A.2 Corticosteroid management in neuromuscular disease: a Canadian Survey
Bibliographic record
Abstract
Background: Systemic corticosteroids (CS) are first-line therapy for many neuromuscular diseases. Although long-term use is associated with many adverse effects, guidelines regarding prevention and management of CS-induced (CSI) complications in neurology are lacking, introducing potential practice variation. We aimed to evaluate Canadian neuromuscular neurologist practices for screening and management of CSI complications. Methods: A web-based anonymous questionnaire was disseminated to 99 Canadian neuromuscular neurologists addressing the screening, prevention, monitoring and treatment of CSI adverse effects, such as infection and osteoporosis. Results: 71% completed the survey. Of those, 52% perform screening blood work prior to initiating CS, 56.3% screen for infections, and 18.3% for osteoporosis. The majority monitor glycemic control and blood pressure. 28.6% never use pneumocystis jiroveci pneumonia prophylaxis, and 28.6% routinely recommend vaccinations prior to CS initiation (most commonly influenza and pneumococcal). 80.0% recommended calcium supplementation to prevent osteoporosis. 36% were unaware of any existing guidelines for preventing CSI complications, and 91% endorsed a need for neurology-specific guidelines. Additional data and details of responses will be presented. Conclusions: There is substantial variability in the management of CSI adverse effects among neuromuscular neurologists. This suggests a need for neurology-specific guidelines to help standardize practice.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".