MétaCan
Menu
Back to cohort
Record W2997739414 · doi:10.18192/uojm.v9i2.4476

Bitter sweet: Fournier’s Gangrene and SGLT2 inhibitors

2019· article· en· W2997739414 on OpenAlexaffvenueabout
Coralea Kappel

Bibliographic record

VenueUniversity of Ottawa Journal of Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEmpagliflozinMedicineCanagliflozinDiabetes mellitusGangreneFood and drug administrationType 2 diabetesDapagliflozinIntensive care medicineDrug classDiseaseAdverse effectSurgeryInternal medicinePharmacologyDrugEndocrinology

Abstract

fetched live from OpenAlex

Diabetes mellitus, especially type 2 is becoming the biggest epidemic of the 21st century affecting more than 415 million adults globally and expected to increase to more than 640 million adults by 2040. Patients with diabetes are at high risk for adverse outcomes, notably cardiovascular disease with an increased risk of death. In fact, the 2018 Canadian Diabetes Association (CDA) guidelines have updated the type 2 diabetes management algorithm; if the patient has clinical cardiovascular disease, an antihyperglycemic agent with demonstrated cardiovascular (CV) benefit should be added. There is a growing armamentarium of therapies with Health Canada-approved CV benefit include two from the sodium-glucose co-transporter 2 (SGLT2) inhibitors class namely Canagliflozin and empagliflozin. Despite their many advantages, the Food and Drug Administration (FDA) issued a black box warning for associated necrotizing fasciitis of the perineum in diabetes treated with SGLT2 inhibitors. This case report highlights a case of Fournier’s gangrene (FG) in a male treated with empagliflozin for type 2 diabetes.

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)0.002
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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

Citations1
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueUniversity of Ottawa Journal of MedicineSame topicAutoimmune and Inflammatory DisordersFrench-language works237,207