Winter Season, Frequent Hand Washing, and Irritant Patch Test Reactions to Detergents Are Associated With Hand Dermatitis in Health Care Workers
Bibliographic record
Abstract
BACKGROUND: Irritant hand dermatitis (IHD) is common in health care workers. OBJECTIVE: We studied endogenous irritant contact dermatitis threshold by patch testing and exogenous factors such as season and hand washing for their association with IHD in health care workers. METHODS: Irritant patch testing with sodium lauryl sulfate (SLS), sodium hydroxide, and benzalkonium chloride at varying concentrations was measured in 113 health care workers. Examination for hand dermatitis occurred at 1-month intervals for a period of 6 months in the Midwestern United States. RESULTS: Positive patch testing to low-concentration SLS was associated with IHD (P = 0.0310) after adjusting for age, sex, ethnicity, season, history of childhood flexural dermatitis, mean indoor relative humidity, and glove and hand sanitizer usage. Subjects with a positive patch test to SLS were 78% more likely to have occurrence of IHD (incidence rate ratio [IRR] = 1.78; 95% confidence interval [CI], 0.92-3.45). Hand washing frequency (≥10 times a day; IRR = 1.55; 95% CI, 1.01-2.39) and cold season (IRR = 2.76; 95% CI, 1.35-5.65) were associated with IHD. No association was found between history of childhood flexural dermatitis and IHD in this population. CONCLUSIONS: Both genetic and environmental factors are important in the etiology of IHD and should be considered in designing strategies to protect, educate, and treat susceptible individuals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".