Real-World Experience With a Tapered Biodegradable Polymer-Coated Sirolimus-Eluting Stent in Patients With Long Coronary Artery Stenoses
Bibliographic record
Abstract
BACKGROUND: Treatment of long coronary stenoses (LCS) with long tapered drug-eluting stents (LT-DES) would offer clinical and economic benefits. However, the feasibility of an interventional strategy based upon the systematic LCS treatment with an LT-DES has not been evaluated so far. METHODS: We performed a multicenter prospective study including consecutive patients with: 1) An LCS > 25 mm at coronary angiography; 2) An attempt to fix the LCS with a single BioMime Morph™ stent, a novel LT-DES available from 30 to 60 mm long. The primary efficacy endpoint was procedural success. The secondary safety endpoints were post-procedural TIMI3 flow, stent detachment during delivery, acute stent thrombosis and in-hospital mortality. RESULTS: From February 2017 to March 2018, we recorded 272 patients with an LCS and an attempt to deploy an LT-DES during percutaneous coronary intervention (PCI) (69.3 ± 11.4 years, 75.7% males, 25.7% diabetic and 43.8% with acute coronary syndromes, mean LCS length 48.8 ± 9.5 mm). LT-DES deployment was successful in 262 patients (96.3%), and failure occurred without stent detachment or other complications. Final TIMI3 flow was present in 270 (99.3%) patients. In-hospital death occurred in five patients (1.8%), with no case of acute stent thrombosis, recurrent myocardial infarction or repeated revascularization. CONCLUSION: In this real-world study, a strategy of fixing LCS with a single LT-DES was feasible and safe, with a high rate of procedural success and a low rate of in-hospital complications. More extensive randomized studies are warranted to assess the potential clinical and economic benefits of LT-DES.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".