Emergency department presentations for injuries associated with inflatable amusement structures, Canada, 1990-2009
Bibliographic record
Abstract
INTRODUCTION: Inflatable amusement attractions, structures that are air-supported and inflated by a blower, have recently gained popularity. The purpose of this study was to describe the epidemiology of inflatable-related injuries presenting to Canadian emergency departments. METHODS: The Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) is an injury and poisoning surveillance system presently operating in the emergency departments of all 11 pediatric and 4 general hospitals across Canada. The CHIRPP was searched for cases of injuries associated with commercial inflatable amusement structures. RESULTS: Overall, 674 cases were identified over the 20-year surveillance period, during which time the average annual percent increase was 24.6% (95% CI: 21.6, 27.7). Children aged 2 to 9 years were the most frequently injured (59.3/100,000 CHIRPP cases), and fractures accounted for 34.5% of all injuries. DISCUSSION: A sharp increase in emergency department visits for injuries associated with commercial inflatable amusement structures has been observed in recent years. Injury mechanisms could be mitigated by product design modifications and stricter business operational practices.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".