Results of Patch Testing to Botanicals: Review of the Mayo Clinic Experience over 2 Decades (1997–2017)
Bibliographic record
Abstract
Abstract: Background: Botanicals are increasingly incorporated into skincare products. Although allergic contact dermatitis due to botanicals is recognized, data describing the prevalence of positive patch tests to botanicals are sparse. Objective: To report the Mayo Clinic experience of patch testing to selected botanical products in the standard, extended standard, fragrance, and plant series. Methods: IRB-approved retrospective study of the Mayo Clinic experience with patch testing to botanicals from 1997 to 2017. Results: In total, 12,169 people were patch tested to botanicals in the standard, extended standard, fragrance, and plant series; 4032 were men and 8137 were women. The mean age of the population tested was 54 (standard deviation 17.7) years. Almost 11% (1320/12,169) of the patch-tested population exhibited positive reactions to at least 1 botanical agent. Myroxylon pereirae resin 25% was the most common positive allergen in the series. Patients who had positive reactions to at least 1 botanical agent were more (19.8%) likely to have a positive reaction to at least 1 additional botanical than those patients who did not have any positive tests. Most patients presented with generalized involvement (334) or involvement of the hands (284) or face (232). Conclusion: Physicians should be aware of the high prevalence of allergic contact dermatitis and patch test positivity associated with botanical products.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".