‘Fused-Gold’ vs. ‘Bare’ stainless steel NIRflex stents of the same geometric design in diseased native coronary arteries. Long-term results from the NIR TOP Study
Bibliographic record
Abstract
OBJECTIVES: We evaluated the long-term clinical and angiographic results of 'fused-gold' (NIRFlex Royal) and 'bare' (NIRFlex) stainless steel stents in patients undergoing percutaneous coronary intervention (PCI). BACKGROUND: Recent studies have shown high clinical and angiographic restenosis rates following the intracoronary implantation of 'gold-coated' stainless steel stents. The new 'fused-gold' stent, with improved surface characteristics and flexibility, was developed to improve procedural and long-term results, while maintaining enhanced radiopacity. METHODS: A total of 305 patients (358 lesions) with symptomatic native coronary artery disease (CAD) undergoing native vessel PCI were randomised to receive a 'fused-gold' (n=147) or 'bare' (n=158) stent. Primary endpoint was minimal luminal diameter (MLD) at 6 months angiographic follow-up. Secondary endpoints included technical and procedural success, major adverse cardiac events (MACE), target vessel failure (TVF), angiographic binary restenosis rates, and additional angiographic comparisons. RESULTS: There were no major differences in the baseline angiographic variables or patient characteristics between the two groups, however there was a trend towards a higher risk in the 'fused-gold' stent group. Clinical and angiographic follow-up was 100% and 87% respectively. MLD at 6 months follow-up was smaller in the 'fused-gold' stent group compared to the 'bare' stent group (1.61+/-0.65 vs. 1.81+/-0.60 mm, respectively); Therefore, the null hypothesis of non-inferiority cannot be rejected (p=0.49); equivalency cannot be claimed for the two stent types. The 'fused-gold' stents were also associated with a higher angiographic binary and clinical restenosis rates (33 vs. 18%; p=0.002 & 26.9 vs. 20.3%; p<0.001, respectively). CONCLUSION: The 'bare' NIRflex stent was associated with excellent long-term clinical and angiographic results. Taking into account the equivalence margin, the null hypothesis of non-equivalence between the 'fused-gold' NIRflex Royal stent and the 'bare' NIRflex stent cannot be rejected (p=0.49), so equivalence cannot be claimed for the two stent types.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".