Short and Long-Term Outcomes of Transcatheter Aortic Valve Implantation in the Small Aortic Annulus: A Systematic Literature Review
Bibliographic record
Abstract
Transcatheter aortic valve implantation has revolutionized the treatment of aortic stenosis. The small aortic annulus is one of the most challenging aspects of aortic stenosis treatment and since the beginning, TAVI has shown promising results in this subgroup of patients. This systematic literature review aims to investigate the short and long-term outcomes of TAVI in the small aortic annulus. The literature was meticulously screened for this topic until April 2024 using the PRISMA guidelines. Technical aspects, characteristics of this subgroup of patients, hemodynamic performances, and outcomes are discussed. The importance of device selection has shown up, with insight into the differences between self-expandable and the balloon-expandable valves. Two special populations were also taken into account: outcomes of TAVI in the small aortic annulus with bicuspid aortic valve and extra-small aortic annulus. The last 10 years have been paramount in technological advancements, bringing TAVI to broader use in this population. While several important trials underscored the usefulness of TAVI in the small aortic annulus population, the clinical practice still lacks consensus on the ideal device, and the outcomes are debated. The pivotal role of TAVI in this context needs to be addressed with a patient-tailored approach to optimize patient care.
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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".