Bibliographic record
Abstract
Once considered a burgeoning area of clinical care in children, osteoporosis in the young is now recognized as an important facet of child health with sufficient evidence to support standardized approaches to diagnosis, monitoring, treatment and prevention. Current management strategies are based on monitoring at-risk children to identify and treat early, rather than late, signs of osteoporosis in those with limited potential for spontaneous recovery. In patients with extremely high risk of fractures (such as glucocorticoid [GC]-treated Duchenne muscular dystrophy [DMD]), the fracture rates are so high and the potential for spontaneous (medication-unassisted) recovery so limited that strategies to prevent first-ever fractures are currently under consideration. This chapter focuses on the evidence that shapes the current approach to diagnosis, monitoring, and treatment of osteoporosis in childhood, with emphasis on the key paediatric-specific biological principles that are pivotal to the overall approach, and on the main questions with which clinicians are faced during routine care. The scope of this chapter is to review the manifestations of and risk factors for primary and secondary osteoporosis in children, to discuss the definition of paediatric osteoporosis, and to provide specific recommendations for monitoring and prevention. As well, this chapter reviews when a child is a candidate for osteoporosis therapy, which agents and doses should be prescribed, the duration of therapy, how the response to therapy is evaluated, and the short- and long-term side effects of current treatments. With this information, the bone health clinician will be poised to diagnose osteoporosis in children, to identify when children need osteoporosis therapy and for how long, the safe administration of osteoporosis treatment, and the clinical outcomes that gauge treatment efficacy.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".