Diagnosis and Management of Osteopetrosis: Consensus Guidelines From the Osteopetrosis Working Group
Bibliographic record
Abstract
Background: Osteopetrosis encompasses a group of rare metabolic bone diseases characterized by impaired osteoclast activity or development, resulting in high bone mineral density. Existing guidelines focus on treatment of the severe infantile forms with hematopoietic cell transplantation (HCT) but do not address the management of patients with less severe forms for whom HCT is not the standard of care. Therefore, our objective was to develop expert consensus guidelines for the management of these patients. Methods: A modified Delphi method was used to build consensus among participants of the Osteopetrosis Working Group, with responses to an anonymous online survey used to identify areas of agreement and conflict and develop a follow-up survey. The strength of recommendations and quality of evidence was graded using the Grading of Recommendations Assessment, Development and Evaluation system. Results: Consensus was found in the areas of diagnosis, monitoring, and treatment. We recommend relying on characteristic radiographic findings to make the diagnosis and found that genetic testing adds important information by identifying mutations associated with unique disease complications. We recommend ongoing monitoring for changes in mineral metabolism and other complications, including cranial nerve impingement, anemia, leukopenia, and dental disease. We suggest that calcitriol should not be used in high doses and instead recommend symptom-based supportive therapy for disease complications because noninfantile osteopetrosis has no effective treatment. Conclusions: Scarcity of published studies on osteopetrosis reduce the ability to develop evidence-based guidelines for the management of these patients. Expert opinion-based guidelines for this rare condition are nevertheless important to enable improved care.
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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 | 0.096 | 0.161 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.014 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".