Long-term developmental progression in infants and young children taking sapropterin for phenylketonuria: a two-year analysis of safety and efficacy
Bibliographic record
Abstract
PURPOSE: Sapropterin is an oral synthetic formulation of tetrahydrobiopterin prescribed as adjunctive therapy for phenylketonuria. The efficacy of sapropterin in reducing blood phenylalanine levels has been demonstrated in clinical studies of individuals with phenylketonuria older than 4 years of age. Its effect on neurocognitive functioning in younger children has not been examined. METHODS: A 2-year interim analysis of blood phenylalanine levels, prescribed dietary phenylalanine intake, and neurocognitive functioning was performed in children who started receiving sapropterin at 0-6 years of age and responded with a ≥30% mean blood phenylalanine reduction. Children were evaluated at baseline and 2-year follow-up. RESULTS: Sapropterin had a favorable safety profile and lowered blood phenylalanine levels with increased prescribed dietary phenylalanine intakes. Mean full-scale intelligence quotient was 103 ± 12 at baseline and 104 ± 10 at 2-year follow-up (P = 0.50, paired t-test, n = 25). For children younger than 30 months of age, the cognitive composite score from the Bayley Scales of Infant and Toddler Development, Third Edition, remained within the average range. CONCLUSION: Sapropterin had a favorable safety profile, was effective in lowering blood phenylalanine levels while clinically requiring dietary adjustment, resulting in increased phenylalanine intake, and preserved neurocognitive performance in children who started therapy between 0 and 6 years of age.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".