Transcatheter Aortic Valve Durability: Focus on Structural Valve Deterioration
Bibliographic record
Abstract
Transcatheter aortic valve replacement has emerged as a valuable alternative to surgical aortic valve replacement in patients with severe aortic stenosis. Given the expansion of transcatheter aortic valve replacement to lower-risk and younger populations with longer life expectancy, the durability of transcatheter heart valves (THVs) has become an important issue that may impact cardiovascular outcomes. THVs share similarities with surgical valves but have unique features, including a trend to larger effective orifice area and less prosthesis-patient mismatch, interactions with the native valve, and crimping process, that may all potentially influence a THV's life span. Multiple mechanisms may lead to bioprosthetic valve dysfunction, including structural valve deterioration, thrombosis, endocarditis, and nonstructural valve deterioration. With an incidence of up to 12.3% 5 years after transcatheter aortic valve replacement, structural valve deterioration represents the ultimate consequence of fibrotic remodeling and calcification within the bioprosthesis, driven by thrombotic and inflammatory processes involving the native aortic valve and influenced by patient and procedural factors. Understanding these mechanisms is crucial for improving THV durability.
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.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".