Allergic Contact Dermatitis in Children: The Ottawa Hospital Patch-Testing Clinic Experience, 1996 to 2006
Bibliographic record
Abstract
BACKGROUND: Allergic contact dermatitis in children is a significant clinical problem. Patch testing is a diagnostic tool for the evaluation of patients with suspected allergic contact dermatitis. OBJECTIVES: To determine the frequency and relevance of positive patch-test results in children and to identify the most common allergens in children at our clinic. METHODS: Retrospective chart review of 100 children and adolescents, aged 4 to 18 years, who were patch-tested at the Ottawa Hospital patch-testing clinic between 1996 and 2006. The children were patch-tested with the North American Contact Dermatitis Group (NACDG) standard series, supplementary series if indicated, and their own products if available. RESULTS: Seventy percent of children had at least one positive patch-test reaction; 55.8% of positive patch-test reactions were relevant. The ratio of females to males was 62:38. The most common allergens were nickel sulfate (26%), cobalt (14%), fragrance mix (7%), neomycin (7%), colophony (6%), formaldehyde (4%), lanolin (4%), quaternium-15 (4%), and para-phenylenediamine (4%). Nickel co-reacted with cobalt (68%) and palladium (100%). Of children tested, 41% had a history of atopic dermatitis. CONCLUSIONS: The frequency of positive and relevant allergens in children is similar to that in adults as compared with data from the NACDG 2001-2002 study period. Differences between the top 10 allergens in children and adults were seen. Nickel and cobalt were more common allergens in children, and colophony, lanolin, and para-phenylenediamine ranked in the top 10 allergens among children.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".