Moving away from metal: Step toward the future with bioresorbable vascular scaffolds and novel antiproliferative agents
Bibliographic record
Abstract
Background: Peripheral arterial disease (PAD) is a common source of morbidity and mortality globally and is expected to raise increase in prevalence. Many endovascular techniques exist to manage PAD; however, there remains room for improvement, especially as it relates to below-the-knee vessels. Recent evidence and devices are leading to a resurgence of interest in bioresorbable vascular scaffolds and the -limus family of antiproliferative drugs in the PAD treatment space. Methods: This nonsystematic review examines emerging technology for treatment of PAD with a specific focus on below-the-knee vessels and bioresorbable vascular scaffolds. Additional emerging and early technology such as novel delivery platforms are also briefly discussed with directions of future research highlighted. Results: Bioresorbable vascular scaffold biomechanics and history are highlighted. Foundational knowledge of antiproliferative agents and evolving agents in peripheral vascular disease are also described. Conclusions: Bioresorbable vascular scaffolds are an additional endovascular tool for the treatment of peripheral vascular disease. The integration with an antiproliferative agent may result in improved patency and performance; however, there is a paucity of data in the literature at present.
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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 | 0.001 | 0.001 |
| 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 | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".