Contact Dermatitis Associated With Skin Cleansers: Retrospective Analysis of North American Contact Dermatitis Group Data 2000–2014
Bibliographic record
Abstract
BACKGROUND: There is limited information regarding contact dermatitis (CD) associated with skin cleansers (SCs). OBJECTIVE: The aim of the study was to evaluate the prevalence of allergic patch test (APT) reactions and irritant CD (ICD) associated with SCs. METHODS: A retrospective cross-sectional analysis was performed using North American Contact Dermatitis Group data, 2000-2014. RESULTS: Of 32,945 tested patients, 1069 (3.24%) had either APT reaction or ICD associated with SCs. Of these, 692 (64.7%) had APT reaction only, 350 (32.7%) had ICD only, and 27 (2.5%) had both. Individuals with APT reaction and/or ICD were more likely to have occupationally related skin disease (relative risk [RR] = 3.8 [95% confidence interval {CI} = 3.3-4.5] for APT reaction and 10.0 [95% CI = 8.2-12.2] for ICD, respectively, P < 0.0001). As compared with those without APT reaction to SC, individuals with APT reaction had significantly higher frequencies of hand (RR = 2.4 [95% CI = 2.1-2.7]) and arm dermatitis (RR = 1.3 [95% CI = 1.1-1.6], P ≤ 0.001). Irritant CD was strongly associated with hand dermatitis (RR = 6.2 [95% CI = 5.2-7.3], P < 0.0001). More than 50 allergens were associated with SCs including quaternium-15 (11.2%), cocamidopropyl betaine (9.5%), methylchloroisothiazolinone/methylisothiazolinone (8.4%), coconut diethanolamide (7.9%), fragrance mix I (7.7%), Myroxylon pereirae (5.9%), 4-chloro-3,5-xylenol (5.8%), amidoamine (5.5%), and formaldehyde (4.4%). CONCLUSIONS: Many allergens, especially preservatives and surfactants, were associated with SCs. Most cases involved the hands and were occupationally related.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".