Transcatheter aortic valve‐in‐valve implantation for failed surgical bioprosthetic valves. A minimalist approach without contrast aortography or echocardiographic guidance
Bibliographic record
Abstract
Abstract Objectives To demonstrate safety, feasibility and short‐term clinical outcomes after transcatheter aortic valve‐in‐valve (ViV) implantation under local anesthesia without contrast aortography or echocardiographic guidance. Background Transcatheter ViV implantation is an emerging treatment modality for patients with degenerative surgical bioprostheses. Given the radiopaque properties of the surgical aortic valve (SAV) frame, ViV procedures can often be performed with fluoroscopic guidance alone. Methods ViV implantation was performed in 37 patients with SAV failure under local anesthesia without contrast aortography. Clinical and echocardiographic data were obtained at baseline, discharge, and 30 days. Results Mean age was 74 ± 10 years and STS predicted risk of mortality was 5.6 ± 2.4%. Mean transaortic gradient decreased from 39.4 ± 15.5 mmHg to 13 ± 6.3 mmHg at discharge (p < .001), and 20 ± 7.5 mmHg at 30 days (p < .001 compared to baseline), aortic valve area increased from 0.9 ± 0.3 cm2 to 1.2 ± 0.4 cm2 at 30 days (p = .007). No patient had more than mild aortic regurgitation. Hospital discharge occurred at a median of 2.6 ± 4.4 days. At 30‐day follow‐up there were no deaths, myocardial infarctions, strokes, repeat hospital admissions for heart failure, or renal failure. One patient (2.7%) required a new pacemaker. 93% of the patients were in New York Heart Association functional class I or II. Conclusions Transcatheter aortic ViV implantation for selected patients with degenerative surgical bioprostheses under local anesthesia without aortography or echocardiographic guidance is feasible and safe.
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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 | 0.000 | 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) | 0.001 | 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".