Biodegradable Metals for Cardiovascular Stent Application: Interests and New Opportunities
Bibliographic record
Abstract
During the last decade, biodegradable metallic stents have been developed and investigated as alternatives for the currently-used permanent cardiovascular stents. Degradable metallic materials could potentially replace corrosion-resistant metals currently used for stent application as it has been shown that the role of stenting is temporary and limited to a period of 6-12 months after implantation during which arterial remodeling and healing occur. Although corrosion is generally considered as a failure in metallurgy, the corrodibility of certain metals can be an advantage for their application as degradable implants. The candidate materials for such application should have mechanical properties ideally close to those of 316L stainless steel which is the gold standard material for stent application in order to provide mechanical support to diseased arteries. Non-toxicity of the metal itself and its degradation products is another requirement as the material is absorbed by blood and cells. Based on the mentioned requirements, iron-based and magnesium-based alloys have been the investigated candidates for biodegradable stents. This article reviews the recent developments in the design and evaluation of metallic materials for biodegradable stents. It also introduces the new metallurgical processes which could be applied for the production of metallic biodegradable stents and their effect on the properties of the produced metals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".