Ticagrelor for the treatment of peripheral arterial disease
Bibliographic record
Abstract
INTRODUCTION: Peripheral arterial disease (PAD) is a manifestation, and marker of severity, of a generalized atherosclerotic process. Antiplatelet therapy is recommended to prevent cardiovascular events but much of the evidence to support this is drawn from studies on older drugs. AREAS COVERED: In this review, the authors discuss the available evidence for the basis of current recommendations and review the data from Phase I to III trials on ticagrelor as a potential future treatment. This paper also reviews the properties of ticagrelor, its adverse effects, and how it differs from current recommended antiplatelet agents. As it is also more potent, a personalized approach to antiplatelet therapy may prove useful. It further highlights the additional effects of ticagrelor mediated by adenosine and their potential benefits, which may provide an explanation to its superior outcomes in trials comparing it with clopidogrel. EXPERT OPINION: Although there is a current lack of evidence to support the use of ticagrelor in patients with PAD, its unique pleomorphic properties make it attractive for future investigations and development of similar drugs.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".