Paediatric heart transplantation: life-saving but not yet a cure
Bibliographic record
Abstract
In the 1980s, heart transplantation was the first successful treatment for infants born with hypoplastic left heart syndrome. Infants who have required heart transplantation benefit from immunologic "advantages," including long-term survival free from cardiac allograft vasculopathy. Currently ∼ 90% of children undergoing a heart transplant are reaching their first-year anniversary and the clinical practices of paediatric heart transplantation have dramatically improved. These successes are largely attributed to research sponsored by the Pediatric Heart Transplant Study Group, the International Society of Heart and Lung Transplantation and, more recently, the Non-profits Enduring Hearts and Additional Ventures. Despite these successes, the field is challenged to increase progress to achieve long-term survival into adulthood. The wait-list mortality, especially among infants, is unacceptably high often leading to palliative measures that can increase post-transplant mortality. Cardiac allograft vasculopathy remains a major cause for progressive graft loss of function and sudden death. The relative tolerance seen in immature recipients has not been translated to modifying older recipients' post-transplant outcomes. The modifiable cause(s) for the increased risks of transplantation in children of different ethnicities and races require definition. Addressing these challenges faces the reality that for-profit research favours funding adult recipients, with ∼ 10-fold greater numbers, and their more modest longevity goals. Advocacy for funding "incentives" such as the Orphan Drug rules in the United States and upholding principles of equity and inclusion are critical to addressing the challenges of paediatric heart transplant recipients worldwide.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.013 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".