Clinical Outcomes of Novel Long-Tapered Sirolimus-Eluting Coronary Stent System in Real-World Patients With Long Diffused <i>De Novo</i> Coronary Lesions
Bibliographic record
Abstract
Background: When coronary lesions involve segments > 48 mm, the only treatment possibility is stent overlapping which is associated with higher neointimal proliferation that lead to more restenosis. Furthermore, tapering of coronary arteries is a major challenge observed with long diffuse coronary lesions. This study attempted to assess the safety and performance of world's first commercialised long-tapered (60 mm) sirolimus-eluting coronary stent (SES) system for the treatment of long diffused de novo coronary lesions in real world scenario. Methods: This was a retrospective, non-randomised, multicentre study which included 362 consecutive patients implanted with long-tapered BioMime™ Morph SES system for the treatment of long diffused de novo coronary lesions. Safety endpoint was major adverse cardiac events (MACE), which was defined as composite of cardiac death, myocardial infarction (MI) and ischemic-driven target lesion revascularization (ID-TLR), at 12-month follow-up. Results: Out of 362 patients included, 170 (47.0%) were diabetic and 159 (43.9%) were hypertensive. The mean age of all patients was 61.09 ± 9.04 years. A total of 625 lesions were identified; out of which 402 lesions were intervened successfully using BioMime Morph. The cumulative incidence of MACE was 7 (2.0%) at 12-month follow-up which included four (1.1%) cardiac deaths, one (0.3%) case of MI and two (0.6%) ID-TLR. Acute stent thrombosis was reported in one (0.3%) patient. Conclusions: The present study confirms the safety and performance of BioMime Morph, and hence, can be considered as a treatment of choice for long diffused tapered de novo coronary lesions in routine clinical practice. Cardiol Res. 2018;9(6):350-357 doi: https://doi.org/10.14740/cr795 Â
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 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".