Dental and maxillofacial injuries associated with electric‐powered bikes and scooters in Israel: A report for 2014‐2019
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND/AIMS: Electric-Powered Bikes and powered scooters present a new method of transportation and are becoming commonly used worldwide. However, the reports on traumatic dental injuries related to their use are scarce. The aim of this study was to report the frequency and severity of dental and maxillofacial injuries associated with electric-powered bikes and scooters in Israel between the years 2014 and 2019. METHODS: This was a retrospective cohort study based on data from the Israeli National Trauma Registry (INTR). The INTR provides comprehensive data on hospitalized patients from all six Level I trauma centers (TC) and 15 of the 20 Level II TCs in Israel. All injured patients who were hospitalized due to a traffic collision between 2014 and 2019 were identified. The data for those hospitalized due to an e-bike or motorized scooter accident were extracted as well as for pedestrians who were injured as a result of a crash with these vehicles. RESULTS: A total of 3,686 hospital admissions were related to electric-powered bikes and scooters. Of those, 378 (10.3%) were oral and maxillofacial injuries. Most of the oral and maxillofacial injuries were attributed to powered bikes (321 out of 378; 84.92%) and the rest to powered scooters. There was a constant increase in general as well as the oral and maxillofacial injuries during the study years. Almost 20% of the cases involved injuries to the teeth. Overall, 291 pedestrians were reported to be injured due to electric-powered bikes and scooters; 29 (9.97%) of them, suffered from oral and maxillofacial injuries. Most of those were children aged 0-15 years (41.38%) and elders older than 60 years (37.39%). CONCLUSIONS: Trauma related to electric-powered bikes and scooters is an increasing concern. Dental professionals should be actively involved in educational and legislative efforts focusing on the prevention of e-bike and scooter-related injuries, in general, and specifically maxillofacial injuries.
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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 | 0.000 | 0.000 |
| 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 it