Growth and disease burden in children with hypophosphatasia
Bibliographic record
Abstract
Objective: Hypophosphatasia, an inborn error of metabolism characterized by impaired bone mineralization, can affect growth. This study evaluated relationships between anthropometric parameters (height, weight, and body mass index) and clinical manifestations of hypophosphatasia in children. Design: Data from children (aged <18 years) with hypophosphatasia were analyzed from the observational Global Hypophosphatasia Registry. Methods: Anthropometric parameters were evaluated by age group (<2 years and ≥2 years) at assessment. The frequency of hypophosphatasia manifestations was compared between children with short stature (< percentile) and those with normal stature. Results: This analysis included 215 children (54.4% girls). Short stature presented in 16.1% of children aged <2 years and 20.4% of those aged ≥2 years at assessment. Among those with available data (n = 62), height was below the target height (mean: -0.66 standard deviations). Substantial worsening of growth (mean delta height z score: -1.45; delta weight z score: -0.68) occurred before 2 years of age, while in those aged ≥2 years, anthropometric trajectories were maintained (delta height z score: 0.08; delta weight z score: 0.13). Broad-ranging hypophosphatasia manifestations (beyond dental) were observed in most children. Conclusions: Short stature was not a consistent characteristic of children with hypophosphatasia, but growth impairment was observed in those aged <2 years, indicating that hypophosphatasia might affect growth plate activity during infancy. In addition, a broad range of clinical manifestations occurred in those above and below the third percentile for height, suggesting that height alone may not accurately reflect hypophosphatasia disease burden and that weight is less affected than longitudinal growth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".