Trends in Patch Testing With the Mayo Clinic Standard Series, 2011–2015
Bibliographic record
Abstract
BACKGROUND: Patch testing to a standard (baseline) series of allergens is the screening tool used to identify culprit allergens in patients with contact dermatitis. The allergens and concentrations used in a standard series are constantly evolving to be most relevant to the patients being patch tested. OBJECTIVE: The aim of this study was to analyze the 2011-2015 patch test results of the Mayo Clinic standard series. METHODS: We retrospectively reviewed patch test reactions of standard series allergens from 2011 through 2015 and compared these results with the 2011-2012 and 2013-2014 North American Contact Dermatitis Group (NACDG) reports. CONCLUSIONS: Of 2582 patients included, 1566 (60.7%) had at least 1 positive reaction, and 516 (20.0%) had at least 1 irritant reaction. The 15 allergens with the highest reaction rates (from highest to lowest) were nickel sulfate hexahydrate, methylisothiazolinone, Myroxylon pereirae resin, neomycin sulfate, cobalt (II) chloride hexahydrate, benzalkonium chloride, fragrance mix I, potassium dichromate, bacitracin, methylchloroisothiazolinone/methylisothiazolinone, carba mix, formaldehyde, p-phenylenediamine, quaternium-15, and methyldibromo glutaronitrile. Twelve (80%) of these allergens were also in the top 15 of the most recent NACDG report; the 3 allergens not in the NACDG top 15 allergens were potassium dichromate, benzalkonium chloride, and methyldibromo glutaronitrile (the latter 2 allergens are not included in their series).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".