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Record W3083838007 · doi:10.1093/jscr/rjaa282

Necrotizing fasciitis from perforated sigmoid diverticulitis with subsequent pyoderma gangrenosum: a case report

2020· article· en· W3083838007 on OpenAlexaff
Matthew G.K. Benesch, Angela S D Bussey

Bibliographic record

VenueJournal of Surgical Case Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicinePyoderma gangrenosumFasciitisDiverticulitisSurgeryDifferential diagnosisDermatologyAbscessDiseasePathology

Abstract

fetched live from OpenAlex

Postsurgical pyoderma gangrenosum is a very rare form of cutaneous ulceration that is poorly recognized outside of dermatology and in some circumstances has been mistaken for necrotizing fasciitis. Here, we present a rare case of sigmoid diverticulitis with left ureter obstruction that perforated and quickly progressed into necrotizing fasciitis of the left buttock and leg via retroperitoneal spread in an immunocompetent patient. Nearly a year after intense surgical therapy, the patient rapidly developed ulcerating lesions over the left hip which presented a diagnostic dilemma. These were initially thought to represent Marjolin's ulcers, which would require aggressive local excision. Multiple diagnostic imaging tests and biopsies eventually confirmed pyoderma gangrenosum, which was successfully treated with immunosuppressive therapy. This case highlights the need for a very broad differential diagnosis and wide expertise consultation when managing unusual postsurgical complications, especially when treatment modality critically depends on the correct diagnosis.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0040.003
Scholarly communication0.0040.004
Open science0.0020.004
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.020
GPT teacher head0.246
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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