Hematopoietic Stem Cell Transplantation for Inherited Metabolic Diseases: An Overview of Long-Term Outcomes in A Single Pediatric Centre
Bibliographic record
Abstract
Over the past two decades, hematopoietic stem cell transplantation (HSCT) has been utilized as effective therapy for selected inherited metabolic diseases (IMD's). The primary objective of HSCT for these disorders has been to promote long-term survival, optimize quality of life and improve neuro-cognitive performance. Between 1990–2007, in the Hospital for Sick Children in Toronto, Canada, we performed 39 HSCT's for IMD's (10 related and 29 unrelated); 22 HSCT's for 21 children with Hurler syndrome, 8 for malignant infantile osteopetrosis, 6 for X- linked adrenoleukodystrophy (ALD), 2 for Gaucher's syndrome, 1 for gangliosidosis, 1 for sialiosis type 1 and 1 HSCT for Neiman-Pick type 1A. Busulfan (BU), cylophosphamide (CY) and single dose (300cGy) total body irradiation (TBI) were used as a conditioning regimen in 33 patients and 6 patients, in recent years of the study, received BU/CY and thymoglobulin. At a median follow up of 5.6 years (range 1.3–15.6 years) 18/21 patients with Hurler syndrome are alive. Educational status was determined in 16 of them; 14 attended regular schools, some with educational assistants, 1 attended a special needs school and 1 attended day-care. As of the last follow-up, 13/18 were ambulatory, 2 had some mobility difficulties and 1 was wheelchair-bound. For non-Hurler's, two children, 1 with osteopetrosis and 1 with ALD suffered secondary graft failure and died from progressive disease. The remaining children with osteopetrosis are alive and most children attended regular school or education for the visually handicapped. One out of the five survivors with ALD has been transferred to the adult follow up clinic and he is in full time employment. The patient with Neiman Pick type 1A progressed despite durable engraftment. Conclusion: These findings confirm that results and long-term follow up of allogeneic HSCT in these serious and lethal IMD's are very encouraging and long term, independent and meaningful survival, is possible.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".