Reoperation of Left Heart Valve Bioprostheses According to Age at Implantation
Bibliographic record
Abstract
BACKGROUND: Evidence supporting the use of bioprostheses for heart valve replacement in young adults is accumulating. However, reoperation data, which may help guide clinical decision making in young patients, remains poorly defined in the literature. METHODS AND RESULTS: We examined the need for reoperation in 3975 patients who underwent first-time bioprosthetic aortic valve replacement (AVR) (n=3152) or mitral valve replacement (MVR) (n=823). There were 895 patients below the age of 60 years at bioprosthesis implant (AVR, n=636; MVR, n=259). The median interval to reoperation of contemporary, stented aortic bioprostheses was 7.74 years (95% CI 7.28 to 9.97 years) in patients less than 40 years, and 12.93 years (95% CI 11.10 to 15.76 years) in patients between 40 and 60 years of age. Multivariable risk factors associated with reoperation following bioprosthetic AVR include age (hazard ratio [HR] 0.94 per year, 95% CI 0.91 to 0.96, P<0.001) and concomitant coronary artery bypass grafting (HR 0.34, 95% CI 0.11 to 0.99, P=0.04). The median interval to reoperation of contemporary mitral bioprostheses was 8.11 years (95% CI 5.79 to 16.50 years) in patients less than 40 years, and 10.14 years (95% CI 8.64 to 11.14 years) in patients between 40 and 60 years of age. As for AVR, age (HR 0.96 per year, 95% CI 0.95 to 0.98, P<0.001) and concomitant coronary artery bypass grafting (HR 0.55, 95% CI 0.32 to 0.93, P=0.03) were associated with decreased reoperation risk following bioprosthetic MVR. CONCLUSIONS: These data constitute clinically relevant age-specific prognostic information regarding reoperation in young patients, who may wish to select a bioprosthesis at initial left heart valve replacement.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".