Patch Test Results with the Latin American Baseline Series in a Colombian Population. 2016–2021
Bibliographic record
Abstract
Abstract: Background : Contact dermatitis (CD) is one of the most prevalent skin diseases. It is commonly divided into irritant contact dermatitis (ICD) and allergic contact dermatitis (ACD). Patch testing is a procedure used to support the diagnosis of ACD. This test should be interpreted along with the clinical history and morphology of the skin lesions to determine clinical relevance. Objective: To describe the sensitization patterns of patients undergoing patch testing with the Latin American baseline series. Methods: A single-center retrospective study was performed. For the study, patients older than 18 years with a clinical diagnosis of contact dermatitis, who underwent patch testing using the Latin American baseline series were considered. These tests took place at the Alma Mater Hospital of Antioquia between January 1, 2016, and December 31, 2021. Results: A total of 648 patients were included. Patch tests were positive in 63% of cases, with a mean age of 51.5 years. Around 36.6% had atopy-related diseases. The main occupation was housework (30.7%). The hands were the most affected area in the body (31%). The main allergens were nickel sulfate (34%), sodium tetrachloropalladate (24.2%), and thimerosal (8.0%). Fifteen allergens had a percentage below 1%. Hydrocortisone and budesonide did not yield positive results. Conclusion: Nickel sulfate was the most frequent allergen, and women were the most affected. The information gathered could be useful for adjusting the allergens that should be included in the regional baseline series, taking into account the frequency found.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".