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Record W4388836306 · doi:10.3121/cmr.2023.1837

Primary Epiploic Appendagitis: A Mimicker of Abdominal Pain

2023· article· en· W4388836306 on OpenAlexaff
Matthew Patel, Imran Haider, Andrew Cheung

Bibliographic record

VenueClinical Medicine & Research · 2023
Typearticle
Languageen
FieldMedicine
TopicOmental and Epiploic Conditions
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineAbdominal painGeneral surgeryFamily medicineOptometryLibrary scienceSurgery

Abstract

fetched live from OpenAlex

Epiploic appendagitis is a rare cause of acute lower abdominal pain. Epiploic appendices are fat-filled serosal outpouchings of the cecum and sigmoid colon. Primary epiploic appendagitis (PEA) is characterized by epiploic inflammation caused by torsion of the appendage leading to ischemia or thrombosis of the appendage draining vein. Secondary epiploic appendagitis occurs in association with other inflammatory conditions of the abdomen or pelvis, most commonly diverticulitis. PEA is an important clinical mimicker of more severe causes of acute abdominal pain, such as diverticulitis, appendicitis, or gynaecological causes. The ease of access to computed tomography (CT), the diagnostic test of choice, has resulted in increased recognition of PEA. The classic CT findings of PEA are an ovoid mass measuring between 1.5 and 3.5 cm surrounded by a hyperattenuating/hyperdense ring with a centrally located hyperdense area. It is important to diagnose PEA as it is self-limiting and the correct diagnosis can prevent unnecessary hospital admission, antibiotic use, or even surgical intervention. We present a case of a 65-year-old male with a history of diverticulitis, presenting with left lower quadrant abdominal pain who was diagnosed with PEA based on CT and successfully managed with conservative treatment.

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)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0020.002
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 head0.321
GPT teacher head0.554
Teacher spread0.233 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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