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Record W2791686366 · doi:10.1159/000487473

The Importance of Excluding Cutaneous T-Cell Lymphomas in Patients with a Working Diagnosis of Papuloerythroderma of Ofuji: A Case Series

2018· article· en· W2791686366 on OpenAlexaffabout
Anthony Maher, Chloé E. Ward, Steven J. Glassman, Ivan V. Litvinov

Bibliographic record

VenueCase Reports in Dermatology · 2018
Typearticle
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsMcGill University Health CentreUniversity of OttawaMemorial University of Newfoundland
Fundersnot available
KeywordsMycosis fungoidesMedicineErythrodermaDermatologyCutaneous T-cell lymphomaSkin biopsyLymphomaBiopsyPeripheral T-cell lymphomaPathologyImmunologyT cell

Abstract

fetched live from OpenAlex

Papuloerythroderma of Ofuji (PEO) is an erythroderma-like eruption with flat-topped papules that spare the skin folds (a "deck-chair sign" finding). Many infections, medications, and systemic diseases have been associated with PEO, including cutaneous T-cell lymphomas (CTCL). The relationship between the clinical presentation of PEO and CTCL remains poorly elucidated. Clinical, laboratory, and histopathological data were obtained from the Lymphoma Clinic at the Ottawa Hospital, Canada. We report 5 patients with deck-chair-sign-positive CTCL, mycosis fungoides, and Sézary syndrome variants. We contend that PEO should be viewed as a diagnosis of exclusion and that these patients should be monitored carefully for possible emergence of CTCL. Skin biopsy alone is not sufficient to exclude CTCL in these patients. A skin eruption demonstrating a positive deck-chair sign may signify systemic/leukemic CTCL and, therefore, warrants a thorough investigation, including skin biopsy, flow cytometry, and T-cell receptor clonality studies.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.283
Teacher spread0.266 · 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

Citations15
Published2018
Admission routes2
Has abstractyes

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