Positive Patch Test Reactions to Lanolin: Cross-Sectional Data from the North American Contact Dermatitis Group, 1994 to 2006
Bibliographic record
Abstract
BACKGROUND: The prevalence of lanolin sensitivity in referred patients is less than 4%. OBJECTIVES: To (1) describe patients with positive patch-test reactions to lanolin, (2) determine clinical and occupational relevance associated with reactions to lanolin and common sources, and (3) examine the frequency of co-reacting allergens. METHODS: A retrospective analysis of 26,479 patients patch-tested by the North American Contact Dermatitis Group (NACDG), 1994 to 2006. RESULTS: Overall, 2.5% of patients (643 of 25,811) tested to lanolin alcohol 30% in petrolatum had positive reactions. Prevalence decreased from 3.7% in 1996 to 1998 to 1.8% in 2005 to 2006 (p <.0001); 83.4% of all positive reactions were currently relevant, but only 2.5% were occupationally relevant. Lanolin-positive patients were 1.2 times more likely to be male and 1.4 times more likely to have a history of atopic dermatitis when compared to allergic, but lanolin-negative, patients (p < .0002 and p < .0001, respectively). Cosmetics were the most common source. Lanolin-positive patients were significantly more likely to be co-sensitized to another NACDG standard screening allergen (p <.0001). CONCLUSIONS: The prevalence of allergic patch-test reactions to lanolin in North America patch-test populations is decreasing. Current relevance of reactions was high, but occupational relevance was low. Concomitant reactions were more common in lanolin-positive patients.
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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 | 0.000 | 0.000 |
| 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".