Sensitization Prevalence for Benzalkonium Chloride and Benzethonium Chloride
Bibliographic record
Abstract
BACKGROUND: Benzalkonium chloride (BAK) and benzethonium chloride (BEC) are well-characterized skin irritants and rare sensitizers, but optimal testing for allergic contact dermatitis (ACD) is not established. OBJECTIVE: Sensitization prevalence was sought, and several patch testing concentrations and vehicles were compared. METHODS: One hundred forty-two patients tested to the standard screening series for evaluation of dermatitis consented to additional tests including BAK 0.15% aqueous (aq), BAK 0.15% petrolatum (pet), BEC 0.15% aq, and BEC 0.5% aq. Follow-up to assess clinical relevancy included early and late patch test reads, 1-month clinical follow-up, and long-term phone calls. Patients were categorized as definite, possible, or unlikely to have ACD to BAK and/or BEC. RESULTS: Atopy was not associated with patch test reactions (P = 0.154). Seventy-five percent (6/8) of the patients with possible ACD to BAK had coreactions with BEC. Testing to both BAK 0.15% pet and 0.15% aq would have identified 91% of those with possible ACD to BAK, twice as many than if only BAK 0.1% aq from the standard series was used. CONCLUSION: Sensitization to BAK and BEC, although rare, does occur. Weak and morphologically irritant reactions at day 7 reading can be relevant. We recommend testing to BAK 0.15% aq and 0.15% pet to increase sensitivity and having patients undergo long-term follow-up.
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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 | 0.001 | 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) | 0.004 | 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".