P914Balloon aortic valve valvuloplasty as palliative therapy in severe aortic valve stenosis: 10 years experience in a single centre
Bibliographic record
Abstract
Abstract Background Improved technology together with greater operator experience has led to refinement of balloon aortic valve valvuloplasty (BAV) in recent years. It may provide a palliative treatment option in high-risk patients, highly symptomatic, for whom no other invasive therapy is available. However, there has not been universal adoption of BAV as a standalone therapy. Methods A retrospective analysis of ten years of practice of BAV as palliative strategy in patient with symptomatic aortic stenosis between March 2008 and June 2018 was performed. Demographic, clinical, procedural, and follow-up data on all patients were collected. Results A total of 152 patients (95 women, 63%) with a mean age of 85±6 years underwent BAV. All patients had severe aortic stenosis, were considered not suitable to aortic valve replacement nor Trans-catheter aortic valve implantation (TAVI) for appreciable comorbidity (STS score 9±5) and had severe symptoms mainly of heart failure which required medical attention. A statistically significant decrease in trans-valvular gradient was observed (peak to peak gradient before BAV 52±22 mmHg, after BAV 29±16 mmHg, delta gradient 24±14 mmHg; p<0.0001). Only one patient, who undergone BAV because of cardiogenic shock, died during the procedure. Considering the high-risk population, intra-hospital mortality was low (7 patients died, 4%). Mortality at 1-year follow-up was 43% and survival free from new hospitalization for heart failure was 63% at 1-year follow-up and 53% at 2 years follow-up. 19 patients (13%) required repeated BAV during follow-up. Conclusion BAV as a palliative procedure in high-risk patients who are highly symptomatic, has a low operative mortality in our experience. BAV is associated with a significant reduction in aortic valve gradient and is valuable since half of the patients were alive without re-hospitalizations for heart failure at 2 years follow-up. Acknowledgement/Funding None
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".