Patch Testing Results From the Massachusetts General Hospital Contact Dermatitis Clinic, 2007–2016
Bibliographic record
Abstract
BACKGROUND: Patch testing is the criterion standard for diagnosis of allergic contact dermatitis (ACD). OBJECTIVE: The aim of the study was to report the trends of patch testing results with the standard series at Massachusetts General Hospital from January 1, 2007, to December 31, 2016, compared with previous data from 1998 to 2006 and from 1990 to 2006 and those reported by the North American Contact Dermatitis Group. METHODS: Data were collected and analyzed from retrospective chart reviews, focusing on 50 allergens in our standard series. RESULTS: A total of 2373 patients were patch tested. One or more positive reactions were observed in 1428 patients (60.2%), and 1153 patients (48.6%) had a final primary diagnosis of ACD. Top 5 allergens were nickel (19.8%), fragrance mix I (14.6%), Myroxylon pereirae (balsam of Peru) (13.5%), neomycin (9.4%), and bacitracin (7.7%). Sensitization frequencies statistically increased over time for 3 allergens: nickel, neomycin, and propylene glycol, and decreased for 5 allergens: formaldehyde, paraben mix, thiuram mix, n-isopropyl-N-phenyl-4-phenylenediamine, and epoxy resin (P ≤ 0.001). CONCLUSIONS: Surveillance of ACD trends is essential to detect emerging sensitizers. Patch testing is an important diagnostic tool for detection of ACD to commonly encountered and potential allergens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.004 | 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".