Pesticide Patch Test Series for the Assessment of Allergic Contact Dermatitis among Banana Plantation Workers in Panama
Bibliographic record
Abstract
BACKGROUND: Irritant contact dermatitis and allergic contact dermatitis (ACD) are frequent among agricultural workers and require targeted interventions. Patch testing is necessary for differential diagnosis, but patch testing with pesticides is uncommon. OBJECTIVE: This study explores the frequency of ACD and sensitization to pesticides among highly exposed banana plantation workers. METHODS: Frequently and recently used pesticides on banana plantations in Divala, Panama, were documented. A pesticide patch test tray specific for this population was prepared. A structured interview was administered to 366 participants, followed by a complete skin examination. The pesticide patch test series, as well as a standard patch test series, was applied to 37 workers with dermatoses likely to be pesticide related and to 23 control workers without dermatoses. RESULTS: The pesticide patch tests identified 15 cases (41%) of ACD (20 positive reactions) among the 37 workers diagnosed with pesticide dermatosis. Three controls had allergic reactions to pesticides (4 positive reactions). The pesticides were carbaryl (5 cases), benomyl (4 cases), ethoprophos (3), chlorothalonil (2), imazalil (2), glyphosate (2), thiabendazole (2), chlorpyrifos (1), oxyfluorfen (1), propiconazole (1), and tridemorph (1). Ethoprophos and tridemorph had not been previously identified as sensitizers. Thus, the prevalence of ACD was 0.03 (15 of 366). On the basis of observed prevalences of positive patch-test reactions among the subgroups with and without dermatoses, we estimated that > or = 16% of the entire population may be sensitized to pesticides. CONCLUSION: Sensitization to pesticides among banana plantation workers is a frequent occupational health problem. Pesticide patch test trays should be used in assessing skin diseases in highly exposed workers.
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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) | 0.002 | 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 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".