A Contemporary View of the Definition and Diagnosis of Osteoporosis in Children and Adolescents
Bibliographic record
Abstract
The last 2 decades have seen growing recognition of the need to appropriately identify and treat children with osteoporotic fractures. This focus stems from important advances in our understanding of the genetic basis of bone fragility, the natural history and predictors of fractures in chronic conditions, the use of bone-active medications in children, and the inclusion of bone health screening into clinical guidelines for high-risk populations. Given the historic focus on bone densitometry in this setting, the International Society for Clinical Densitometry published revised criteria in 2013 to define osteoporosis in the young, oriented towards prevention of overdiagnosis given the high frequency of extremity fractures during the growing years. This definition has been successful in avoiding an inappropriate diagnosis of osteoporosis in healthy children who sustain long bone fractures during play. However, its emphasis on the number of long bone fractures plus a concomitant bone mineral density (BMD) threshold ≤ -2.0, without consideration for long bone fracture characteristics (eg, skeletal site, radiographic features) or the clinical context (eg, known fracture risk in serious illnesses or physical-radiographic stigmata of osteoporosis), inappropriately misses clinically relevant bone fragility in some children. In this perspective, we propose a new approach to the definition and diagnosis of osteoporosis in children, one that balances the role of BMD in the pediatric fracture assessment with other important clinical features, including fracture characteristics, the clinical context and, where appropriate, the need to define the underlying genetic etiology as far as possible.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.017 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".