Metabolic Control and Growth during Exclusive Growth Hormone Treatment in X-Linked Hypophosphatemic Rickets
Bibliographic record
Abstract
BACKGROUND: GH may improve phosphate balance and height in X-linked hypophosphatemic rickets (XLH). This study evaluated the impact of exclusive rhGH therapy on phosphate homeostasis and growth. METHODS: Ten children (median age 12.2 years) with XLH were included in a 12-month trial with GH. Conventional treatment was discontinued 1 month prior GH (0.033 mg/kg/day); 1alpha-hydroxyvitamin D was added at 6 months and oral phosphate at 12 months, when GH was discontinued. Patients were followed 1-3 monthly until 18 months for clinical, biochemical and radiographic parameters. RESULTS: Serum phosphate Z-score increased significantly from baseline at 6 months (p = 0.005) and 9 months (p = 0.009) but returned to baseline by 12 months. Serum 1,25-dihydroxyvitamin D also increased significantly. Parathyroid function normalized. The median height Z-score was -2.2 (-2.7 to +0.4) at GH onset and -1.7 (-2.3 to +0.3) at 12 months. One patient showed a significant increase in radiographic rickets activity and 3 patients aggravation of lower limb deformity; the others showed no changes or improvement in these parameters. CONCLUSIONS: GH treatment improved serum phosphate and 1,25-dihydroxyvitamin D, normalized parathyroid function and improved longitudinal growth in XLH. It may however aggravate pre-existing skeletal deformities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".