Combination Oral Prednisone and Intravenous Immunoglobulin in the Treatment of Scleromyxedema
Bibliographic record
Abstract
Scleromyxedema is a clinical variant of the rare disease papular mucinosis that has both cutaneous and systemic manifestations. Treatment options are numerous and tend to be associated with serious potential side effects and frequent relapse. We report a case of scleromyxedema treated with low-dose oral prednisone and intravenous immunoglobulin (IVIg). This is followed by a review of the literature. IVIg is being used for a growing number of inflammatory and immune disorders. It is being increasingly reported as a successful treatment for scleromyxedema. Although our patient succumbed to the disease, combination therapy with prednisone and IVIg provided temporary symptomatic, laboratory, and clinical improvement of the condition. Optimization of this therapeutic strategy is thus indicated for the management of scleromyxedema. Le scléromyxoedème est une variante clinique de la maladie rare mucinose papuleuse dont les manifestations sont à la fois cutanées et systémiques. Les options de traitement sont nombreuses et souvent associées é des effets secondaires graves et à des récidives fréquentes. Nous rapportons un cas de scléromyxoedème traité avec de faibles doses de prednisone oral et d’immunoglobuline intraveineuse. Par la suite, nous passons en revue les publications scientifiques. L’immunoglobuline intraveineuse est utilisée dans le traitement d’un. nombre de plus en plus élevé de maladies inflammatoires et auto-immunes. Les rapports sont de plus en plus fréquents sur son efficacité dans les cas de scléromyxoedème. Bien que patiente n’ait pas survécu à sa maladie, la polythérapie au prednisone et àl’immunoglobuline intraveineuse a permis une amélioration temporaire au niveau des symptômes ainsi que des résultats cliniques et de laboratoire. Ainsi, l’optimisation de cette thérapie est recommandée dans la gestion du scléromyxoedème.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".