The evolution of coronary stents
Bibliographic record
Abstract
Introduction: Percutaneous coronary intervention (PCI) is 40 years old this year. From its humble beginnings of experimental work, PCI has transitioned over years with coronary artery stenting now a standard medical procedure performed throughout the world.Areas covered: The conversion from plain old balloon angioplasty (POBA) to the present era of drug eluting stents (DES) has been driven by many technological advances and large bodies of clinical trial evidence. The journey to present day practice has seen many setbacks, such as acute vessel closure with POBA; rates of instant restenosis with bare metal stents (BMS) and more recently, high rates of stent thrombosis with bioabsorbable platforms. This work discusses POBA, why there was a need for BMS, the use of inhibiting drugs to create 1st generation DES, the change of components to 2nd generation DES, the use of absorbable drug reservoirs and platforms, and possible future directions with Prohealing Endothelial Progenitor Cell Capture Stents.Expert commentary: This paper reviews the evolution from the original pioneering work to modern day practice, highlighting landmark trials that changed practice. Modern day contemporary practice is now very safe based on the latest drug eluting stents and supported by large datasets.
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 | 0.002 | 0.005 |
| 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 | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".