Using a symptom diary to investigate work-related urticaria
Bibliographic record
Abstract
BACKGROUND: The strategy of keeping a diary may not be considered by many treating clinicians, but this approach has been recommended for occupational asthma and proved useful in this case of chronic urticaria associated with work. AIMS: To report a case of a health care worker who had significant allergic reactions that were found to be associated with exposure to test allergens while working in an asthma clinic. METHODS: The patient, a nurse working in a paediatric asthma clinic, was known to be allergic to common allergens that were used to test patients in the clinic. She developed reactions including swelling of the eyelids and urticarial reactions on the forehead, torso and upper and lower limbs on different occasions. A symptom diary was used to collect information on the reactions and the activity performed at the time they occurred. RESULTS: She recorded symptoms that were mainly urticarial, with additional rhinitis or wheeze on occasion, on 20 (74%) working days and only 5 (28%) non-work days, indicating a significant association (P < 0.01) between her symptoms and working days. CONCLUSIONS: Medical management had not controlled her symptoms, which improved on removal from the work activity and was confirmed by further diary recording.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".