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Record W2614374113 · doi:10.1097/der.0000000000000287

Multicenter Patch Testing With Methylchloroisothizoline/Methylisothiazolinone in 100 and 200 ppm Within the International Contact Dermatitis Research Group

2017· article· en· W2614374113 on OpenAlexvenueno aff
Malin Engfeldt, Iris Ale, Klaus E. Andersen, Peter Elsner, Chee‐Leok Goh, An Goossens, Hemangi Jerajani, Kayoko Matsunaga, M. Bruze

Bibliographic record

VenueDermatitis · 2017
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePatch testingDermatologyContact dermatitisMulticenter studyGroup (periodic table)Patch testSurgeryRandomized controlled trialImmunologyOrganic chemistry

Abstract

fetched live from OpenAlex

BACKGROUND: The preservative methylchloroisothiazolinone/methylisothiazolinone (MCI/MI) is a well-known contact sensitizer. Historically, there have been different opinions on the optimal patch test concentration of MCI/MI, and both 0.01% and 0.02% aqueous (aq.) have been proposed. In 2011, based on literature reviews, it was recommended that the concentration of 0.02% aq. should be used in the international baseline series. OBJECTIVES: The aim of this study was to verify the recommendation from 2011 by comparing the patch test results from consecutive patch testing with MCI/MI 0.01% and 0.02% in clinics representing countries around the world. PATIENTS AND METHODS: Two thousand seven hundred three consecutive patients with dermatitis in 8 dermatology clinics representing 8 countries were patch tested with MCI/MI 0.01% aq. and, in parallel with MCI/MI 0.02% aq., provisionally included in the baseline series. RESULTS: Contact allergy to MCI/MI at 0.01% and 0.02% was found in 3.7% and 5.6% of the patients, respectively (P < 0.001). CONCLUSIONS: Methylchloroisothiazolinone/MI 0.02% aq. (dose, 6 μg/cm) diagnoses significantly more contact allergy than 0.01% (dose, 3 μg/cm), without resulting in more adverse reactions. Methylchloroisothiazolinone/MI at 0.02% aq. should therefore be continuously used in the international 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)0.001
metaresearch head score (Gemma)0.001
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 score0.055
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.060
GPT teacher head0.336
Teacher spread0.276 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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