Patch Test Results among Older Adults: A Retrospective Analysis of the North American Contact Dermatitis® Group Data (2009–2020)
Bibliographic record
Abstract
Abstract: Background: Allergic contact Dermatitis® (ACD) in older adults (OA) represents a significant health burden, but few studies examine the prevalence and characteristics of contact allergy and ACD in this population. Objective: To compare positive and clinically relevant patch test results in OA versus younger adults (YA) and children. Methods: Retrospective analysis of patch test results obtained in OA (≥65 years), YA (19–64 years), and children (≤18 years) by the North American Contact Dermatitis® Group, 2009 to 2020. Results: Of 28,177 patients patch tested, 5366 (19.0%) were OA. OA were more likely to have a final primary diagnosis of ACD as compared with YA (50.8% vs 49.2%, P = 0.035) and children (44.6%, P < 0.0001). The primary site of Dermatitis® also differed by age group, with OA having a higher proportion of Dermatitis® affecting the trunk, scalp, anogenital region, and “under clothing,” and a lower proportion of Dermatitis® affecting the face, lips, and feet. Limitations: Retrospective design, lack of follow-up, and referral population. Conclusion: OA were as likely and were statistically even more likely to have a final primary diagnosis of ACD compared with YA and children. Anatomic site of Dermatitis® also differed by age group. This underscores the need for patch testing in OA when ACD is suspected.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".