1-Year Outcomes following Bioprosthetic Valve Fracture to Facilitate Valve-in-Valve Transcatheter Aortic Valve Replacement
Why this work is in the frame
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Bibliographic record
Abstract
BackgroundBioprosthetic valve fracture (BVF) improves the hemodynamic results of valve-in-valve transcatheter aortic valve replacement (VIV TAVR) by facilitating optimal expansion of the transcatheter heart valve (THV). Long-term outcomes following BVF are unknown.MethodsConsecutive cases of VIV TAVR and BVF (n = 139) performed at 11 sites were analyzed retrospectively. Hemodynamic measurements and aortic valve area (AVA) were assessed during the procedure and by echocardiography at 30-day and 1-year follow-up.ResultsVIV TAVR and BVF resulted in significant improvements in mean valve gradient (42.3 ± 17.1 vs. 9.4 ± 5.8 mmHg, p < 0.001) and AVA (0.8 ± 0.4 vs. 1.8 ± 0.7 cm2, p < 0.001) compared with baseline. Mortality was 2.3% at 30 days and 8.7% at 1-year. In adjusted models, mean valve gradient was higher (+5.1 [3.7, 6.5] mmHg, p < 0.001) and AVA was lower (−0.3 [−0.4, −0.2] cm2, p < 0.001) at 1 month as compared to post-procedure. Between 30 days and 1 year, no significant changes in mean valve gradient (+1.4 [−0.5, 3.4] mmHg, p = 0.15) or AVA (−0.1 [−0.3, 0.03] cm2, p = 0.11) were observed. In a multivariable analysis, use of a CoreValve (compared with a SAPIEN) THV was an independent predictor of a lower mean valve gradient at 1 year (−6.0 mmHg, p = 0.01).ConclusionSurvival is excellent following VIV TAVR and BVF and valve hemodynamics are stable between 30-day and 1-year follow-up. CoreValve use is a predictor of better hemodynamic results following VIV TAVR and BVF.Abbreviations: VIV TAVR: valve-in-valve transcatheter aortic valve replacement; THV: transcatheter heart valve; BSV: bioprosthetic surgical valve; PPM: patient prosthesis mismatch; BVF: bioprosthetic valve fracture; IQR: interquartile range; LVEF: left ventricular ejection fraction; AVA: aortic valve area; STS PROM: Society of Thoracic Surgeons predicted risk of mortality
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.009 |
| 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 it