Sutureless aortic valves
Bibliographic record
Abstract
PURPOSE OF REVIEW: Sutureless aortic valve replacement (AVR) has emerged as an alternative to traditional AVR for patients with aortic stenosis who present a higher surgical risk, such as the elderly, or those with small or highly calcified aortic roots. With transcatheter aortic valve implantation - the other major AVR alternative - being used in increasingly lower-risk patients, the place of sutureless valves in the AVR landscape needs to be defined. In this review, we discuss recent data and expert opinion as it pertains to the subject of sutureless AVR. RECENT FINDINGS: Several recent studies have evaluated the performance of sutureless valves in a variety of clinical contexts, including minimally invasive operations and high-risk surgical procedures. The optimal surgical technique for sutureless AVR has been refined through the publication of several reports addressing technical considerations. Reduction in operative times represents the main advantage of sutureless valves over conventional surgical prostheses, and the possibility of complete annular decalcification - and hence a reduced incidence of paravalvular leak - is the primary advantage over TAVI. SUMMARY: Sutureless valves have emerged as an attractive option for high-risk patients or for complex surgeries where a minimization of bypass time is critical. However, there is limited data regarding long-term outcomes, durability or reoperation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".