MétaCan
Menu
Back to cohort
Record W2980500350 · doi:10.1097/der.0000000000000524

Patch Testing for Cheilitis: A 10-Year Series

2019· article· en· W2980500350 on OpenAlexvenueno aff
Harriet Cheng, Joseph Konya, E. Lobel, Pablo Fernández‐Peñas

Bibliographic record

VenueDermatitis · 2019
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDermatologyPatch testingEtiologyPatch testContact dermatitisRefractory (planetary science)AtopyAllergyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The etiology of cheilitis includes endogenous, irritant, and allergic dermatitis; lichenoid and granulomatous disorders; infection; trauma; and actinic damage. Patch testing is indicated for refractory cases (other than actinic cheilitis). OBJECTIVE: The aim of the study was to review demographics and allergens in patients patch tested for cheilitis at 2 sites in Sydney, Australia. METHODS: Records for patients patch tested for a 10-year period from 2007 to 2017 were reviewed. Baseline characteristics and patch test results were compared for patients with and without cheilitis. CONCLUSIONS: There were 1584 patients including 91 with cheilitis. Patients with cheilitis were more likely to be female, younger, and atopic and have concurrent eyelid involvement than those presenting with other dermatoses. Seventeen percent of patients with cheilitis had a post-patch test diagnosis of allergic contact cheilitis, and the most frequent relevant reactions were to patients' own products, fragrances, and sunscreens. Those with cheilitis had more positive reactions to sunscreens, especially benzophenones, compared with those without cheilitis (P < 0.001). This is an important finding in Australia where high rates of melanoma and nonmelanoma skin cancer necessitate promotion of strict sun protection measures.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
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)0.0020.001

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 head0.246
Teacher spread0.229 · 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 designNot applicable
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

Citations16
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueDermatitisSame topicContact Dermatitis and AllergiesFrench-language works237,207