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Record W4306729947 · doi:10.1097/der.0000000000000964

Assessment of Comorbidities Associated With Allergic Contact Dermatitis in the United States: A Retrospective Claims-Based Study

2022· article· en· W4306729947 on OpenAlexvenueno aff
Vivian Hua, Shufeng Li, Mollie F. Qian, Golara Honari, Kavita Y. Sarin, Jennifer K. Chen

Bibliographic record

VenueDermatitis · 2022
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCulpritDiseaseComorbidityInfectious disease (medical specialty)Psychological interventionEndotypeIntensive care medicineAtopic dermatitisPsychiatryDermatologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Allergic contact dermatitis (ACD) is a common dermatologic disease. Patch testing remains the criterion standard for diagnosis. In clinical practice, avoidance may be limited by patient occupation or noncompliance, the pervasive nature of the culprit agent, or barriers to expert care because of socioeconomic, cultural, or geographic factors. Thus, ACD is frequently chronic and/or recurrent; however, the comorbidities associated with ACD are not well characterized. OBJECTIVE: The aim of the study is to identify associations between ACD and psychiatric, sleep health, cardiovascular, and infectious conditions. METHODS: In this study, we used a large US claims database to identify comorbidities associated with ACD diagnosed after patch testing, including psychiatric, sleep health, cardiovascular, and infectious conditions. We also stratified these associations by chronicity of disease. RESULTS: We identified associations between ACD and psychiatric, sleep-related, cardiovascular, and infectious comorbidities. We also found that more chronic ACD was associated with more infectious comorbidities. All of these associations remained significant on further subanalysis when patients with AD and venous stasis were excluded. CONCLUSIONS: Allergic contact dermatitis is associated with multiple comorbidities. Further study is required to corroborate these findings, determine causality, and to explore the impact of possible interventions in the workup and management of this common and often debilitating disease.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.019
GPT teacher head0.279
Teacher spread0.260 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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