Lobular panniculitis at the site of glatiramer acetate injections for the treatment of relapsing‐remitting multiple sclerosis. A report of two cases
Bibliographic record
Abstract
Lipoatrophy and localized panniculitis have been described as rare complications of daily subcutaneous glatiramer acetate injections for the treatment of relapsing-remitting multiple sclerosis (MS). We describe the biopsies from two MS patients in a single neurologist's practice who developed clinical lesions of lipoatrophy at the sites of subcutaneous glatiramer acetate injections. These biopsies showed a lobular panniculitis with lipoatrophy that more closely resembled lupus panniculitis than previous reports of localized panniculitis at glatiramer acetate injection sites. In one case, the area of clinical lipoatrophy continued to enlarge for 6 months after stopping glatiramer acetate therapy, before stabilizing at its current size for the last 8 months. Injection site reactions to glatiramer acetate should be considered in the differential diagnosis of biopsies that show a lupus panniculitis-like appearance. Our observations indicate that glatiramer acetate induced panniculitis is common and may continue to progress after therapy has stopped. In this single neurologist's practice, 64% of the patients receiving daily glatiramer acetate injections had clinical evidence of lipoatrophy or panniculitis. Of 100 consecutive patients receiving therapy for MS between February and November 2006, 14 patients were on glatiramer acetate, 9 of whom had clinical lipoatrophy.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".