Retrospective Study of PhotoPatch Testing in a Chinese Population During a 7-Year Period
Bibliographic record
Abstract
BACKGROUND: Photoallergic contact dermatitis (PACD) is of importance in a proportion of photodermatoses and can be evaluated through photopatch testing (PPT). OBJECTIVES: The objectives of this study were to evaluate the results of PPT and investigate the prevalence of PACD reactions to different photoallergens in Chinese patients at the Department of Dermatology of Huashan Hospital Fudan University during a 7-year period. METHODS: A retrospective PPT study was conducted. During the 7 years, 4957 patients attending for investigation of suspected photodermatoses were tested according to the European consensus methodology with up to 14 allergens prepared according to Chinese National Standards. The reactions were scored using the International Contact Dermatitis Research Group visual scoring system. RESULTS: A total of 3472 PACD reactions in 2454 subjects (49.5%) were recorded. The most common agents were chlorpromazine (44.3%), followed by para-aminobenzoic acid (14.7%), thimerosal (8.9%), and sulfanilamide (6.9%). Allergic contact dermatitis reactions comprised 409 reactions in 399 subjects (8%). Photoinhibition and photoaugmentation of allergic contact dermatitis compromised 3810 reactions in 2412 subjects and 11 reactions in 11 subjects, respectively. Irritant reactions (1928 reactions) were seen in 1140 subjects. CONCLUSIONS: The most predominant photoallergens in our region were chlorpromazine, para-aminobenzoic acid, thimerosal, and sulfanilamide, which likely reflected the particular exposures of this Chinese population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".