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Record W3194524196 · doi:10.1097/der.0000000000000763

Update on Contact Sensitization in the Older Adult Population

2021· article· en· W3194524196 on OpenAlexvenueno aff
Carina M. Woodruff, Alexander Kollhoff, Daniel Butler, Nina Botto

Bibliographic record

VenueDermatitis · 2021
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePatch testAllergenDermatologyAllergic contact dermatitisContact dermatitisPopulationPatch testingAllergyImmunologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Little is known about the epidemiology of allergic contact dermatitis in the aging US population. OBJECTIVE: The aim of this study was to describe patch test results in a cohort of older adult patients evaluated in a patch testing clinic in a tertiary medical center. METHODS: This study was a retrospective analysis of patch test results of adults 65 years and older from February 2013 to December 2019. RESULTS: Data from a total of 169 patients 65 years and older were analyzed. Of these patients, 84.6% (143/169) had 1 or more positive reactions on patch testing, 84.6% (121/143) of which were felt to be clinically relevant and received a final diagnosis of allergic contact dermatitis. The most common allergen categories were fragrances (30.1%), preservatives (20.8%), metals (11.0%), medicaments (8.3%), and textile dyes (6.5%). The most common individual allergens were Myroxylon pereirae resin (balsam of Peru), hydroperoxide of linalool, methylisothiazolinone, nickel sulfate, and fragrance mix I. Personal products were by far the most common presumed source of allergen exposure. CONCLUSIONS: Allergic contact dermatitis is a common diagnosis in the older adult population, and patch testing with allergen avoidance counseling can be an important diagnostic step and potential cure for this allergic condition.

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 score0.460
Threshold uncertainty score0.316

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)0.0000.000

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 head0.009
GPT teacher head0.246
Teacher spread0.237 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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