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Record W3097043363 · doi:10.1159/000510920

Cronkhite-Canada Syndrome Successfully Treated by Corticosteroids before Presenting Typical Ectodermal Symptoms

2020· article· en· W3097043363 on OpenAlexaboutno aff
Kazumoto Murata, Kiichi Sato, Shinya Okada, Daisuke Suto, Takaaki Otake, Yutaka Kohgo

Bibliographic record

VenueCase Reports in Gastroenterology · 2020
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFailure to thriveGastroenterologyEtiologyDermatologyInternal medicineHyperpigmentationDiarrheaHyperplastic PolypWeight lossStomachFamily historyColonoscopyColorectal cancerCancerObesity

Abstract

fetched live from OpenAlex

Cronkhite-Canada syndrome (CCS) is a rare disease characterized by diffuse gastrointestinal polyposis with chronic diarrhea and ectodermal change, but its etiology is unknown. We present a case at the age of 26 years complaining of epigastralgia and weight loss. Endoscopic examination revealed extensive diffuse polypoid lesions of the stomach and the terminal ileum, all of which showed hyperplastic polyps pathologically. There were no polypoid lesions in his colon. He has no family history of diffuse gastrointestinal polyposis. Diffuse gastrointestinal hyperplastic polyposis without any hereditary association led us to suspect this case as CCS although he did not show chronic diarrhea and any ectodermal symptoms such as onychodystrophy, alopecia, and hyperpigmentation. After initiation of a corticosteroid therapy, his epigastralgia disappeared and he gained appetite and weight, accompanied by normalization of serum albumin levels. Endoscopic examination 1 year after initiation of corticosteroid therapy revealed a decrease in the number of gastric polyposis and those inflammations. This rare young case may suggest that early therapeutic intervention with corticosteroids could improve the prognosis of CCS, preventing not only malnutrition but also appearance of several ectodermal symptoms.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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