Bibliographic record
Abstract
Prasugrel is a potent antiplatelet inhibitor with a rapid onset of activity and reduced inter-patient variability. Clinical trial data from TRITON TIMI-38 demonstrated significantly fewer cardiovascular events in patients presenting with acute coronary syndrome (ACS) and undergoing percutaneous coronary intervention (PCI) who were treated with prasugrel compared with clopidogrel (all patients also received low-dose aspirin). However, prasugrel is also associated with a significantly greater risk of bleeding, including major, life-threatening and fatal bleeds. As a result prasugrel is contraindicated in patients with prior stroke or transient ischaemic attack (TIA); and should only be used cautiously and at a lower maintenance dose in older patients (>75 years) and those of low bodyweight (<60kg). NICE guidance recommends that prasugrel is considered for patients presenting with ACS and scheduled for PCI in three specific groups: patients undergoing primary PCI following an ST-elevation myocardial infarction, patients that experienced re-infarction or stent thrombosis while taking aspirin and clopidogrel, and patients with diabetes mellitus. Since launch, the adoption of prasugrel into routine clinical practice has been slow, probably because clinicians are unsure of the benefit-to-risk ratio, particularly with respect to the risk of bleeding. Patients prescribed prasugrel should be carefully counselled on the importance of adherence to therapy for the prescribed period and should be encouraged to seek specialist advice should side effects or other issues arise during treatment.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".