Azacitidine-Induced Pyoderma Gangrenosum at Injection Sites in a Patient with Myelodysplastic Syndrome
Bibliographic record
Abstract
Pyoderma gangrenosum (pg) is a rare neutrophilic dermatosis characterized by painful necrotic ulceration affecting preferentially the lower extremities. Diagnosis is challenging, and a thorough workup (including biopsy) is required. In this case report, we describe a 67-year-old patient with a diagnosis of myelodysplastic syndrome (mds) who developed fever and pg two days after the first cycle of subcutaneous azacitidine (Vidaza; Celgene Corporation, Summit, NJ, USA). On physical examination, the patient had four erythematous plaques at sites of subcutaneous injections of azacitidine on the arms, as well as three other plaques in proximity. A skin biopsy demonstrated a dense neutrophilic interstitial infiltrate in the dermis. After the diagnosis of pg, prednisone 1 mg/kg was started and the fever subsided rapidly. This was followed by the resolution of the cutaneous lesions. Changing the route of administration of azacitidine from subcutaneous to intravenous and adding a daily dose of prednisone during the treatment allowed the patient to receive a total of 10 cycles of azacitidine. This is the second case reported in the literature. Because azacitidine is frequently used in mds and acute myeloid leukemia, clinicians should be aware of this rare cutaneous adverse event. Our approach can be used to avoid the recurrence of pg when continuing azacitidine treatment.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".