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Recombinant Thrombomodulin Used to Successfully Treat Cronkhite-Canada Syndrome with Disseminated Intravascular Coagulation due to Sepsis in a Compromised Patient

2018· article· en· W2807415577 on OpenAlexaboutno aff
Kahori Morino, Yuichi Honma, Shinsuke Kumei, Tatsuyuki Watanabe, Keiichiro Kume, Ichiro Yoshikawa, Masaru Harada

Bibliographic record

VenueInternal Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDisseminated intravascular coagulationSepsisThrombomodulinDermatologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Cronkhite-Canada syndrome (CCS) is a rare non-inherited disease characterized by gastrointestinal polyposis, chronic diarrhea, ectodermal dysplasia, skin hyperpigmentation, hair loss and nail atrophy. Although the efficacy of corticosteroid and immunomodulatory agents has been demonstrated, no standard therapy regimen has been established, and the prognosis of CCS is still poor due to various complications. We here in report a CCS patient complicated with severe sepsis and disseminated intravascular coagulation who was successfully treated by combined modality therapies, including recombinant human soluble thrombomodulin.

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)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.269
Teacher spread0.257 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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