Contact Allergens in Prescription Topical Ophthalmic Medications
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Both active and inactive ingredients in topical ophthalmic agents may cause allergic contact dermatitis. Here, we examined ingredients in prescription topical ophthalmic medications available in the United States. METHODS: A comprehensive list of topical ophthalmic medications was generated using AccessPharmacy. Categories included antiglaucoma, antibiotic, antibiotic/corticosteroid, corticosteroid, antiviral, antifungal, mydriatic, and miotic agents. For each formulation, ingredients were investigated using the National Institutes of Health US National Library of Medicine database and/or manufacturer websites. Counts and proportions were calculated for inactive ingredients, including those in the American Contact Dermatitis Society (ACDS) Core 90 Allergen Series. RESULTS: Two hundred sixty-four unique prescription ophthalmic medications met the inclusion criteria. The most common ACDS Core 90 allergen/cross-reactor inactive ingredient was benzalkonium chloride (68.1%, 180/264), followed by sorbates (11.7%, 31/264), parabens (6.8%, 18/264), sodium metabisulfite (3.8%, 10/264), propylene glycol (3.0%, 8/264), and lanolin (3.0%, 8/264). Approximately 21% (20.8%, 55/264) of products had no ACDS Core 90 allergens/cross-reactor inactive ingredients. The most common ACDS Core 90 allergen/cross-reactor active ingredients were aminoglycoside antibiotics, bacitracin/polymyxin B, and corticosteroids. Important non-ACDS Core 90 allergens included inactive ingredients, such as EDTA 28.0% and thimerosal 2.7%, as well as active ingredients, especially β-blockers. CONCLUSIONS: Benzalkonium chloride, sodium metabisulfite, propylene glycol, and lanolin were common inactive ingredient allergens. Most ophthalmic categories had low allergen formulations available for patients with contact allergy.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".