Frequency and Main Sites of Allergic Contact Dermatitis Caused by Nail Varnish
Bibliographic record
Abstract
BACKGROUND: Liquid nail varnish has been used since 1919, and allergic contact dermatitis (ACD) has been recognized for at least 80 years, but it is difficult for nonspecialists to identify this condition. OBJECTIVES: (1) To verify the frequency of ACD from nail varnish in patients with a presumptive diagnosis of contact dermatitis seen at an outpatient clinic, (2) to characterize the groups studied according to site of skin disorder, and (3) to determine the main sensitizer related to varnish. METHODS: Patients with a final diagnosis of ACD caused by nail varnish were assessed by means of retrospective analysis of medical charts and protocols used in the clinic from January 1996 to December 2006. Patch tests with the Brazilian standard series and a complementary series were applied to all patients. RESULTS: Diagnosis of ACD from nail varnish was made in 8% of cases (157 of 1,971). The most affected sites were the face and neck; however, involvement of some uncommon areas, such as periungual and perianal regions, was also observed. CONCLUSIONS: ACD from nail polishes is a common event and recognition of the condition must be improved. Toluenesulfonamide formaldehyde resin (TSFR) was the most common allergen in the group studied.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.000 |
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".