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Record W4407608292 · doi:10.14740/jcs482

Clinical Presentation, Diagnostic Approach, and Management of Symptomatic Gastrointestinal Lipomas

2025· article· en· W4407608292 on OpenAlexvenueno aff
Lefika Bathobakae, Heba Farhan, Tyler Wilkinson, Dina Rohira, Trevor Ruff, Nischal Sharma, Kamal Amer, Yana Cavanagh, Walid Baddoura

Bibliographic record

VenueJournal of Current Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePresentation (obstetrics)LipomaSurgeryCase presentationGeneral surgeryRadiology

Abstract

fetched live from OpenAlex

Gastrointestinal (GI) lipomas are a rare form of benign submucosal neoplasm composed of mature adipose tissue. These lesions can grow anywhere in the GI tract, with a higher prevalence observed in the colon and the small intestines. Owing to their relative rarity and asymptomatic nature, the true incidence and prevalence remain unknown. GI lipomas can present with dysphagia, abdominal pain, intestinal obstruction, or GI bleeding, prompting further workup and interventions. On computed tomography and magnetic resonance imaging, GI lipomas typically appear as ovoid/spherical, sharply demarcated, and homogeneously hypodense lesions. On endoscopy, lipomas appear as smooth mucosal protrusions and, rarely, with ulceration. In some cases, an endoscopic ultrasound may be used to confirm diagnosis, staging, or pre-operative planning. Asymptomatic lipomas are managed conservatively using periodic imaging or endoscopy. Symptomatic lipomas, however, require endoscopic or surgical resection, and endoscopic techniques are preferred because of their non-invasive nature. Surgery is typically reserved for giant lipomas or more complex cases. There is a paucity of data regarding the clinical features and management of symptomatic GI lipomas. The current evidence is retrospective, in the form of case reports and conference abstracts. In this review, we discuss the clinical presentation, diagnostic approach, and management of symptomatic GI lipomas.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.047
GPT teacher head0.362
Teacher spread0.316 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes1
Has abstractyes

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