Patch-Test Reactions to Topical Anesthetics: Retrospective Analysis of Cross-Sectional Data, 2001 to 2004
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Allergy to topical anesthetics is not uncommon. The cross-reactivity among topical anesthetics and the screening value of benzocaine alone are not well understood. OBJECTIVES: The goals for this study were: (1) to evaluate the frequency and pattern of allergic patch-test reactions to topical anesthetics, using North American Contact Dermatitis Group (NACDG) data, and (2) to compare these results to allergen frequencies from other published studies. METHODS: The NACDG patch-tested 10,061 patients between 2001 and 2004. In this analysis patients were included who had positive patch-test reactions to one or more of the following: benzocaine, lidocaine, dibucaine, tetracaine, and prilocaine. RESULTS: Of patch-tested patients, 344 (3.4%) had an allergic reaction to at least one anesthetic. Of those, 320 (93.0%) had an allergic reaction to only one topical anesthetic. Overall, reactions to benzocaine (50.0%, 172 of 344) were most prevalent, followed by reactions to dibucaine (27.9%, 96 of 344); however, reactions to dibucaine were significantly more frequent in Canada than in the United States (relative risk [RR], 2.31; 95% confidence interval [CI], 1.67-3.20; p < .0001). Of patients reacting to more than one anesthetic, most (79%, 19 of 24) reacted to both an amide and an ester. CONCLUSIONS: Of the topical anesthetics tested, benzocaine was the most frequent allergen overall. Over 50% of allergic reactions to topical anesthetics in this study would have been missed had benzocaine been used as a single screening agent. Cross-reactivity patterns were not consistent with structural groups.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
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 it