Aortic valve replacement in younger patients
Bibliographic record
Abstract
This editorial refers to ‘Mechanical aortic valve replacement in non-elderly adults: meta-analysis and microsimulation’†, by N.M. Korteland et al., on page 3370. Aortic stenosis is the most common form of valvular heart disease in the developed world, and valve replacement is still the standard treatment. Mechanical valves are generally preferred over tissue valves for younger patients with aortic stenosis because of their greater durability. Information provided on The American Heart Association website suggests that most manufactured mechanical valves ‘will last throughout the remainder of the patients’ lifetime’,1 but the life expectancy of younger patients with aortic stenosis is almost halved at the time of valve implantation.2 In this issue of the journal, Takkenberg and colleagues explore outcomes after bi-leaflet mechanical aortic valve replacement in younger patients by performing a meta-analysis of 29 observational studies published between 1995 and 2015 that involved 5728 patients aged 18–55 years (mean age 48 years).3 Their pooled results indicate early (<30 days) mortality of 3.15% and late (>30 days) mortality of 1.55%/year (of which 38.7% were valve related); and annual rates of thrombo-embolism of 0.90%, major bleeding of 0.85%, non-structural valve dysfunction of 0.39%, endocarditis of 0.41%, valve thrombosis of 0.14%, and re-intervention of 0.51%. The pooled mean follow-up was only 5.7 years, but using a microsimulation model they estimated age-specific life expectancy and lifetime risk of valve-related morbidity. For example, they estimated that a 45-year-old undergoing mechanical valve replacement has a life expectancy of 19 years (compared with 34 years in the general population), and lifetime risk of thrombo-embolism, bleeding, and re-intervention of 18, 15, and 10%, respectively.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".