Transcatheter Versus Surgical Aortic Valve Replacement in Young, Low-risk Patients with Severe Aortic Stenosis
Bibliographic record
Abstract
Aortic stenosis is a common form of acquired degenerative valvular disease associated with poor survival after the onset of symptoms. Treatment options for patients with aortic stenosis in addition to medical therapy include surgical aortic valve replacement (SAVR) with either tissue or mechanical valves, or transcatheter aortic valve replacement (TAVR) with either balloon-expandable or self-expanding valves via either transfemoral or alternative access routes. In this review, the authors discuss the current evidence and special considerations regarding the use of TAVR versus SAVR in the management of severe aortic stenosis in young (<65 years of age), low-risk patients, highlighting the history of aortic stenosis treatment, the current guidelines and recommendations, and important issues that remain to be addressed. Ultimately, until ongoing clinical trials with long-term follow-up data shed light on whether interventions for aortic stenosis can be broadened to a low-risk population, TAVR in young, low-risk patients should be undertaken with caution and with guidance from a multidisciplinary heart team.
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) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".