Bicycle injuries presenting to the emergency department during <scp>COVID</scp>‐19 lockdown
Bibliographic record
Abstract
AIM: Since the start of the COVID-19 pandemic, there have been many changes in the presenting complaints in paediatric emergency departments (EDs). We sought to characterise the impact of the COVID-19 pandemic on bicycle-related injuries in children presenting to a tertiary care paediatric ED. METHODS: We conducted a descriptive, cross-sectional study of ED visits to a large urban tertiary children's hospital, comparing March to October 2020 (the study period) to the same date range 2 years prior (i.e. March to October 2018-2019). We included children 0-17.99 years presenting for a bicycle-related injury. We compared absolute visit counts of bike injuries per month, demographics, triage acuity, injury type and disposition. RESULTS: A total of 1215 bike-related visits were analysed. There were 234 presentations in 2018 (March to October), 305 in 2019, and 676 in 2020. Overall, the mean age was 9.5 years (standard deviation 5.5-13.5), there were 67% males, median Canadian Emergency Department Triage and Acuity Scale score was 3 (interquartile range 3-4) and the most common injuries were fractures (n = 471, 38.8%). There were significantly more bike injuries presenting to the ED per month in the COVID group, 33.7(17.9) versus 84.5(61.4) (two-tailed P value = 0.041). There was no statistical difference in 'severe injuries' pre- versus post-COVID (odds ratio 0.815 (95% confidence interval 0.611-1.088), P = 0.165). CONCLUSION: There was a significant increase in bicycle-related injuries presenting to our ED during the pandemic, compared to previous years. Evaluating these trends will allow for the exploration of harm reduction strategies for preventing future bicycle-related injuries.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".