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Article Abstract
Background: Use of electric bikes (EBs) and electric scooters (ESs) has increased dramatically, and so are EB-related and ES-related orthopaedic injuries. There is limited research regarding the severity of EB injuries and whether they more closely resemble ES, motorcycle (MC), or pedal bicycle (PB) related injuries. The aim of this study was to characterize injury patterns associated with EB accidents and compare injury severity and details with those of PB, ES, and MC accidents.
Methods: This was a retrospective review of trauma patients presenting to an academic, level one trauma center between 2019 and 2022 to compare EB, ES, PB, and MC trauma patients. Descriptive statistics were obtained to characterize demographic data. Two-sided Fisher exact tests were used to compare categorical data, and ANOVA was used to compare continuous variables between groups.
Results: EB trauma patients were significantly more likely to experience traumatic brain injury (TBI), intracranial hemorrhage (ICH), or fractures of the head/face compared with MC (54.0% vs. 19.3%, P < 0.0001) and PB (54.0% vs. 33.5%, P = 0.0001) cohorts. EB trauma patients were more likely to lose consciousness than MC or PB trauma patients. Spine fractures (11.0%) were the most prevalent in the EB study population, followed by fractures of the acetabulum (6.0%) and clavicle/scapula/radius (5.0%). EB trauma patients were significantly more likely to be admitted to the intensive care unit (ICU) than MC trauma patients (25.0% vs. 16.0%, P = 0.0256) and were significantly more likely to present as critical trauma activations than PB trauma patients (14.0% vs. 6.0%, P = 0.0106).
Conclusions: While the overall injury severity scores are similar to the modes of transport, there are differences in injury severity and patterns. EB accidents have a higher prevalence of TBIs, ICH, and facial fractures. EB trauma patients can result in high utilization of resources because many are critical trauma activations and have a higher rate of ICU stays. These data can help providers better understand injury patterns of EB accidents.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12168694 | PMC |
| http://dx.doi.org/10.5435/JAAOSGlobal-D-25-00099 | DOI Listing |
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