Bibliographic record
Abstract
PURPOSE OF REVIEW: Recently, there has been a renewed interest with regard to surgical strategies for aortic valve preservation in the presence of isolated valve disease or concomitant aortic root disease, despite concerns having been raised about the mid/long-term durability of such repair techniques for the aortic valve. The aim of the present review is to analyze the currently available evidence about aortic valve repair strategies, for either bicuspid or tricuspid valves. RECENT FINDINGS: An improved understanding of the surgical anatomy and functional analysis of the aortic valve and root has allowed a systematic classification for the mechanisms of aortic valve insufficiency. Similarly, the use of dedicated instruments and devices has led to improved outcomes in terms of not only long-term survival but also freedom from reoperation. SUMMARY: Aortic valve repair, either as a stand-alone procedure or especially in combination with surgery of the root, is a well-tolerated and effective procedure with excellent outcomes at mid/long term. Recent efforts allowed the refinement of surgical techniques to develop a systematic approach to aortic valve repair, which implies a thorough understanding of the surgical anatomy, the functional causes of disease, and the available repair techniques along with their potential limitations. A specialized team including dedicated surgeons and cardiologists appears to be crucial to achieve durable and satisfactory outcomes following aortic valve repair.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".