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Record W3127707579 · doi:10.1136/bcr-2020-237784

Fournier’s gangrene with dapagliflozin in a rural hospital: a case report

2021· article· en· W3127707579 on OpenAlexaff
Ali Elbeddini, Yasamin Tayefehchamani, Michelle Davey, Jodi Gallinger, Naushin Hooda, Ahmed Aly, D. Erickson, Stephanie J. Lee

Bibliographic record

VenueBMJ Case Reports · 2021
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsYork Central HospitalUniversity of WaterlooUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsDapagliflozinMedicineNecrotising fasciitisGangreneType 2 diabetesDiabetes mellitusSurgeryGenitourinary systemIncision and drainageFournier gangreneFasciitisAbscessInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Sodium-glucose cotransporter 2 (SGLT2) inhibitors, which are used for treatment of type 2 diabetes, are associated with risk of urogenital infections. FDA issued a black box warning about multiple case reports of Fournier's gangrene (FG) observed in patients taking SGLT2 inhibitors. FG is a type of necrotising fasciitis that occurs in the anogenital area. We report a case of a 71-year-old woman with type 2 diabetes on dapagliflozin, presenting with foul-smelling discharge and a large abscess in the perianal area. Her risk factors for FG included her advanced age, obesity, diabetes and trauma to the site. During her stay, dapagliflozin was discontinued and she received procedural debridement, wound care and broad-spectrum intravenous antibiotics. Due to possible association between FG and SGLT2 inhibitors, patients presenting with signs and symptoms of FG who are taking SGLT2 inhibitors should be examined for infection in the urogenital area and treated promptly.

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)0.000
metaresearch head score (Gemma)0.004
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 score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0040.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0060.005
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 head0.019
GPT teacher head0.323
Teacher spread0.303 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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