Cerebral palsy and bisphosphonates – and what can be learned from other types of secondary osteoporosis in children: A scoping review
Bibliographic record
Abstract
AIM: We aimed to improve bone health management of children with cerebral palsy (CP) by reviewing studies investigating bisphosphonate therapy in children with CP and other types of secondary osteoporosis. METHODS: We included trials on bisphosphonate treatment reporting any direct bone measurement or fracture outcome. All studies of patients with CP were included. We also included all controlled trials of children with secondary bone fragility as well as observational studies with ≥20 participants or at least 3 years of follow-up. Studies were assessed according to PRISMA guidelines using the RoB2-tool and the Newcastle-Ottawa Scale. RESULTS: We reviewed 1104 studies and found 37 eligible. Some studies were sufficiently homogeneous to include in a meta-analysis, and we found a 1-year effect on lumbar spine bone mineral density (BMD) Z-score of +0.65 after oral and + 1.21 after intravenous bisphosphonates in children with secondary osteoporosis. Further, data on adverse events and post-treatment follow-up were reviewed. Limitations were heterogeneity and small size of the included studies. CONCLUSION: Meta-analysis consistently showed significant BMD increases with bisphosphonates in children with secondary osteoporosis. Direct evidence of the effect of bisphosphonates on reducing fractures is lacking. We found no reports of long-term adverse events yet longer studies are needed.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".