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Record W2040719390 · doi:10.2310/6620.2007.06042

Repeated Open Application Tests with Methyldibromoglutaronitrile in Dermatitis Patients with and without Hypersensitivity to Methyldibromoglutaronitrile

2007· article· en· W2040719390 on OpenAlexvenueno aff
Marléne Isaksson, Birgitta Gruvberger, M. Bruze

Bibliographic record

VenueDermatitis · 2007
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePatch testMoisturizerPatch testingContact dermatitisDermatologyContact allergyAllergic contact dermatitisAllergySurgeryImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Contact allergy to and allergic contact dermatitis from methyldibromoglutaronitrile (MDBGN) have been frequently reported since the 1990s. OBJECTIVE: This study was initiated to help determine the optimal test preparation for MDBGN and to help determine the clinical relevance of such a contact allergy. METHOD: In 38 patients with positive (32 patients) or doubtful (6 patients) patch-test reactions to at least one of four test preparations of MDBGN in petrolatum at 1.0%, 0.5%, 0.3%, and 0.1% (all weight per weight [w/w]), a repeated open application test (ROAT) with moisturizers with and without MDBGN at 0.03% w/w was conducted on patients' upper arms for a maximum of 4 weeks. Seven patients not hypersensitive to MDBGN served as controls and went through the same procedure. RESULTS: Nineteen (59.4%) of the 32 MDBGN-allergic patients developed a positive ROAT result on the arm on which the moisturizer containing MDBGN was applied whereas no patients with doubtful or negative reactions to MDBGN reacted (p = .002). A statistically significant association was found between the patch-test reactivity and the outcome of the ROAT (p < .001). CONCLUSION: Patch testing with MDBGN at 0.3% and 0.1% will miss clinically relevant patch-test reactions to MDBGN.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.263
Teacher spread0.253 · 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 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

Citations9
Published2007
Admission routes1
Has abstractyes

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