Scanning electron microscopic analysis of different drug eluting stents after failed implantation: From nearly undamaged to major damaged polymers
Bibliographic record
Abstract
BACKGROUND: Implantation of drug eluting stents (DES) in tortuous and/or calcified vessels is much more demanding compared with implantation of bare metal stents (BMS) due to their larger diameters. It is unknown whether drug eluting stent coatings get damaged while crossing these lesions. METHODS: In 42 patients (34 male, 68.1 +/- 10 years) with 45 calcified lesions (15.9 mm +/- 7.9 mm), DES could not be implanted, even after predilatation. Diabetes was present in 19 patients (45%). Sixty-one stents were used; 19 Cypher select, 18 Taxus Liberté, 10 CoStar, 5 Endeavor RX, 4 Xience V. 3 Janus Carbostent, 1 Yukon Choice S, and 1 Axxion DES. The entire accessible surface area of these stents, in either the unexpanded and expanded state, were examined with an environmental scanning electron microscope (XL30 ESEM, Philips) to evaluate polymer or surface damage. RESULTS: The polymers of Taxus Liberte, Cypher Select, Xience V, CoStar, and Janus DES were only slightly damaged (less than 3% of surface area), whereas the Endeavor RX Stents showed up to 20% damaged surface area. In DES without a polymer (Yukon and Axxion), it could be shown that most of the stent surface (up to 40%) were without any layer of drug. CONCLUSION: Placement of drug eluting stents in tortuous vessels and/or calcified lesions could cause major surface damage by scratching and scraping of the polymer or drug by the arterial wall, even before implantation. There were remarkable differences among the stents examined, only minor damage with the Cypher, Taxus Costar, Janus, and Xience V, whereas the Endeavor, the Yukon, and the Janus DES showed large areas of surface injury.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".