Long-Term Follow-Up of Percutaneous Coronary Intervention With Paclitaxel-Eluting Balloon Catheter
Bibliographic record
Abstract
Drug-eluting balloons currently constitute a therapeutic tool used in percutaneous coronary interventions (PCI). Long-term results remain unknown. We evaluated the prognosis of PCI using a second generation paclitaxel-eluting balloon (PEB) in real-world patients. We included all PCI with PEB in de novo or in-stent restenosis coronary lesions performed in our unit from March 2009 to March 2019. We assessed the composite of major adverse cardiovascular events (MACE) rate after a median follow-up of 42 months. Consecutive patients (n = 320) with 386 lesions were included; 46.9% presented with stable angina and 53.1% acute coronary syndromes; 52.6% of the lesions were in-stent restenosis and 47.3% de novo lesions with a mean diameter of 2.4 ± 0.5 mm. A bare metal stent was implanted in 6.7% and a drug-eluting stent in 8.5% of patients. The MACE rate was 8%: 10 (2.6%) cardiovascular deaths, 13 (3.4%) myocardial infarctions, and 16 (4.1%) target lesion revascularization. The all-cause death rate was 5.2%. No cases of thrombosis were recorded. In conclusion, PEB was a safe and effective tool to treat in-stent restenosis and de novo coronary lesions, especially small vessel disease, during long-term 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".