Comparison of Inflammatory Response After Implantation of Sirolimus- and Paclitaxel-Eluting Stents in Porcine Coronary Arteries
Bibliographic record
Abstract
BACKGROUND: Although both sirolimus (CYPHER) and paclitaxel (TAXUS) drug-eluting stents have demonstrated efficacy and safety in clinical trials, human autopsy data have raised concerns about long-term healing and the potential for local inflammatory reactions. METHODS AND RESULTS: Overlapping stents (CYPHER drug-eluting stents, Bx SONIC bare metal stents, TAXUS drug-eluting stents, and Liberté bare metal stents) were implanted in noninjured coronary arteries of 58 domestic swine. Histopathological evaluation of proximal, overlapped, and distal stented segments was determined with emphasis on inflammation at 30, 90, and 180 days. Circumferential granulomatous inflammation in all stented segments was defined as inflammation consisting of macrophages, multinucleated giant cells, lymphocytes, and granulocytes, including many eosinophils, adjacent to almost all struts. Circumferential granulomatous inflammation was more prevalent in CYPHER (9 of 23, 39%) compared with TAXUS (1 of 21, 5%; P=0.01) and control bare metal stents (0 of 44) in the combined 90- and 180-day cohorts. Only CYPHER specimens showed marked adventitial inflammation (P=0.0025) and fibrosis (P=0.0055) accompanied by extensive remodeling. Fibrin deposition within neointima and medial smooth muscle cell death were greater (both P<0.001) in TAXUS than CYPHER at 30 days, with more fibrin in TAXUS than CYPHER through 90 days (P<0.05). CONCLUSIONS: Although these data cannot be directly extrapolated to humans, the high prevalence in this porcine model of diffuse granulomatous inflammation seen with CYPHER stents, persisting at 180 days and associated with extensive remodeling of the artery, and persistent para-strut fibrin deposition with TAXUS stents emphasize the need for further investigation of biocompatibility with these and other novel combination drug/polymer drug-eluting stents.
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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 | 0.000 | 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) | 0.001 | 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".