Transplantation as disease modifying therapy in adults with inherited metabolic disorders
Bibliographic record
Abstract
Transplantation is an established disease modifying therapy in selected children with certain inherited metabolic diseases (IMDs). Transplantation of hematopoietic stem cells or solid organs can be used to partially correct the underlying metabolic defect, address life threatening disease manifestations (such as neutropenia) or correct organ failure caused by the disease process. Much less information is available on the use of transplantation in adults with IMDs. Transplantation is indicated for the same IMDs in adults as in children. Despite similar disease specific indications, the actual spectrum of diseases for which transplantation is used differs between these age groups and this is partly related to the natural history of disease. There are diseases (such as urea cycle defects and X-linked adrenoleukodystrophy) for which transplantation is recommended for selected symptomatic patients as a treatment strategy in both adults and children. In those diseases, the frequency with which transplantation is used in adults is lower than in children and this may be related in part to a reduced awareness of transplantation as a treatment strategy amongst adult clinicians as well as limited donor availability and allocation policies which may disadvantage adult patients with IMDs. Risks of transplantation and disease-specific prognostic factors influencing outcomes also differ with age. We review the use of transplantation as a disease modifying strategy in adults focusing on how this differs from use in children to highlight areas for future research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".