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Record W6962150158 · doi:10.15953/j.ctta.2023.017

The Diagnosis of Cronkhite-Canada Syndrome with CT Enterography: A Clinical Case Analysis

2023· article· en· W6962150158 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMalabsorptionAnemiaDiarrheaEndoscopyComputed tomographyEnteropathy

Abstract

fetched live from OpenAlex

Cronkhite-Canada syndrome (CCS) is a rare cause of chronic diarrhea and malabsorption where patients develop multiple polyps throughout the gastrointestinal (GI) tract, accompanied by ectodermal changes. Due to its rarity, its early detection and diagnosis can be challenging for physicians. This case report described a 58-year-old male patient with CCS who presented with chronic watery diarrhea, hematochezia, weight loss, and skin changes including nail dystrophy and hyperpigmen-tation. Laboratory results showed anemia and hypoalbuminemia. He underwent CT enterography (CTE) which identified diffuse edematous polyposis in the GI tract. The CTE results were highly suspicious of CCS and a subsequent endoscopic examination confirmed the diagnosis. The patient received supportive treatment which improved his symptoms. Based on CTE and endoscopy at 1-year follow-up, the patient was deemed to be in remission. We included a literature review of CCS. The case report aimed to improve the understanding of CCS and explored the key CTE features relevant to its early diagnosis.

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.265
GPT teacher head0.569
Teacher spread0.304 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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