Is metal fume fever a determinant of welding related respiratory symptoms and/or increased bronchial responsiveness? A longitudinal study
Bibliographic record
Abstract
BACKGROUND: The current prospective study investigated the hypothesis of metal fume fever (MFF) being a predictor for the development of respiratory symptoms and functional abnormalities. METHODS: The study consisted of a pre-exposure and two follow up assessments of 286 welding apprentices during an average period of 15 months. A respiratory and a systemic symptom questionnaire, skin prick tests to common allergens and metal salts, spirometry, and methacholine challenge tests were administered. RESULTS: Developing at least one positive skin prick test to a metallic salt solution was found in 11.8% of apprentices. Possible MFF (at least one of fever, feelings of flu, general malaise, chills, dry cough, metallic taste, or shortness of breath) was reported by 39.2% of apprentices. The presence of at least one welding related respiratory symptom (cough, wheezing, or chest tightness) suggestive of welding related asthma was reported by 13.8%. MFF was significantly associated with these respiratory symptoms (OR = 4.92, 95% CI 2.10 to 11.52), after adjusting for age, atopy, smoking, physician diagnosed asthma, and symptoms of non-welding related asthma. Apprentices with possible MFF, and no welding related respiratory symptoms suggestive of welding related asthma at the first follow up, had an increased risk of developing the latter symptoms by the second follow up visit (OR = 7.4, 95% CI 1.97 to 27.45) compared with those not having MFF. MFF was not significantly associated with an increase in bronchial responsiveness. CONCLUSION: MFF could be a predictor for the development of respiratory symptoms but not for functional abnormalities in welders.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".