A Retrospective Review of Bone Health Screening of at-risk Children and Adolescents: A Single Center Experience
Bibliographic record
Abstract
Abstract Background Bone health surveillance that includes laboratory tests and dual-energy x-ray absorptiometry (DXA) for patients with conditions that predispose them to a higher risk of osteoporosis is recommended. This study aimed to review current practice of such surveillance in a local tertiary referral centre. Methods Retrospective review of clinical data of patients who underwent DXA from 2013 to 2017 inclusive. Laboratory test results and presence of osteoporotic risk which was defined as bone mineral density (BMD) Z-score -2 SD or less were documented.Results This review consisted of 112 patients, 58 boys and age ranged from 1.1 to 20.3 years. Most referrals for DXA came from the subspecialty of nephrology (56.3%). Vitamin D status was rarely evaluated in this cohort of patients, only 17.9% of subjects had their vitamin D level checked. Overall, osteoporotic risk was demonstrated in 37% of the subjects. Thalassaemia, other haematological diseases like chronic ITP, osteogenesis imperfecta and inflammatory bowel disease accounted for majority of cases with high risk of osteoporosis.Conclusion DXA is underutilized in this center. Bone health surveillance and protection should be strengthened.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".