Percutaneous coronary intervention for treating de-novo lesions in small coronary vessels
Bibliographic record
Abstract
BACKGROUND: Paclitaxel-coated balloon (PCB) coronary angioplasty is an alternative treatment for de-novo coronary lesions in small vessels. This study with the new Essential PCB aimed to evaluate early and mid-term clinical outcomes following angioplasty with the Essential PCB in the treatment of de-novo lesions in small vessels. PATIENTS AND METHODS: We included all patients who underwent PCB angioplasty for treating de-novo coronary lesions in small vessels (reference diameter <2.5 mm) between October 2015 and June 2016 in 2 centres. The primary endpoint was the 12-month target lesion failure (TLF) rate: a composite of cardiac death, target vessel-related myocardial infarction, and target lesion revascularization. The secondary endpoints were rates of target vessel failure and global major adverse cardiac events (MACE). RESULTS: A total of 71 patients (comprising 71 lesions) were included, with a mean age of 66±11 years. A 56% were diabetic and 70% had an acute coronary syndrome as an indication for coronary revascularization. The mean vessel diameter and lesion length were 2.21±0.41 and 20.7±9.2 mm, respectively. Predilatation was performed in 85.9% of patients. The median diameter, length, and inflation pressure of the Essential balloon were 2.0 [interquartile range (IQR): 2.0-2.5] mm, 20 (IQR: 15-30) mm, and 12±2 atmospheres, respectively. Angiographic success was achieved in 97.2% of cases, and bail-out stenting was required in nine (12.7%) cases. The incidence of TLF at the 12-month follow-up was 4.2%, with a target lesion revascularization rate of 4.2%. Target vessel failure and global MACE rates were 4.2 and 9.9%, respectively. CONCLUSION: Use of the Essential PCB for treating de-novo coronary lesions in small vessels was safe, with low TLF and MACE rates at the 12-month follow-up.
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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) | 0.000 | 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) | 0.002 | 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".