Canadian Consensus Statement on the Use of Intravenous Immunoglobulin Therapy in Dermatology
Bibliographic record
Abstract
BACKGROUND: As a safe, well-tolerated, and potentially beneficial therapy, intravenous immunoglobulin (IVIG) has been increasingly used by dermatologists to treat immune-mediated skin disease. However, practical and comprehensive guidelines for the use of IVIG have yet to be established. OBJECTIVE: To develop the first Canadian consensus statement on the use of IVIG therapy in skin disease. METHODS: A group of Canadian dermatologists convened to discuss current issues in IVIG therapy. The participants reviewed and evaluated the literature and shared clinical experience. Using a modified Delphi process, a consensus statement was developed. RESULTS: Herein we provide a brief overview of pemphigus vulgaris, pemphigus foliaceus, bullous pemphigoid, mucous membrane pemphigoid, epidermolysis bullosa acquisita, Stevens-Johnson syndrome, and toxic epidermal necrolysis. Recommendations for the management of these diseases are detailed, and therapeutic algorithms for the treatment of various autoimmune mucocutaneous blistering diseases are presented. The appropriate use of IVIG therapy is placed in context for each disease. CONCLUSION: Although preliminary data suggest that IVIG is a safe and effective therapy for many skin disorders, uncontrolled clinical trials, case series, and anecdotal case reports dominate the literature. Collaborative randomized controlled trials are required to firmly establish the role of IVIG in dermatology.
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 | 0.040 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".