What Is the Relevance of Contact Allergy to Sodium Metabisulfite and Which Concentration of the Allergen Should We Use?
Bibliographic record
Abstract
BACKGROUND: The prevalence of contact allergy to sodium metabisulfite (SMB) has increased from the range of 1.4% to 1.7% to the range of 3.4% to 6.8% in published series over the past 20 years. AIMS: The aims of this study were to review contact allergy to SMB in our cohort and to investigate different concentrations to define the most appropriate concentration for patch testing. METHODS: Patient records were reviewed between February 2009 and December 2011 to obtain information on patient demographics, clinical presentation, and prevalence of contact allergy to SMB. Patients attending for patch testing, between January 2012 and June 2013, were tested with 3 strengths of SMB as part of the British standard series (1%, 0.1%, and 0.01%). RESULTS: Nine hundred ninety-six patients were patch tested to the British standard series including SMB 1% in petrolatum between February 2009 and June 2013, and 70 (7%) were positive. In the prospective group, 380 were tested to 3 concentrations of SMB (1.0%, 0.1%, and 0.01%). Fourteen patients (3.68%) had a positive patch test with 1% SMB, 7 to 0.1% SMB, and 3 to 0.01% SMB. There was exposure to SMB in 10 patients who cleared with avoidance at review 3 months later. The most frequent location of rash included face, hands, vulval, and perianal region. CONCLUSIONS: Our study confirms reports of increasing prevalence of SMB allergy. A detailed review of exposure in the prospective study showed that SMB is relevant in most patients, and 1% in petrolatum is the best concentration for patch testing.
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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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".