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Record W3131919474 · doi:10.1097/der.0000000000000721

Hand Dermatitis in the Time of COVID-19: A Review of Occupational Irritant Contact Dermatitis

2021· review· en· W3131919474 on OpenAlexvenueno aff
Anna E. Kersh, Maija Johansen, Ashley Ojeaga, Salma de la Feld

Bibliographic record

VenueDermatitis · 2021
Typereview
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsIrritant contact dermatitisMedicineHygienePersonal protective equipmentEnvironmental healthPsychological interventionOccupational DermatitisContact dermatitisHand eczemaContext (archaeology)Occupational safety and healthPersonal hygieneCoronavirus disease 2019 (COVID-19)DermatologyFamily medicineDiseaseNursingInfectious disease (medical specialty)AllergyPathology

Abstract

fetched live from OpenAlex

Occupational contact dermatitis accounts for 95% of all cases of occupational skin disease with irritant contact dermatitis (ICD) constituting 80% to 90% of these cases. Health care workers, hairdressers, and food service workers are typically most affected by occupational ICD of the hands as these occupations require frequent hand hygiene and/or prolonged exposure to water, also known as "wet work." In the context of the current COVID-19 pandemic, frequent hand hygiene has become a global recommendation for all individuals, and new workplace guidelines for hand sanitization and surface sterilization are affecting occupations not previously considered at risk of excessive wet work including grocery or retail workers, postal workers, sanitization workers, and others. In this review, we discuss the etiology and pathogenesis of occupational ICD with additional focus on treatment and interventions that can be made at an institutional and even national level for education and prevention of ICD resulting from frequent hand hygiene.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.050
GPT teacher head0.354
Teacher spread0.305 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2021
Admission routes1
Has abstractyes

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