Antithrombotic treatment for peripheral arterial disease
Bibliographic record
Abstract
CONTEXT: Patients with peripheral arterial disease (PAD) bear a substantial risk for vascular events in the coronary, cerebral and peripheral circulations. In addition, this disorder is associated with a systemic milieu characterised by ongoing platelet activation and heightened thrombogenesis. OBJECTIVE: To determine the optimal antithrombotic prophylaxis for patients with PAD. DATA SOURCES: Using terms related to PAD and antithrombotic agents, we searched the following databases for relevant articles: MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, the Cochrane Database of Systematic Reviews, the National Institutes of Health Clinical Trials Database, Web of Science, and the International Pharmaceutical Abstracts Database (search dates: 1 January 1990 to 1 January 2007). Additional articles were identified from cardiovascular and vascular surgery conference proceedings, bibliographies of review articles, and personal files. STUDY SELECTION: We focused on randomised trials, systematic reviews and consensus guidelines of antithrombotic therapies for PAD. DATA EXTRACTION: Detailed study information was abstracted by each author working independently. RESULTS: Multiple studies show that patients with PAD manifest platelet hyperaggregability, increased levels of soluble platelet activation markers, enhanced thrombin generation and altered fibrinolytic potential. Many of these markers predict subsequent cardiovascular events. Available randomised trials and meta-analyses show that most available antithrombotic agents prevent major cardiovascular events and death in patients with PAD, including aspirin, aspirin/dipyridamole, clopidogrel, ticlopidine, picotamide and oral anticoagulants. CONCLUSIONS: Although the most favourable risk-benefit profile, cost-effectiveness and overall evidence base supports aspirin in this setting, we provide scenarios in which alternatives to aspirin should be considered.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".