First presentation of Sneddon-Wilkinson disease with unexpected immunoglobulin A gammopathy: A case report and review of the literature
Bibliographic record
Abstract
We present a case of Sneddon-Wilkinson disease in a 52-year-old female at her first presentation to dermatology. Outlined in the case are various investigations undertaken at this initial presentation, including rheumatologic and hematologic malignancy markers, which identified immunoglobulin A gammopathy. The systemic and topical therapies used to treat the patient's condition are described, as well as her response to these treatments. In this discussion, we explain the epidemiology, pathophysiology, and clinical presentation of Sneddon-Wilkinson disease. Various medical conditions having known association with Sneddon-Wilkinson disease are discussed, including immunoglobulin A or immunoglobulin G monoclonal gammopathies and lymphoproliferative disorders. A comprehensive differential diagnosis for Sneddon-Wilkinson disease is provided, including immunoglobulin A pemphigus, acute generalized exanthematous pustulosis and pustular psoriasis, among others. We describe the systemic and topical therapy options for the treatment of Sneddon-Wilkinson disease, of which first line treatment is systemic dapsone. This patient serves as an excellent case of Sneddon-Wilkinson disease with unexpected immunoglobulin A gammopathy.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".