The Rising Incidence of Allergic Contact Dermatitis to Acrylates
Bibliographic record
Abstract
BACKGROUND: Allergic contact dermatitis (ACD) caused by (meth)acrylates used in nail products is being increasingly reported in nail technicians and consumers. OBJECTIVES: The aim of the study was to assess the incidence of sensitization to (meth)acrylates in technicians and users of nail products with ACD, referred for patch testing in a tertiary center, during the last 10 years. METHODS: All patients with ACD, who reported a profession associated with cosmetic nail procedures or use of such services and were referred for patch tests in our department between January 2009 and December 2018, were identified. The incidence of positive sensitization to (meth)acrylates was assessed. RESULTS: Contact allergy to 1 or more (meth)acrylates was found in 116 (74.4%) of 156 nail technicians or nail product users, all women. One hundred thirty-eight (88.5%) were occupationally exposed, and 18 (11.5%) were consumers. In addition, there was a statistically significant increase in (meth)acrylate ACD during 2014-2018 (100/127 cases [79%]) when compared with 2009-2013 (16/29 cases [55%]). The most common sensitizer among the 156 allergic individuals was ethylene glycol dimethacrylate, which was positive in 113 cases (72.4%), and among patients with acrylate-positive patch test, the rate was 97.4%. CONCLUSIONS: Our experience confirms the worldwide changing landscape of rising (meth)acrylate sensitization in nail technicians and nail products users with ACD. Efforts to improve prevention are needed, and clinicians should have a high index for suspicion in this occupational group.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".