Bone Health and Osteoporosis Management of the Patient With Duchenne Muscular Dystrophy
Bibliographic record
Abstract
Duchenne muscular dystrophy is associated with an increased risk of bone fragility due to the adverse effects of prolonged glucocorticoid therapy and progressive muscle weakness on bone strength. Osteoporosis manifests clinically as low-trauma long-bone and vertebral fractures (VFs), with VFs frequent, particularly in those treated with glucocorticoid therapy. It is increasingly recognized that bone pain, medical complications of osteoporosis (such as fat embolism syndrome), and the potential for permanent, fracture-induced loss of ambulation can be mitigated with timely bone health surveillance and management. This includes periodic spine radiographs for VF detection because VFs can be asymptomatic in their early phases and thereby go undetected in the absence of monitoring. With this article, we provide a comprehensive review of the following 4 phases of bone health management: (1) bone health monitoring, which is used to identify early signs of compromised bone health; (2) osteoporosis stabilization, which is aimed to mitigate back pain and interrupt the fracture-refracture cycle through bone-targeted therapy; (3) bone health maintenance, which has the goal to preserve the clinical gains realized during the stabilization phase through ongoing bone-targeted therapy; and (4) osteoporosis therapy discontinuation, which places those who are eligible for discontinuation of osteoporosis treatment back on a health monitoring program. In the course of reviewing these 4 phases of management, we will discuss the criteria for diagnosing osteoporosis, along with detailed recommendations for osteoporosis intervention including specific drugs, dose, length of therapy, contraindications, and monitoring of treatment efficacy and safety.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".