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Record W2088863951 · doi:10.5402/2011/767589

Tinea Corporis Gladiatorum Presenting as a Majocchi Granuloma

2011· article· en· W2088863951 on OpenAlexaff
Anil Kurian, Richard M. Haber

Bibliographic record

VenueISRN Dermatology · 2011
Typearticle
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsUniversity of CalgaryMcMaster University
Fundersnot available
KeywordsTerbinafineTinea capitisMedicineDermatologyTrichophyton tonsuransDermatophyteGranulomaLesionScalpDifferential diagnosisDermatomycosisTrichophytonAntifungalPathologyItraconazole

Abstract

fetched live from OpenAlex

Background. Wrestlers are at increased risk of developing cutaneous infections, including fungal infections caused by dermatophytes. Erythematous lesions due to tinea infections can be mistakenly diagnosed as an inflammatory dermatitis and incorrectly treated with potent topical corticosteroid treatments which cause localized skin immunosuppression. This can eventuate in a Majocchi granuloma which then becomes refractory to topical antifungal therapy. To our knowledge, this is the first case of tinea corporis gladiatorum presenting as a Majocchi granuloma. Observations. A 20-year-old wrestler presented with a 4-year history of a large pruritic, scaly erythematous plaque with follicular papules, and pustules on his right forearm. The lesion had the clinical appearance of a Majocchi granuloma. He had been treated with potent topical corticosteroids and topical antifungal therapy. KOH and fungal culture of the lesion were negative. An erythematous scaly lesion in the scalp was cultured and grew Trichophyton tonsurans. Oral Terbinafine therapy was initiated and complete resolution of both lesions occurred within 6 weeks. Conclusion. The purpose of this report is to inform dermatologists that tinea corporis gladiatorum can present as a Majocchi granuloma and needs to be considered in the differential diagnosis of persistent skin lesions in wrestlers.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.002

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 head0.027
GPT teacher head0.271
Teacher spread0.244 · 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

Citations20
Published2011
Admission routes1
Has abstractyes

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