Neurodevelopmental outcomes following hematopoietic cell transplantation for patients with severe combined immunodeficiency (SCID): A PIDTC study
Bibliographic record
Abstract
Hematopoietic cell transplantation (HCT) is a potentially curative treatment for severe combined immunodeficiency (SCID). Since the initiation of newborn screening (NBS), survival rates have improved significantly, but the impact of HCT upon neurodevelopment for patients with SCID requires more investigation. We performed a cross-sectional study of subjects with SCID in North America to assess the impact of NBS, transplant conditioning regimen, and genotype on neurodevelopmental outcomes after HCT. 69 subjects with SCID from 17 PIDTC centers (excluding those with ADA deficiency), ages 6-16 years, received comprehensive standardized neurodevelopmental testing of cognitive, behavioral, and emotional function. Compared with the normative population, our subjects performed in the average range. We found no impact of NBS, chemotherapy conditioning, or genotype. Multivariate analysis revealed a significant decrease in IQ in subjects whose families earned <$50,000 per year. We recommend that children treated by HCT for SCID be monitored with periodic cognitive and behavioral assessments for deficits that could potentially impact long-term ND outcomes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".