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Record W3086312934 · doi:10.1016/j.jcol.2020.07.004

Fournier’s gangrene by perianal abscess

2020· article· en· W3086312934 on OpenAlexaff
Natiele Santos de Souza, Djoney Rafael dos Santos, André Pereira Westphalen, Fernando Antônio Campelo Spencer Netto

Bibliographic record

VenueJournal of Coloproctology · 2020
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsRoyal College of Physicians and Surgeons of Canada
Fundersnot available
KeywordsMedicineGangreneSepsisPerianal AbscessComorbidityAbscessSurgeryMedical recordDiabetes mellitusRetrospective cohort studyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Objective To describe and analyze the cases of Fournier’s Gangrene caused by perianal abscess treated in a tertiary hospital in western Paraná, correlating possible factors that influence mortality, with emphasis on late diagnosis and therapy. Methods A retrospective and descriptive case series was carried out based on the analysis of medical records of patients with Fournier’s Gangrene due to perianal abscess from January 2012 to December 2017. Results Thirty-one patients with Fournier’s Gangrene due to perianal abscess were treated in the period: 26 men and 5 women. Mean age was 53.51 ± 14.5 years. The most prevalent comorbidity in this group was type 2 diabetes mellitus, showing a strong correlation with mortality. The mean time from disease progression, from the initial symptom to the admission at the service, was 9.6 ± 6.81 days. All patients were submitted to antibiotic therapy and surgical treatment, with a mean of 3.25 ± 2.89 procedures/patient. Seven (22.58%) patients died and all of them showed signs of sepsis on admission; only 2 patients with sepsis did not die. Conclusion The presence of sepsis on admission and type 2 diabetes mellitus were strongly correlated with mortality.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.295
Teacher spread0.271 · 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 teacher head, not a consensus.

Study designObservational
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

Citations6
Published2020
Admission routes1
Has abstractyes

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