Metabolic Control and Frequency of Clinical Monitoring Among Canadian Children With Phenylalanine Hydroxylase Deficiency: A Retrospective Cohort Study
Bibliographic record
Abstract
ABSTRACT Achieving and maintaining metabolic control is critical for children with phenylalanine hydroxylase (PAH) deficiency. This retrospective longitudinal cohort study investigated metabolic control and monitoring frequency of children with PAH deficiency (≤ 12 years) treated at one of 12 pediatric metabolic centres across Canada. We abstracted data from medical charts and analyzed outcomes by age and diagnostic classification, using mixed effects regression. Of 215 children included in the study, 43% had a chart diagnosis of classic phenylketonuria (PKU); the remainder had a diagnosis of mild PKU or mild hyperphenylalaninemia (grouped as “less severe PAH deficiency”). During the first month of life, blood phenylalanine levels of children with classic PKU reached the target therapeutic range of 120–360 μmol/L at a median age of 15 days, but 74.3% and 32.9% had ≥ 1 and ≥ 3 values below 120 μmol/L, respectively. From age > 1 month to 12 years, mean blood phenylalanine values were 260.6 and 236.7 μmol/L for children with classic PKU and less severe PAH deficiency, respectively, with a trend of increased blood phenylalanine levels with increasing age (p < 0.001). Fewer children with classic PKU (37.2%) versus less severe PAH deficiency (77.9%) had > 60% of values in the therapeutic range, indicating less optimal metabolic control. Frequency of blood phenylalanine testing and communication with metabolic centres decreased with age. Our findings suggest a need to better understand the reasons for blood phenylalanine variability across child age and disease severity in order to inform supports for children with PAH deficiency and their caregivers to maintain metabolic control.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".