A Case of Pyoderma Gangrenosum Misdiagnosed as Necrotizing Infection: A Potential Diagnostic Catastrophe
Bibliographic record
Abstract
In this article, we present a case of pyoderma gangrenosum (PG), misdiagnosed initially as a necrotizing infection that significantly worsened due to repeated surgical debridement and aggressive wound care therapy, almost resulting in limb amputation despite antibiotic therapy. The PG lesions improved after pancytopenia were further investigated, and the diagnosis and treatment of an underlying hematologic malignancy was initiated. The diagnosis and management of PG is challenging given the paucity of robust clinical evidence, lack of standard diagnostic criteria, and absence of clinical practice guidelines. It is imperative that clinicians recognize PG as a clinical diagnosis that must be considered in any patient with enlarging, sterile, necrotic lesions that are unresponsive to prolonged and appropriate antibiotics. Early recognition can prevent devastating sequelae such as deep tissue and bone infections associated with a chronic open wound, severe cosmetic morbidity, and potential limb amputation.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.005 |
| 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".