Aortic valve replacement in young and middle-aged adults: looking beyond the tree that hides the forest
Bibliographic record
Abstract
The ideal aortic valve substitute for young and middle-aged adults with aortic valve disease remains elusive. Owing to a longer anticipated life expectancy, these patients present a higher cumulative lifetime risk of prosthesis-related complications. Conventional prosthetic valves expose the young patient to the virtual inevitability of a reoperation in the case of bioprosthetic valves or the continuous hazards of thrombosis and bleeding in the case of mechanical valves. In the long run, this translates into excess mortality compared to the general population. The Ross procedure offers unique advantages and is the only operation that has shown the potential to restore a normal life expectancy in young and middle-aged adults with severe aortic valve disease. Despite these advantages, its use has declined dramatically in recent years due to concerns over technical complexity, perioperative complications, and longterm autograft failure. These concerns can be largely mitigated by adequate patient selection and careful attention to minute technical details. In the current era, the Ross procedure can be performed safely and reproducibly in centers of excellence. Furthermore, several recently published studies have demonstrated superior long-term outcomes with the Ross operation compared to mechanical aortic valve replacement in young and middle-aged adults. In this article, we argue that the under-use of the Ross operation represents a missed opportunity that is mainly driven by an excessive focus on perioperative outcomes at the expense of long-term results.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".