Recommendations for a Screening Series for Allergic Contact Eyelid Dermatitis
Bibliographic record
Abstract
BACKGROUND: Although allergic contact dermatitis of the eyelids is a common condition, limited information is available regarding the selection of patch-testing chemicals for proper evaluation. OBJECTIVE: The purpose of this analysis was to evaluate the relevance of allergens responsible for allergic eyelid dermatitis among a series of patch-tested patients attending our clinic at the University of Miami and compare these results to published studies in the literature. METHODS: Data were retrospectively reviewed for eyelid-only dermatitis from clinically relevant patch-test evaluations performed between December 2004 and January 2007. RESULTS: Formaldehyde was the most frequently encountered antigen, accounting for 45.83% (11/24) of the cases, followed by nickel 33.33% (8/24) and balsam of Peru (Myroxylon pereirae) 29.17% (7/24). In addition, not only did we find a higher prevalence of certain allergens when compared with other studies, but we identified several relevant allergens not previously reported at other referral centers. CONCLUSIONS: The allergens found to be relevant in eyelid dermatitis vary among different regions. These data may help contribute to generating a standard screening tool to improve the detection and management of these cases.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.012 |
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".