Effects of aspirin dose on ischaemic events and bleeding after percutaneous coronary intervention: insights from the PCI-CURE study
Bibliographic record
Abstract
AIMS: In the setting of percutaneous coronary intervention (PCI), due to a paucity of data, the optimal dose of aspirin is uncertain. We evaluated the safety of different doses of aspirin after PCI. METHODS AND RESULTS: In the PCI-CURE study, 2658 patients with acute coronary syndromes undergoing PCI were stratified into three aspirin dose groups >/=200 mg (high, n = 1064), 101-199 mg (moderate, n = 538), and </=100 mg (low, n = 1056). For efficacy, the moderate- (7.4%) and high-dose groups (8.6%) had similar rates of cardiovascular death, myocardial infarction, or stroke compared with the low-dose group (7.1%). For safety, major bleeding was increased with high-dose aspirin [3.9, 1.5, and 1.9% in the high-, moderate-, and low-dose groups; hazard ratio (HR) of high vs. low dose 2.05 (95% CI 1.20-3.50, P = 0.009]. The net adverse clinical events (death, MI, stroke, major bleeding) favoured low-over high-dose aspirin (8.4 vs. 11.0%, HR 1.31, 95% CI 1.00-1.73 P = 0.056). CONCLUSION: In this large observational analysis of patients undergoing PCI, low-dose aspirin appeared to be as effective as higher doses in preventing ischaemic events but was also associated with a lower rate of major bleeding and an improved net efficacy to safety balance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".