Patch Test Practice Patterns of Members of the American Contact Dermatitis Society
Bibliographic record
Abstract
BACKGROUND: Patch testing is the criterion standard for diagnosis and management of allergic contact dermatitis. Limitations on the number of allergens tested can negatively impact patient care. OBJECTIVE: This study reports clinical practice patterns of American Contact Dermatitis Society (ACDS) members. METHODS: In October and November 2018, the US-based members of the ACDS received an electronic survey regarding their procedures and experiences with patch testing. We evaluated the type of practice, number of patients tested, type of screening and supplemental series, number of allergens tested, and billing and reimbursement concerns. RESULTS: There were 149 respondents; 62% use ACDS Core 80, 70% "sometimes" or "always" test with supplemental series, and 70% "sometimes" or "always" test patient products. Participants estimated that supplemental series identify relevant allergens 35% of the time. Approximately 66% most commonly test more than 81 allergens per patient, and 78% expressed concerns regarding fair reimbursement. CONCLUSIONS: Most ACDS members routinely test more than 81 allergens per patient. Barriers to fair payment for beyond a fixed number of patches at any one visit may impede the diagnosis of allergic contact dermatitis, prolong suffering, and worsen outcomes.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".