Patch Testing by Additional Series of Allergens: Results of Further Experiences
Bibliographic record
Abstract
Background: Patch testing with additional series (AS) of allergens may be a useful tool in diagnosing allergic contact dermatitis (ACD). Objective: Aim of the study was to verify the usefulness, to check the reliability in clinical practice and to evaluate the economic costs of AS previously built up. Methods: A total of 281 patients with suspicious ACD underwent patch test with the standard series (SS) and with one or more AS (51 among 71 built up). Results: A total of 170 patients (60.5%) showed positive reactions to SS; 116 (41.3%) to AS. Among 582 nonstandard allergens used, 113 (19.4%) elicited 1 or more positive reactions: out of 10,916 patch tests carried out, 260 (2.4%) positive reactions were observed. The correlation between SS and AS indicated that 8.2% patients resulted SS-/AS+, 27.7% SS+/AS-, 32.7% SS+/AS+, 31.3% SS-/AS-. The most frequently used AS showed the following percentages of patients with 1 or more positive reactions: clothes 41.4%, building industry 51.8%, hairdressers 77.3%, textile industry 42.1%, shoes 36.8%. Positive reactions to the most frequently used nonstandard allergens resulted: propylene glycol 0.4%, cobalt chloride 12.6%, phenylmercuric nitrate 2.2%, p-aminophenol 4.5%. The approximate economic cost of patch testing with AS has been evaluated in € 1.3 per single patch test. Conclusion: The cost of patch testing AS is not irrelevant, but it can be compensated by the advantages deriving from the increase of data concerning ACD etiology. A reduction in the number of allergens included in single AS should be performed. Cobalt chloride, taking into account the high percentage of positive reactions observed and its presence in a large number of AS, could be (re)introduced in the standard series.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".