Adrenal Suppression in Duchenne Muscular Dystrophy: Management Strategies Incorporating Novel Steroid Vamorolone
Bibliographic record
Abstract
Adrenal suppression is an iatrogenic form of adrenal insufficiency that occurs secondary to exogenous glucocorticoids (GCs) and is a documented cause of premature mortality among individuals with Duchenne muscular dystrophy (DMD). Adrenal suppression in DMD necessitates awareness and careful management, given that GCs are currently the mainstay of therapy for individuals living with DMD. Vamorolone, a novel GC that has recently been approved in some regions worldwide for the treatment of DMD, has also been reported to place individuals at high risk of adrenal suppression in a dose-dependent fashion, requiring health care professional awareness. Vamorolone is a mineralocorticoid receptor antagonist, which differentiates it from classic GCs, and this characteristic impacts the approach to adrenal suppression management. This contemporary perspective provides insights into the mechanisms underlying adrenal suppression due to both classic GCs and novel vamorolone therapy, followed by an overview of adrenal suppression management with a particular focus on the unique aspects of providing care for individuals treated with vamorolone. It also emphasizes the importance of educating the DMD community and health care providers about the recognition and management of adrenal suppression and outlines critical concepts for clinicians managing adrenal suppression risk, tapering GCs, and transitioning from classic GC therapy to vamorolone. The key principles of managing adrenal suppression due to classic GCs and novel vamorolone therapy highlighted in this perspective are expected to enhance clinical practice, mitigate mortality, and optimize health outcomes for individuals with DMD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".