Aims. Due to the recent rapid expansion of scooter sharing companies, there has been a dramatic increase in the number of electric scooter (e-scooter) injuries. Our purpose was to conduct a systematic review to characterize the demographic characteristics, most common injuries, and management of patients injured from electric scooters. Methods. We searched PubMed, EMBASE, Scopus, and Web of Science databases using variations of the term “electric scooter”. We excluded studies conducted prior to 2015, studies with a population of less than 50, case reports, and studies not focused on electric scooters. Data were analyzed using t-tests and p-values < 0.05 were considered significant. Results. We studied 5,705 patients from 34 studies. The mean age was 33.3 years (SD 3.5), and 58.3% (n = 3,325) were male. The leading mechanism of injury was falling (n = 3,595, 74.4%). Injured patients were more likely to not wear a helmet (n = 2,114; 68.1%; p < 0.001). The most common type of injury incurred was bony injuries (n = 2,761, 39.2%), of which upper limb fractures dominated (n = 1,236, 44.8%). Head and neck injuries composed 22.2% (n = 1,565) of the reported injuries, including traumatic brain injuries (n = 455; 2.5%), lacerations/abrasions/contusions (n = 500; 7.1%), intracerebral brain haemorrhages (n = 131; 1.9%), and concussions (n = 255; 3.2%). Standard radiographs comprised most images (n = 2,153; 57.7%). Most patients were treated and released without admission (n = 2,895; 54.5%), and 17.2% (n = 911) of injured patients required surgery. Qualitative analyses of the cost of injury revealed that any intoxication was associated with higher billing costs. Conclusion. The leading injuries from e-scooters are upper limb fractures. Falling was the leading mechanism of injury, and most patients did not wear a helmet. Future research should focus on injury characterization, treatment, and cost. Cite this article: Bone Jt Open 2022;3(9):674–683

Objectives

Loss of motion following spine segment fusion results in increased strain in the adjacent motion segments. However, to date, studies on the biomechanics of the cervical spine have not assessed the role of coupled motions in the lumbar spine. Accordingly, we investigated the biomechanics of the cervical spine following cervical fusion and lumbar fusion during simulated whiplash using a whole-human finite element (FE) model to simulate coupled motions of the spine.

Objectives. To evaluate the neck strength of school-aged rugby players, and to define the relationship with proxy physical measures with a view to predicting neck strength. Methods. Cross-sectional cohort study involving 382 rugby playing schoolchildren at three Scottish schools (all male, aged between 12 and 18 years). Outcome measures included maximal isometric neck extension, weight, height, grip strength, cervical range of movement and neck circumference. Results. Mean neck extension strength increased with age (p = 0.001), although a wide inter-age range variation was evident, with the result that some of the oldest children presented with the same neck strength as the mean of the youngest group. Grip strength explained the most variation in neck strength (R. 2. = 0.53), while cervical range of movement and neck girth demonstrated no relationship. Multivariable analysis demonstrated the independent effects of age, weight and grip strength, and the resultant model explained 62.1% of the variance in neck strength. This model predicted actual neck strength well for the majority of players, although there was a tendency towards overestimation at the lowest range and underestimation at the highest. Conclusion. A wide variation was evident in neck strength across the range of the schoolchild-playing population, with a surprisingly large number of senior players demonstrating the same mean strength as the 12-year-old mean value. This may suggest that current training regimes address limb strength but not neck strength, which may be significant for future neck injury prevention strategies. Age, weight and grip strength can predict around two thirds of the variation in neck strength, however specific assessment is required if precise data is sought