Surveillance of acute nonfatal occupational inhalation injuries treated in US hospital emergency departments, 2014–2017
Bibliographic record
Abstract
BACKGROUND: Acute nonfatal occupational inhalation injuries are caused by exposures to airborne toxicants and contaminants in the workplace. A 1990s study found that US emergency department (ED)-based inhalation injury rates were higher than those seen in the United Kingdom and Canada. This study examines 4 years of hospital ED data to estimate current rates of occupational inhalation injuries. METHODS: Data from the National Electronic Injury Surveillance System Occupational Supplement were used to identify nonfatal occupational inhalation injuries treated in US hospital EDs from 2014 to 2017. A workplace inhalation injury was defined as any worker treated in an ED as a result of inhaling a harmful substance at work. RESULTS: From 2014 to 2017, there were an estimated 2.2 occupational inhalation injuries per 10,000 full-time equivalents (FTE) (95% confidence interval [CI]: 1.6-2.8) treated in EDs, a rate nearly four times that found in Bureau of Labor Statistics data. Although men incurred 60% (95% CI: 56%-64%) of the injuries, the overall injury rates for men and women were similar at 2.3 (95% CI: 1.7-2.9) and 2.1 (95% CI: 1.4-2.7) per 10,000 FTE, respectively. By age group, workers less than 25 years of age were at greater risk of injury at 4.1 injuries per 10,000 FTE (95% CI: 2.8-5.3). CONCLUSIONS: These results illustrate the burden of nonfatal occupational inhalation injuries, providing an understanding of how injuries are distributed based on demographics. While inhalation injury rates have declined over the last two decades, additional research is needed to determine whether interventions have reduced risk, or if the availability of alternate sources of medical treatment is a factor.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".