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Record W2059887350 · doi:10.1097/der.0b013e3182811432

Methylchloroisothiazolinone and Methylisothiazolinone Allergic Contact Dermatitis and the Effect of Patch Test Concentration

2013· article· en· W2059887350 on OpenAlexvenueno aff
Eleanor Higgins, Brian Kirby, Sarah Rogers, Paul M. Collins

Bibliographic record

VenueDermatitis · 2013
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDermatologyContact dermatitisPatch testAllergic contact dermatitisAllergyPatch testingContact allergyImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: The isothiazolinones methylchloroisothiazolinone and methylisothiazolinone (MCI/MI) are the active ingredients in a frequently used preservative in cosmetic, household, and industrial products. OBJECTIVES: This study reviewed our department's cases of allergic contact dermatitis caused by MCI/MI, outlining their clinical presentation and possible sources of sensitization. The effect of changing the concentration of MCI/MI from 0.01% to 0.02% in the British Society for Cutaneous Allergy baseline series was also measured. METHODS: A total of 964 patients were patch tested to the British Society for Cutaneous Allergy baseline series in our department over 4 years. Patients were tested either to 0.01% MCI/MI (697) or 0.02% MCI/MI (267). RESULTS: Twenty-one patients (2.2%) had positive reactions to MCI/MI. Of patients tested to 0.02% MCI/MI, 3.8% had a positive reaction compared with 1.6% of those tested to MCI/MI 0.01%. Ten patients (48%) had perianal dermatitis; of these, 50% had used moist toilet wipes. CONCLUSIONS: We highlight MCI/MI as important contact allergens found in moist toilet wipes and should be considered particularly in patients with facial, hand, and perianal allergic contact dermatitis. Patch testing to 0.01% MCI/MI may underestimate its allergenic potential, missing more than half of allergic cases compared with testing to 0.02%. To identify isothiazolinone allergy, we recommend that 0.02% MCI/MI should be used in baseline series.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.809

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 integrity0.0000.000
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 head0.006
GPT teacher head0.227
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2013
Admission routes1
Has abstractyes

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