Expanded Series and Personalized Patch Tests for Children: A Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Epicutaneous patch testing was developed as a simple and effective method for diagnosing allergic contact dermatitis (ACD). Despite its proven value in ACD diagnoses, there is no defined standard for patch testing in children. OBJECTIVE: The aims of this study were to assess patch test positivity in pediatric patients with and without a history of atopic dermatitis suspected to have ACD, to compare these results with what the Thin-Layer Rapid Use Epicutaneous (T.R.U.E.) Test would have captured, and to evaluate likely exposures. METHODS: Pediatric patients receiving a North American 80 Comprehensive Series patch test or a personalized patch test were analyzed for allergen sensitization 48 to 72 hours after patch removal. These data were analyzed for allergen inclusion in the North American 80 Comprehensive Series patch test compared with the T.R.U.E. Test, as well as compared with patients with and without a history of atopic dermatitis. RESULTS: Of the 29 patients (mean ± SD age = 10.9 ± 5.1 years), 25 children demonstrated at least 1 positive reaction, with a total of 81 reactions overall. 40 (49.4%) of the reactions came from allergens outside of the T.R.U.E. Test, including cocamidopropyl betaine, which was frequent in patients with atopic dermatitis. CONCLUSIONS: Expanded and personalized patch tests provide a more comprehensive allergen inventory than the traditional T.R.U.E. Test. Pediatric patients frequently have reactions to allergens not included in the T.R.U.E. Test, and these allergens are commonly found in household products. Cocamidopropyl betaine was a particularly relevant allergen in our population. Expanded series patch testing and appropriate counseling should be provided to pediatric patients with ACD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".