Long-term Follow-up of a Patient With Eruptive Melanocytic Nevi After Stevens-Johnson Syndrome
Bibliographic record
Abstract
BACKGROUND: Eruptive melanocytic nevi (MN) are a rare phenomenon characterized by the simultaneous, abrupt onset of hundreds of MN, often in a grouped distribution. There are few studies on this topic in the literature. We followed up a patient who developed eruptive MN 38 years ago after Stevens-Johnson syndrome. Herein we document this patient's progress and review the literature on this unusual phenomenon. OBSERVATIONS: For 38 years, the patient's lesions have remained stable, without signs of malignant degeneration. We discuss the possible etiology and natural history of this condition in 2 major patient populations: those with bullous disorders and those with systemic immunosuppression. CONCLUSIONS: We postulate that the etiology and natural course of eruptive MN may differ between the 2 main populations of patients at risk for eruptive MN, with MN arising after bullous disorders being more likely to remain benign compared with those in patients with ongoing immunosuppression. However, this hypothesis has yet to be proved, and it will require long-term surveillance of individuals who have developed eruptive MN to determine its merit.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".