The effectiveness of removal from exposure and reduction of exposure for managing occupational asthma: Summary of an updated Cochrane systematic review
Bibliographic record
Abstract
BACKGROUND: The objective was to update the 2011 Cochrane systematic review on the effectiveness of workplace interventions for the treatment of occupational asthma. METHODS: A systematic review was conducted with the selection of articles and reports through 2019. The quality of extracted data was evaluated, and meta-analyses were conducted using techniques recommended by the Cochrane Handbook for Systematic Reviews of Interventions. RESULTS: Data were extracted from 26 nonrandomized controlled before-and-after studies. The mean number of participants per study was 62 and the mean follow-up time was 4.5 years. Compared with continued exposure, removal from exposure had an increased likelihood of improved symptoms and change in spirometry. Reduction of exposure also had more favorable results for symptom improvement than continued exposure, but no difference for change in spirometry. Comparing exposure removal to reduction revealed an advantage for removal with both symptom improvement and change in spirometry for the larger group of patients exposed to low-molecular-weight agents. Also, the risk of unemployment was greater for exposure removal versus reduction. CONCLUSIONS: Exposure removal and reduction had better outcomes than continued exposure. Removal from exposure was more likely to improve symptoms and spirometry than reduction among patients exposed to low-molecular-weight agents. The potential benefits associated with exposure removal versus reduction need to be weighed against the potential for unemployment that is more likely with removal from exposure. The findings are based on data graded as very low quality, and additional studies are needed to generate higher quality data.
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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 | 0.019 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.017 |
| Bibliometrics | 0.015 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".