Intravenous immunoglobulin therapy for juvenile dermatomyositis: efficacy and safety.
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy of intravenous immunoglobulin (IVIG) for the treatment of juvenile dermatomyositis (JDM) in patients who were unresponsive to corticosteroids (steroid resistant or steroid dependent) or showed unacceptable toxicity. METHODS: A retrospective chart review of the course of all patients with JDM treated with IVIG who attended the Dermatomyositis Clinic at The Hospital for Sick Children, Toronto, Canada, from August 1986 to December 1996. RESULTS: Eighteen patients with JDM were treated with IVIG. Ten patients were taking additional 2nd line treatments, methotrexate, azathioprine, cyclosporine, and cyclophosphamide. The main indication for starting IVIG was the failure of steroid therapy to induce remission of JDM. Twelve patients showed clinical improvement with IVIG. In these patients, the corticosteroid dose was reduced by > 50% for > 3 months without clinical or biochemical flare. Nine of these 12 patients had IVIG alone as a 2nd line agent, whereas 3 patients were treated with additional agents. Six patients remained steroid dependent; they subsequently required multiple agents to induce remission of JDM. CONCLUSION: Most steroid dependent or steroid resistant patients in our clinic were able to markedly reduce their dose of corticosteroid with the addition of IVIG. Given the retrospective nature of our data and the fact that multiple agents were sometimes used together, it will be important to confirm these findings in a controlled trial.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".