Allergic Contact Dermatitis in Operation Iraqi Freedom: Use of the T.R.U.E. Test in the Combat Environment
Bibliographic record
Abstract
BACKGROUND: Refractory dermatitis can frequently cause loss of personnel and poses an economic drain on the military due to the evacuation of civilians and soldiers out of theater. OBJECTIVE: Proof-of-concept retrospective analysis to review the utility of the T.R.U.E. Test in the combat environment. METHODS: Thirty T.R.U.E. Tests were performed by the dermatology clinic in Baghdad, Iraq, between January 15, 2008, and July 15, 2008. Thirty active-duty and civilian contractors referred to the dermatology clinic for dermatitis were tested and four others were clinically rechallenged for suspected bacitracin contact allergy. RESULTS: Of the 30 patients tested, 14 (46.7%) had a positive test reaction to at least one antigen. In these positive tests, nickel, neomycin, and thimersol each comprised 17% followed by neomycin, thimerosal, budesonide, epoxy resin, potassium dichromate, p-phenylenediamine, formaldehyde, quaternium-15, fragrance, and balsam of Peru. All four clinical rechallenges for bacitracin allergy were also positive. CONCLUSIONS: The use of the T.R.U.E. Test in the combat desert environment is an efficient, easy, and clinically relevant method of testing for allergic contact dermatitis. Continued study of the prevalence of allergic contact dermatitis at Ibn Sina Hospital, Baghdad, Iraq, is recommended.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".