective, double-blind, and placebo-controlled design. METHODS: One hundred twenty participants were randomized to one of four groups of clopidogrel: (a) 300 mg on the day prior to angiography; (b) 600 mg on the day prior to angiography; (c) 300 mg followed by 75 mg daily started 1 week prior to angiography; and (d) 300 mg followed by 150 mg daily started 1 week prior to angiography. Platelet aggregation was assessed by light transmission aggregometry (LTA) after stimulation with adenosine diphosphate 20 microM at baseline and at the time of diagnostic coronary angiography. The absolute change in platelet aggregation between these two time points was considered the main outcome measure. RESULTS: At the time of diagnostic coronary angiography, the 300-mg/150-mg daily regimen achieved the greatest decrease in platelet aggregation (37 +/- 19%), while the 300 mg regimen provided the smallest (20 +/- 22%), an absolute difference between the two groups of 17.2 +/- 5.1% (P = 0.005). CONCLUSIONS: A 300-mg loading dose of clopidogrel followed by 150 mg daily for 1 week prior to coronary angiography provides more effective platelet inhibition, as defined by LTA, compared to the standard 300-mg loading dose regimen at the time of coronary intervention.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".