Bioprostheses and Mechanical Prostheses Predictors of Performance
Bibliographic record
Abstract
From 1975 to 1995, 4200 patients had bioprosthetic valve replacements (2240 aortic, 1607 mitral, 353 multiple) and 2038 had mechanical valve replacements (747 aortic, 928 mitral, 363 multiple). Freedom from major thromboembolism or both major thromboembolism and hemorrhage for aortic and mitral valve replacement at 15 years was significantly greater for bioprostheses than mechanical prostheses. Freedom from valve-related mortality and reoperation for both aortic and mitral valve replacements was the same for bioprostheses and mechanical prostheses. Advancing age increased overall mortality (all positions), valve-related mortality (aortic, mitral), major thromboembolism (aortic), thromboembolism and hemorrhage (aortic, mitral) but decreased reoperation (all positions). Coronary artery bypass grafting increased overall mortality (aortic, mitral) but not valve-related mortality, and it decreased reoperation rate (aortic, mitral). Overall mortality was not influenced by valve type in aortic or multiple valve replacement but it was decreased by bioprostheses in mitral valve replacement. Valve type did not influence valve-related mortality (all positions). Mechanical valves decreased reoperation only for aortic valve replacement but they increased major thromboembolism with and without hemorrhage for both aortic and mitral replacements. There is support for bioprostheses in aortic valve replacement and mechanical prostheses in mitral valve replacement but for neither in multiple valve replacements.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".