Intravascular Ultrasound Results From the NEVO ResElution-I Trial
Bibliographic record
Abstract
BACKGROUND: The NEVO sirolimus-eluting stent (NEVO SES) is a novel cobalt-chromium stent combining sirolimus release from reservoirs with bioabsorbable polymer to reduce spatial and temporal polymer exposure. The aim of this study was to assess the arterial response to the NEVO SES in a randomized, blinded comparison versus the surface-coated TAXUS Liberte paclitaxel-eluting stent (TAXUS Liberté PES) in human native coronary lesions using intravascular ultrasound (IVUS). METHODS AND RESULTS: The NEVO ResElution-I IVUS substudy enrolled 100 patients (1:1 randomization). In addition to standard IVUS variables, uniformity of neointimal distribution within stents was evaluated in 3 dimensions by computing mean neointimal thickness within 12 equally spaced radial sectors on every 1-mm cross section along the stented segment. The NEVO SES showed significantly less neointimal proliferation (neointimal obstruction: 5.5±11.0% versus 11.5±9.7%, P=0.02), resulting in less late lumen area loss and smaller maximum cross-sectional narrowing at 6 months. The absolute variability of neointima distribution, assessed by the standard deviation of neointimal thickness within each stent, was significantly reduced with the NEVO SES compared with the TAXUS Liberté PES(0.04±0.04 mm versus 0.10±0.07 mm, P<0.0001). TAXUS Liberté PES showed significantly greater positive vessel remodeling than the NEVO SES (Δvessel volume index: 1.30±1.36 mm(3)/mm versus 0.36±0.63 mm(3)/mm, respectively, P=0.003). CONCLUSIONS: The NEVO SES with focal release of sirolimus from reservoirs achieved significantly greater and more consistent suppression of neointimal hyperplasia than the surface-coated TAXUS Liberté PES. This was associated with less positive remodeling and no increased morphological or morphometric abnormalities surrounding the stent or at the stent margins. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00714883.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".