Positive Linear Growth and Bone Responses to Growth Hormone Treatment in Children With Types III and IV Osteogenesis Imperfecta: High Predictive Value of the Carboxyterminal Propeptide of Type I Procollagen
Bibliographic record
Abstract
Extreme short stature is a cardinal feature of severe osteogenesis imperfecta (OI), types III and IV. We conducted a treatment trial of growth hormone in children with OI and followed linear growth velocity, bone metabolism markers, histomorphometrics, and vertebral bone density. Twenty-six children with types III and IV OI, ages 4.5-12 years, were treated with recombinant growth hormone (rGH), 0.1-0.2 IU/kg per day for 6 days/week, for at least 1 year. Length, insulin-like growth factor (IGF-I), insulin-like growth factor binding protein (IGFBP-3), bone metabolic markers, and vertebral bone density by DXA were evaluated at 6-month intervals. An iliac crest biopsy was obtained at baseline and 12 months. Approximately one-half of the treated OI children sustained a 50% or more increase in linear growth over their baseline growth rate. Most responders (10 of 14) had moderate type IV OI. All participants had positive IGF-I, IGFBP-3, osteocalcin, and bone-specific alkaline phosphatase responses. Only the linear growth responders had a significant increase in vertebral DXA z-score and a significant decrease in long bone fractures. After 1 year of treatment, responders' iliac crest biopsy showed significant increases in cancellous bone volume, trabecular number, and bone formation rate. Responders were distinguished from nonresponders by higher baseline carboxyterminal propeptide (PICP) values (p < 0.05), suggesting they have an intrinsically higher capacity for collagen production. The results show that growth hormone can cause a sustained increase in the linear growth rate of children with OI, despite the abnormal collagen in their bone matrix. In the first year of treatment, growth responders achieve increased bone formation rate and density, and decreased fracture rates. The baseline plasma concentration of PICP was an excellent predictor of positive response.
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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 | 0.000 | 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 | 0.000 |
| 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".