Pyoderma gangrenosum as a possible paraneoplastic disease – case study and literature review
Bibliographic record
Abstract
Introduction: Pyoderma gangrenosum is a rare dermatosis characterised by a rapid course and uncertain prognosis.It poses a major therautic challenge in the daily dermatological practice, also to experienced medical practitioners.Pyoderma gangrenosum may coexist with autoimmune diseases, but it can also a paraneoplatic diseease associated with cancers of internal organs and myeloproliferative diseases.Case report: We present a 78-year-old woman with pyoderma gangrenosum hospitalised in the Clinical Department of Dermatology and to review the literature on the coexistence of pyoderma gangrenosum and neoplastic deseases of internal organ cancers.In our patient pyoderma gangrenosum was associated with duodenal thickening observed on computer tomography combined with a positive test for occult blood in the stool.It led to the suspicion of gastrointestinal malignancy.However the patient refused further diagnostic procedures.Conclusions: Multiple case studies and review articles point to a statistically significantly increased frequency of neoplatic diseases (both hematologic malignanciues and solid tumours) in patients with pyoderma Thus, a reasonable strategy is to perform cancer screening in patients with pyoderma gangrenosum.Not all patients consent to expand the diagnostic procedures to confirm or exclude the suspicion of a neoplastic disease.Key words: pyoderma gangrenosum, cancers of internal organs, diagnostic work-up, treatment.streszczenie Wprowadzenie: Piodermia zgorzelinowa jest rzadką dermatozą, o szybkim przebiegu, niepewnym rokowaniu i trudnym leczeniu.Stanowi istotne wyzwanie w codziennej pracy nawet doświadczonych dermatologów.Może współistnieć z chorobami autoimmunologicznymi, ale także stanowić rewelator nowotworów narządów wewnętrznych i chorób mieloproliferacyjnych.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".