Low Prevalence of Fragrance Contact Allergy among Turkish Population
Bibliographic record
Abstract
BACKGROUND: Limited data exist on fragrance contact allergy among Turkish population. OBJECTIVE: The aim of this study was to investigate the frequency and characteristics of fragrance contact allergy in Turkey. METHODS: A retrospective cohort study was conducted on 2566 patients consecutively patch tested with the European baseline series and additionally with a fragrance series (n = 358) at a tertiary referral center between 1996 and 2019. RESULTS: One hundred sixty-three patients (6.4%) (male/female, 1.5:1) were sensitized with at least 1 fragrance allergen. Fragrance mix (FM) I was most frequently positive (3.9%), followed by Myroxylon pereirae (3.1%), FM II (2%), and hydroxyisohexyl 3-cyclohexene carboxaldehyde (0.5%), the latter exclusively positive in FM II-positive patients. Among 358 patients patch tested with a fragrance series, positive patch test reactions were observed in 38 patients, including 8 who did not react to baseline fragrance markers. Clinically relevant fragrance allergy was established in 128 patients (78.5%) from nonoccupational (72.4%) and occupational (6.1%) sources. CONCLUSIONS: The low prevalence, the middle-aged male preponderance, and the predominant involvement of hands were unusual findings. Rose/citrus-flavored perfumes and eau de cologne, which are traditionally preferred in our country, were important elicitors of fragrance contact allergy, especially among middle-aged and older men.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".