MétaCan
Menu
Back to cohort
Record W187612070

Intravenous immunoglobulin therapy for juvenile dermatomyositis: efficacy and safety.

2000· article· en· W187612070 on OpenAlexaffabout
Sulaiman M. Al‐Mayouf, R M Laxer, Rayfel Schneider, Earl D. Silverman, B. M. Feldman

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineJuvenile dermatomyositisDermatomyositisAzathioprineMethotrexateCyclophosphamideRetrospective cohort studyCorticosteroidInternal medicineSurgeryChemotherapyDisease
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.220
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations119
Published2000
Admission routes2
Has abstractyes

Explore more

Same venuePubMedSame topicInflammatory Myopathies and DermatomyositisFrench-language works237,207