Contact Allergens in Oral Antihistamines
Bibliographic record
Abstract
BACKGROUND: Excipients in various formulations of active drugs occasionally include known contact allergens. Their ingestion may trigger dermatitis or cause it to become widespread or refractory to therapy. OBJECTIVE: The aim of this study was to investigate the prevalence of common contact allergens among the excipients of oral antihistamines available in this country. METHODS: We gathered the complete ingredient lists of 2119 different preparations of 12 oral antihistamines from the National Library of Medicine data bank and entered them into an electronic database for analysis. RESULTS: More than half the formulations (55.0%) contained at least 1 member of the 10 allergen families assessed. Most brompheniramine and doxepin preparations included potentially allergenic excipients, whereas fexofenadine was most often free of them. Sorbitan group members, azo dyes, and propylene glycol were the allergens found most frequently in the antihistamines, each present in over 25% of the products. Elixirs, liquids, solutions, suspensions, and syrups were more likely than nonchewable caplets, capsules, and tablets to contain the allergens tabulated (100% vs 39.3%, respectively). Chewable pills frequently contained azo dyes. CONCLUSIONS: Ingestion of antihistamines could precipitate a systemic contact dermatitis in a patient sensitized to an allergen present as an excipient in the medicine.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.006 | 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".