Are Patch Testing Reactions Underrecognized in Skin of Color? Evaluating the Frequency of Borderline Reactions by Fitzpatrick Skin Type
Bibliographic record
Abstract
Abstract: Background: Patch testing reactions can be difficult to interpret in patients with skin of color (higher Fitzpatrick skin types [FSTs]) due to limited erythema or vesiculation. Missed reactions may lead to prolonged allergic contact dermatitis duration and prevent disease clearance in this population. Objective: To compare the frequency of borderline patch test reactions in patients with different FSTs (I, II, III, IV, V, VI). Methods: Retrospective study of 1899 patients comprehensively patch tested in a major metropolitan area over a 4-year period. Borderline (doubtful, ±) reaction frequency and patient FST were recorded and used for analysis. Results: There were statistically significant differences in the frequency of borderline reactions between FSTs I/II and V/VI ( P < 0.0001) and across all 6 FSTs ( P < 0.0001). Patients with FST V or VI had 43% lower odds of having a borderline reaction (OR: 0.57, 95% CI: 0.47–0.69) compared with patients with FST I or II. Patients with FST VI showed the lowest proportion of borderline reactions. Conclusions: Among patients with skin of color, borderline reactions are diagnosed less commonly and may be missed. This has the potential to prolong dermatitis symptoms and prevent disease clearance.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".