A randomised study for optimising crossover from ticagrelor to clopidogrel in patients with acute coronary syndrome
Bibliographic record
Abstract
Summary Ticagrelor has been endorsed by guidelines as the P2Y12 inhibitor of choice in patients with acute coronary syndrome. Clinically, some patients on ticagrelor will require a switch to clopidogrel; however, the optimal strategy and pharmacodynamics effects of switching remain unknown. Patients with an indication to switch were randomly assigned to either a bolus arm (Clopidogrel 600 mg bolus followed by 75 mg daily, n=30) or a no-bolus arm (Clopidogrel 75 mg daily, n=30). Blood samples were collected at baseline, 12, 24, 48, 54, 60 and 72 hours (h) for assessment of platelet reactivity. The primary outcome was P2Y12 reactivity units (PRU) at 72 h. Secondary outcomes included: PRUs at each time point, incidence of high on-treatment platelet reactivity (HPR), major adverse cardiac events (MACE) and TIMI bleeding at 30 days. Serial PRUs increased after switching to clopidogrel in both groups. At 72 h, no difference in PRU was observed (165.8 ± 71.0 vs 184.1 ± 67.7, bolus vs no bolus, respectively, p=0.19). At 48 h the PRUs were significantly lower in the bolus arm (114 ± 73.1 vs 165.1 ± 70.5, respectively; p=0.0076) and at 72 h, there was a significant reduction in incidence of HPR (26.7 % vs 56.7 %, p=0.02). No differences in MACE or TIMI bleeding were observed. Although a bolus strategy was not associated with improved platelet inhibition at 72 h; at 48 h, platelet inhibition was superior with reduced incidence of HPR. Larger studies will be required to determine its clinical significance. Until then, decision for giving a bolus of clopidogrel at the time of a switch may in part be dependent on the indication for switching, especially if there are concerns for bleeding risk. Supplementary Material to this article is available online at www.thrombosis-online.com.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".