Characteristics of Litigations Involving Contact Dermatitis: An Exploratory Analysis
Bibliographic record
Abstract
Abstract: Background: Contact dermatitis (CD) is one of the most common skin disorders, occurring in >20% of patients worldwide. Estimated cost burden for CD in the United States approaches $1 billion annually. Objective: To describe characteristics of litigation among patients with CD. Methods: Westlaw legal database for U.S. lawsuits was queried for lawsuits between the years 1983 and 2021 containing the keywords “dermatitis or eczema.” Each lawsuit associated with CD was analyzed by plaintiff demographics, verdict, prosecution reason, payouts, and allergen implicated. Results: Of 98 cases, 61 met the inclusion criteria. Verdicts issued favored plaintiffs (42.6%) more than defendants (32.8%) with the remaining cases decided through settlements. If payout occurred, the mean was $246,310 (standard deviation [SD] = $798,536), the median was $20,000 (Q1 = $8,500, Q3 = $88,725, interquartile range = $80,225). The top reason for litigation was toxic exposure ( n = 38, 62.2%), and common contact allergens associated with lawsuits were latex ( n = 4, 20%), surgical tape ( n = 4, 20%), and beauty products ( n = 4, 20%). Conclusion: Common allergens associated with lawsuits include latex, surgical tape, and beauty products. Most CD cases adjudicated in the United States since 1983 are associated with toxic exposures.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".