Relative efficacy and safety of ticagelor vs clopidogrel as a function of time to invasive management in non–ST‐segment elevation acute coronary syndrome in the PLATO trial
Bibliographic record
Abstract
Abstract Background Guidelines suggest that “upstream” P2Y12 receptor antagonists should be considered in patients with non–ST‐segment elevation acute coronary syndromes (NSTE‐ACS). Hypothesis Early use of ticagrelor in patients managed with an invasive strategy would be more effective than clopidogrel because of its more rapid onset of action and greater potency. Methods In the PLATO trial, 6792 NSTE‐ACS patients were randomized to ticagrelor or clopidogrel (started prior to angiography) and underwent angiography within 72 hours of randomization. We compared efficacy and safety outcomes of ticagrelor vs clopidogrel as a function of “early” (<3h) vs “late” (≥3h) time to angiography. Adjusted Cox proportional hazards models evaluated interaction between randomized treatment and time from randomization to angiography on subsequent outcomes. Results Overall, a benefit of ticagrelor vs clopidogrel for cardiovascular death/myocardial infarction/stroke was seen at day 7 (hazard ratio [HR]: 0.67, P = 0.002), day 30 (HR: 0.81, P = 0.042), and 1 year (HR: 0.80, P = 0.0045). There were no significant interactions in the <3h vs ≥3h groups at any timepoint. For major bleeding, overall there was no significant increase (HR: 1.04, 95% confidence interval: 0.85‐1.27); but there was a significant interaction with no difference between ticagrelor and clopidogrel in the early group (HR: 0.79), but higher bleeding risk with ticagrelor in the late angiography group, at 7 days (HR: 1.51, Pint = 0.002). Patterns were similar at 30 days and 1 year. Conclusions The benefit of ticagrelor over clopidogrel was consistent in those undergoing early and late angiography, supporting upstream use of ticagrelor.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".