A Multicenter Study of Patch Test Reactions With Dental Screening Series
Bibliographic record
Abstract
Background: Dental products contain many allergens, and may cause problems both for patients undergoing dental treatment and for dental personnel because of occupational exposure. Individual patch test clinics may not study sufficient numbers of patients to collect reliable data on uncommon allergens. Objective: To collect information on dental allergens based on a multicenter study. Materials and Methods: The Finnish Contact Dermatitis Group tested more than 4,000 patients (for most allergens, 2,300 to 2,600 patients) with dental screening series. Conventional patch testing was performed. The total number and percentage of irritant (scored as irritant [IR] or doubtful [?]) and allergic (scored as +, ++, or +++) patch test reactions, respectively, were calculated, as well as the highest and lowest percentage of allergic patch test reactions recorded by the different patch test clinics. A reaction index (RI) was calculated, giving information on the irritancy of the patch test substances. Results: The most frequent allergic patch test reactions were caused by nickel (14.6%), ammoniated mercury (13%), mercury (10.3%), gold (7.7%), benzoic acid (4.3%), palladium (4.2%) and cobalt (4.1%). 2-hydroxyethyl methacrylate (2.8%) provoked most of the reactions caused by (meth)acrylates. Menthol, peppermint oil, ammonium tetrachloroplatinate, and amalgam alloying metals provoked no (neither allergic nor irritant) patch test reactions. Conclusion: Patch testing with allergens in the dental screening series, including (meth)acrylates and mercury, needs to be performed to detect contact allergy to dental products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".