Long-Term Outcomes After Transcatheter Aortic Valve-in-Valve Replacement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Data on long-term outcomes after valve-in-valve (ViV) transcatheter aortic valve replacement (TAVR) are scarce. The objective of this study was to determine the long-term clinical outcomes and structural valve degeneration (SVD) over time in patients undergoing ViV-TAVR. Methods and Results: Consecutive patients undergoing ViV-TAVR in 9 centers between 2009 and 2015 were included. Patients were followed yearly, and clinical and echocardiography data were collected prospectively. SVD was defined as subclinical (increase >10 mm Hg in mean transvalvular gradient+decrease >0.3 cm 2 in valve area or new-onset mild or moderate aortic regurgitation) and clinically relevant (increase >20 mm Hg in mean transvalvular gradient+decrease >0.6 cm 2 in valve area or new-onset moderate-to-severe aortic regurgitation). A total of 116 patients (mean age, 76±11 years; 64.7% male; mean Society of Thoracic Surgeons score, 8.0±5.1%) were included. Balloon- and self-expandable valves were used in 47.9% and 52.1% of patients, respectively, and 30-day mortality was 6.9%. At a median follow-up of 3 years (range, 2–7 years), 30 patients (25.9%) had died, 20 of them (17.2%) from cardiovascular causes. Average mean transvalvular gradients remained stable up to 5-year follow-up ( P =0.92), but clinically relevant SVD occurred in 3/99 patients (3.0%), and 15/99 patients (15.1%) had subclinical SVD. One patient with SVD had redo ViV-TAVR. Conclusions: About one-fourth of ViV-TAVR recipients had died after a median follow-up of 3 years. Overall valve hemodynamics remained stable over time and clinically relevant SVD was infrequent, but 1 out of 10 patients exhibited some degree of SVD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.030 |
| 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