Hand Dermatitis Secondary to Methylchloroisothiazo- linone/methylisothiazolinone in Mechanics
Bibliographic record
Abstract
Background: Allergic contact dermatitis (ACD) is a common oc-cupational disease and significant cause of work absenteeism. Dermatitis can be so severe that it will prompt vocational change. Methylchloroisothiazolinone / methylisothiazolinone (MCI/MI, Ka-thon CG) is a common preservative found in waterless hand cleans-ers, many of which are used by mechanics. We present 9 cases of ACD secondary to MCI/MI evaluated at the Ottawa Patch Test Clinic over a 1-year period. Objectives: 1. Examine the clinical features of ACD secondary to MCI/MI 2. Determine common sources of MCI/MI, particularly waterless hand cleansers used by mechanics 3. Discuss management options for mechanics with MCI/MI ACD 4. Determine the impact of contact allergen identification on the patient’s quality of life, including vocational change Methods: Patients underwent patch testing to the North Ameri-can Contact Dermatitis Group Standard Screening Series, the chemotechnique oil & coolant series, rubber series plus other supplementary allergens in our mechanics series. Readings were performed at 48 and 96 or 120 hours. Follow-up interviews were conducted with patients in order to assess the impact of allergen identification on disease management and their quality of life. Results: All patients had significant contact allergy to MCI/MI (>1+). The patient response to discontinuing waterless hand cleansers containing MCI/MI will be discussed. Conclusions: MCI/MI is a common allergen found in waterless hand cleansers used by mechanics. MCI/MI allergen identification can direct disease management, allowing patients to improve their quality of life and avoid vocational change.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".