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Record W3121056809 · doi:10.1097/der.0000000000000683

Photopatch Testing in New Zealand: A 12-Year Retrospective Review

2021· article· en· W3121056809 on OpenAlexvenueno aff
Yena Kim, Denesh C Patel, Deborah Greig, Harriet Cheng

Bibliographic record

VenueDermatitis · 2021
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDermatologyPromethazinePatch testingAllergic contact dermatitisContact dermatitisReferralPopulationRetrospective cohort studyAllergySurgeryFamily medicineAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Little is known about the common photoallergens in New Zealand, where ultraviolet exposure is particularly high. Availability of photopatch testing is limited because of it being performed in very few tertiary referral and contact dermatitis clinics. OBJECTIVE: To review the photopatch testing experience in New Zealand. METHOD: A retrospective review of all patients who underwent photopatch testing at a tertiary referral center in Auckland from 2008 to 2019 was performed. RESULTS: Seventy patients had photopatch testing over the 12-year period. Of the 58 patients tested using the photoallergen series, 6 (10%) patients had a positive photopatch test reaction, of which 4 were to promethazine and 2 were to benzophenone-3. The most common postpatch diagnosis was endogenous dermatitis (54%), followed by allergic contact dermatitis (21%), photoallergic contact dermatitis (9%), and chronic actinic dermatitis (4%). CONCLUSIONS: Both patch and photopatch testing are important investigations in patients with suspected photoallergic contact dermatitis. Promethazine and benzophenone-3 were the most frequent and only photoallergens in our population. Promethazine sensitization was via oral exposure, supporting a mechanism of systematized photoallergy to promethazine.

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)0.001
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 score0.477
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.025
GPT teacher head0.275
Teacher spread0.250 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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