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.
In the past decade, there has been a rapid increase in use of electric bikes (e-bikes) and electric scooters (e-scooters) because of accessibility and urbanization as well as becoming a more favorable economic and environmental option for transportation.1-5 An increase in popularity could also be due in part to advertisements as a way to “increase physical activity”, increased reliance since the pandemic secondary to social distancing, mandates closing public transportation and overall habit and infrastructure change.6–8
With this increase in popularity and usage, there has been a rise in e-bike/e-scooter–associated injuries and emergency department (ED) visits and hospitalizations, with most of them (up to 81%) being orthopaedic related.6,9 Previous work has found that up to 25% of ED visits for e-bike/e-scooter injuries result in hospital admissions. The average cost of an admission for e-bike/e-scooter–associated injury has been found to be up to 12,000 USD while ED visits have been found to cost an average of 1,000 USD.5 This financial strain on the healthcare system has been characterized both nationally and internationally.10-12
The reason for the spike in injuries and healthcare costs associated with e-transportation is twofold. First, owing to the rapid rise in use and popularity of these electric alternative modes of transportation, there is a lack of consensus involving laws, rules, or regulations for protective gear and/or age mandates and if present, they are difficult to enforce.3 Second, riders have been known to turn to e-bikes/e-scooters when they are unable to drive, because of either lack of licensure or drug/alcohol intoxication. Altogether, this lack of regulation and unique rider population have contributed to a large strain on the healthcare system.3,6
The details and context of e-bike/e-scooter accidents are inconsistently tracked, and there is a lack of consensus on which variables, such as alcohol intoxication, injury environment, and speed, affect injury severity or type markedly.6,9 In addition, there is limited work on fracture patterns associated with these accidents as well as comparison of the injury patterns/details with those of standard bicycles and motorcycles.1 Because the maximum speed of these vehicles is 15 to 28 miles per hour (mph), the question of whether the injury patterns are more similar to bicycles versus motorcycles remains.2,4,6,13 The aim of this study was to better characterize injury patterns, particularly involving orthopaedics, associated with e-bike accidents and compare injury severity and details with those of e-scooter, pedal bicycle, and motorcycle accidents.
Methods
This was a retrospective review of trauma patients presenting to a single academic, level one trauma center between 2019 and 2022. Institutional review board approval was obtained to query an internal general surgery trauma database for patients presenting as trauma activations after e-bike (EB), e-scooter (ES), motorcycle (MC), and pedal bicycle (PB) accidents. The database was used to determine demographic information (age, sex, race, body mass index [BMI], race, ethnicity), level of trauma activation (critical, moderate), information about presentation (use of helmet/protective clothing, loss of consciousness [LOC], drug or alcohol intoxication, etc), injuries (injury severity score [ISS], transfusion requirements, initial workup requirements, etc), hospital course (length of stay [LOS], admission to intensive care unit [ICU], use of a ventilator, days on ventilator, etc), and discharge destination (home, skilled nursing facility, acute rehabilitation facility, jail, leaving against medical advice, death, etc). Review of individual patient charts was then conducted to confirm the mechanism of injury and other database variables; determine time of presentation; and clarify imaging performed, injuries sustained, and operations or procedures performed during the initial admission.
Patients were excluded from the study if chart review revealed a different mechanism of injury than the database query had returned (eg, all-terrain vehicle or powered wheelchair accidents) or if there was insufficient information from the database to locate the electronic medical record. Patients who presented and expired before a full orthopaedic/fracture workup could be completed were included for analysis and comparison of demographic information, ISS, and other obtainable variables but were excluded from fracture pattern or imaging resource comparison because it was not possible to determine what orthopaedic injuries they may or may not have sustained. BMIs that were missing, ≤12, or ≥65 were categorized as unknown because of high probability of height/weight charting error. Patients who tested positive on drug screen but were noted to have received narcotics during transport to the hospital were excluded from analysis of urine drug screening. Injuries were considered dichotomous variables and were classified as lacerations requiring bedside closure, fractures, dislocations, traumatic arthrotomies, or any injury (inclusive of all injury types) across specified body regions. Surgical characteristics and imaging studies obtained throughout the admission were similarly categorized as dichotomous variables by body region.
Descriptive statistics were obtained to characterize demographic data and frequency distribution of injuries, presentation details, ED management, imaging utilization, and surgeries. Two-sided Fisher exact tests were used to compare categorical data between groups using EB as the reference group while one-way ANOVA with the post hoc Tukey test was used to compare continuous variables between groups. Significance level was set at P < 0.05.
Results
Demographics
A total of 1,917 patients were identified in the database who met inclusion criteria (EB n = 100, ES n = 63, MC n = 1,086, PB n = 668) (Table 1). The EB cohort was significantly older than the ES (49.2 ± 16.7 years vs. 40.5 ± 15.8 years, P = 0.0018) and MC (49.2 ± 16.7 years vs. 37.1 ± 13.7 years, P < 0.0001) cohorts, but not significantly different from the PB cohort (49.2 ± 16.7 years vs. 46.8 ± 16.2 years, P = 0.4495). In addition, the EB cohort consisted of more women compared with the MC (24.2% vs. 7.6%, OR 3.867, P < 0.0001) and PB (24.2% vs. 14.7%, OR 1.861, P = 0.0186) cohorts, and more non-Hispanic individuals compared with any cohort (94.0% vs. ES 66.3%, OR 7.954, P < 0.0001; MC 61.6%, OR 9.760, P < 0.0001; PB 64.3%, OR 8.704, P < 0.0001). Caucasian race was the most common in all groups (EB 69.0%, ES 54.0%, MC 65.1%, PB 60.2%), followed by Asian for EB (16.0%) and ES (23.8%) groups and other for MC (24.3%) and PB (24.1%) groups. No significant differences were observed in BMI between any groups compared with the EB cohort.
Table 1.
Demographics of E-Bike, E-Scooter, Motorcycle, and Pedal Bicycle Cohorts
| Characteristic | E-bike (n = 100) | E-scooter (n = 63) | Motorcycle (n = 1,086) | Bicycle (n = 668) |
| Age [years, n, (%)] | ||||
| Mean (SD) | 49.2 (16.7) | 40.5 (15.8) | 37.1 (13.7) | 46.8 (16.2) |
| Median | 51.5 | 38.0 | 33.0 | 47.0 |
| Range | 20-85 | 18-84 | 18-92 | 18-83 |
| 18-25 | 12 (12.0) | 13 (20.6) | 253 (23.3) | 67 (10.0) |
| 26-40 | 22 (22.0) | 20 (31.7) | 453 (41.7) | 184 (27.5) |
| 41-64 | 45 (45.0) | 26 (41.3) | 340 (31.3) | 322 (48.2) |
| 65+ | 21 (21.0) | 4 (6.3) | 40 (3.7) | 95 (14.2) |
| Sex (n, %) | ||||
| Male | 75 (75.0) | 51 (81.0) | 1003 (92.4) | 570 (85.3) |
| Female | 24 (24.0) | 12 (19.0) | 83 (7.6) | 98 (14.7) |
| Nonbinary | 1 (1.0) | 0 (0) | 0 (0) | 0 (0) |
| Race (n, %) | ||||
| Caucasian | 69 (69) | 34 (54.0) | 706 (65.1) | 402 (60.2) |
| African American | 0 (0) | 0 (0) | 40 (3.7) | 8 (1.2) |
| Hispanic | 0 (0) | 0 (0) | 2 (0.2) | 6 (0.9) |
| Asian | 16 (16.0) | 15 (23.8) | 66 (6.1) | 84 (12.6) |
| Pacific Islander | 0 (0) | 0 (0) | 2 (0.2) | 0 (0) |
| Native American | 0 (0) | 0 (0) | 1 (0.1) | 1 (0.1) |
| Other | 14 (14.0) | 14 (22.2) | 264 (24.3) | 161 (24.1) |
| Unknown | 1 (1.0) | 0 (0) | 4 (0.4) | 6 (0.9) |
| Ethnicity (n, %) | ||||
| Hispanic | 6 (6.0) | 21 (33.3) | 411 (38.0) | 232 (34.7) |
| Non-Hispanic | 94 (94.0) | 41 (65.1) | 665 (61.3) | 424 (63.5) |
| Unknown | 0 (0) | 1 (1.6) | 8 (0.7) | 12 (1.8) |
| BMI [kg/m2, n, (%)] | ||||
| Mean (SD) | 26.9 (5.1) | 27.6 (5.0) | 27.8 (5.5) | 26.4 (5.0) |
| Median | 26.4 | 27.0 | 27.3 | 25.7 |
| Range | 14.6-42.6 | 16.4-42.2 | 14.4-60.4 | 16.7-51.4 |
| <18.5 | 2 (2.0) | 2 (3.2) | 19 (1.8) | 11 (1.7) |
| 18.5-24.9 | 35 (35.0) | 15 (23.8) | 316 (29.5) | 275 (41.4) |
| 25.0-29.9 | 35 (35.0) | 32 (50.8) | 433 (40.4) | 240 (36.1) |
| 30.0-34.9 | 21 (21.0) | 8 (12.7) | 198 (18.5) | 88 (13.2) |
| 35.0-39.9 | 6 (6.0) | 4 (6.3) | 81 (7.5) | 29 (4.4) |
| >40 | 1 (1.0) | 2 (3.2) | 25 (2.3) | 14 (2.1) |
BMI = body mass index.
Electric Bike Descriptive Analysis
Within the EB cohort, 34.0% of patients were between 18 and 40 years (Table 1). Approximately one in four patients (23.0%) reported wearing a helmet, and approximately two-thirds reported LOC (63.0%) (Table 2). Time of presentation to the ED was mostly split between 7 am to 3 pm (40.0%) and 3 pm to 11 pm (52.0%), with only 8.0% presenting from 11 pm to 7 am. Most of EB trauma patients arrived at the ED through EMS trauma transportation (90.0%), but there were also 4.0% of patients who were transfers from an outside hospital and 2.0% who self-presented. On presentation, 86.0% were treated as critical trauma activations and 14.0% were treated as moderate trauma activations. Positive alcohol screening was recorded in 40.0% of patients, and drug testing was positive for 42.0% of patients, excluding one case (1.0%) in which the patient received narcotics in field and 6.0% of patients who were not tested.
Table 2.
Accident Characteristics Compared Between Cohorts
| Characteristic | E-bike (n = 100) | E-scooter (n = 63) | Motorcycle (n = 1086) | Bicycle (n = 668) |
| Helmet (n, %) | ||||
| Yes | 23 (23.0) | 22 (34.9) | 1030 (95.0) | 233 (34.9) |
| No | 77 (77.0) | 41 (65.1) | 54 (5.0) | 435 (65.1) |
| LOC (n, %) | ||||
| Yes | 63 (63.0) | 28 (44.4) | 254 (23.5) | 253 (38.2) |
| No | 32 (32.0) | 30 (47.6) | 764 (70.7) | 364 (55.0) |
| Unknown | 5 (5.0) | 5 (7.9) | 63 (5.8) | 45 (6.8) |
| Method of arrival (n, %) | ||||
| Self-presentation | 2 (2.0) | 3 (4.8) | 29 (2.7) | 15 (2.2) |
| EMS nontrauma | 0 (0) | 0 (0) | 4 (0.4) | 3 (0.4) |
| EMS trauma | 90 (90.0) | 49 (79.0) | 1019 (94.0) | 602 (90.3) |
| Transfer from OSH | 6 (6.0) | 10 (16.1) | 30 (2.8) | 47 (7.0) |
| Unknown | 2 (2.0) | 0 (0) | 2 (0.2) | 0 (0) |
| Time of arrival (n, %) | ||||
| 7 am-3 pm | 40 (40.0) | 20 (31.7) | 349 (32.1) | 255 (38.2) |
| 3 pm-11 pm | 52 (52.0) | 33 (52.4) | 610 (56.2) | 313 (46.9) |
| 11 pm-7 am | 8 (8.0) | 10 (15.9) | 126 (11.6) | 99 (14.8) |
| Unknown | 0 (0) | 0 (0) | 1 (0.1) | 1 (0.1) |
| Trauma activation level (n, %) | ||||
| Moderate | 86 (86.0) | 55 (88.7) | 978 (90.1) | 610 (91.6) |
| Critical | 14 (14.0) | 3 (4.8) | 100 (9.2) | 40 (6.0) |
| Other | 0 (0) | 4 (6.5) | 8 (0.7) | 16 (2.4) |
| Alcohol (n, %) | ||||
| Yes | 40 (40.0) | 14 (22.2) | 183 (16.9) | 112 (16.8) |
| No | 59 (59.0) | 47 (74.6) | 887 (81.7) | 544 (81.4) |
| Unknown | 1 (1.0) | 2 (3.2) | 16 (1.5) | 12 (1.8) |
| Drugs (n, %) | ||||
| Yes | 42 (42.0) | 29 (46.0) | 507 (46.7) | 280 (41.9) |
| Yes, given in field | 1 (1.0) | 3 (4.8) | 93 (8.6) | 37 (5.5) |
| No | 50 (50.0) | 27 (42.9) | 300 (27.6) | 248 (37.1) |
| Not tested | 6 (6.0) | 4 (6.3) | 84 (7.7) | 45 (6.7) |
| Unknown | 1 (1.0) | 0 (0) | 102 (9.4) | 58 (8.7) |
EMS = emergency medical service; LOC = loss of consciousness; OSH = outside hospital
The three most common injuries identified within the EB cohort included injuries to the head/face (70.0% overall with fractures occurring in 54.0% of the EB cohort), lacerations (30.0%), and chest injuries (26.0% overall with rib fractures occurring in 24.0% of the EB cohort) (Table 3). Of the orthopaedic injuries, spine fractures (11.0%) were the most prevalent in the study population, followed by fractures of the acetabulum (6.0%), clavicle (5.0%), scapula (5.0%), and radius (5.0%). When stratifying by extremity injuries, any injury to the upper extremities was more common than to the lower extremities (23.0% vs. 18.0%). Of the upper extremity, order of fracture prevalence included clavicle, scapula, and radius (all 5.0%), humerus (4.0%), ulna (2.0%), and hand (1.0%). Of the lower extremity, order of fracture prevalence included acetabulum (6.0%), fibula (4.0%), pelvis (3.0%), tibial plateau (2.0%), tibial shaft (2.0%), distal tibia (2.0%) [combined tibial fracture prevalence of 6.0%], foot (2.0%), and femur (1.0%). Overall, 19.0% of EB patients sustained injuries requiring surgery. Of these 19 patients requiring surgery, 17 required only one trip to the operating room and only two patients returned to the operating room on two separate occasions during the admission (Table 4). Intrathoracic/intra-abdominal surgical interventions were most frequent (n = 7), followed by head/face and radius operations (both n = 3) and acetabulum, tibial shaft, distal tibia, and fibula operations (each n = 2). Notably, although spine fractures were the most prevalent orthopaedic injury, there were no spine fracture cases that required surgical management.
Table 3.
Injury Severity and Profiles by Type of Injury and Injury Location Across Cohorts
| Characteristic | E-bike (n = 100) | E-scooter (n = 63) | Motorcycle (n = 1086) | Bicycle (n = 668) |
| ISS (n, %) | ||||
| Mean (SD) | 9.8 (9.4) | 8.8 (8.0) | 9.6 (9.8) | 8.6 (8.6) |
| Median | 6.0 | 5.0 | 5.0 | 5.0 |
| Range | 1-54 | 1-43 | 0-66 | 0-75 |
| 0 | 0 (0) | 0 (0) | 3 (0.3) | 7 (1.1) |
| 1-5 | 48 (48.0) | 34 (54.0) | 550 (50.9) | 341 (51.4) |
| 6-10 | 23 (23.0) | 10 (15.9) | 187 (17.3) | 132 (19.9) |
| 11-15 | 10 (10.0) | 11 (17.5) | 120 (11.1) | 72 (10.8) |
| 16-20 | 6 (6.0) | 4 (6.3) | 89 (8.2) | 50 (7.5) |
| 21-25 | 5 (5.0) | 2 (3.2) | 44 (4.1) | 26 (3.9) |
| 26-30 | 4 (4.0) | 0 (0) | 39 (3.6) | 17 (2.6) |
| 31-35 | 3 (3.0) | 1 (1.6) | 20 (1.9) | 10 (1.5) |
| 36-40 | 0 (0) | 0 (0) | 6 (0.6) | 4 (0.6) |
| 41-45 | 0 (0) | 1 (1.6) | 13 (1.2) | 3 (0.5) |
| 46-50 | 0 (0) | 0 (0) | 5 (0.5) | 1 (0.2) |
| 51-55 | 1 (1.0) | 0 (0) | 1 (0.1) | 0 (0) |
| 55-75 | 0 (0) | 0 (0) | 3 (0.3) | 1 (0.2) |
| Any injury (n, %) | ||||
| Head/face | 70 (70.0) | 37 (58.7) | 283 (26.1) | 333 (49.9) |
| Chest | 27 (26.0) | 13 (20.6) | 317 (29.2) | 158 (23.7) |
| Intrathoracic/intra-abdominal | 21 (21.0) | 18 (28.6) | 312 (28.7) | 139 (20.8) |
| Pelvis | 8 (8.0) | 0 (0) | 145 (13.4) | 58 (8.7) |
| Spine | 13 (13.0) | 7 (11.1) | 194 (17.9) | 118 (17.7) |
| Upper extremity | 23 (23.0) | 21 (33.3) | 484 (44.6) | 177 (26.5) |
| Lower extremity | 18 (18.0) | 11 (17.5) | 420 (38.7) | 114 (17.1) |
| Laceration (n, %) | ||||
| Yes | 30 (30.0) | 14 (22.2) | 277 (25.5) | 188 (28.1) |
| Dislocation (n, %) | ||||
| Yes | 2 (2.0) | 6 (9.5) | 93 (8.6) | 19 (2.8) |
| Traumatic arthrotomy (n, %) | ||||
| Yes | 4 (4.0) | 2 (3.2) | 39 (3.6) | 8 (1.2) |
| Fracture (n, %) | ||||
| Head/face | 54 (54.0) | 35 (55.6) | 210 (19.3) | 224 (33.5) |
| Chest/ribs | 24 (24.0) | 12 (19.0) | 279 (25.7) | 144 (21.6) |
| Clavicle | 5 (5.0) | 8 (12.7) | 111 (10.2) | 60 (9.0) |
| Scapula | 5 (5.0) | 2 (3.2) | 74 (6.8) | 34 (5.1) |
| Humerus | 4 (4.0) | 1 (1.6) | 43 (4.0) | 6 (0.9) |
| Ulna | 2 (2.0) | 1 (1.6) | 94 (8.7) | 14 (2.1) |
| Radius | 5 (5.0) | 2 (3.2) | 117 (10.8) | 23 (3.4) |
| Hand | 1 (1.0) | 2 (3.2) | 142 (13.1) | 28 (4.2) |
| Pelvis | 3 (3.0) | 0 (0) | 88 (8.1) | 30 (4.5) |
| Acetabulum | 6 (6.0) | 0 (0) | 38 (3.5) | 16 (2.4) |
| Femur | 1 (1.0) | 3 (4.8) | 80 (7.4) | 19 (2.8) |
| Tibial plateau | 2 (2.0) | 3 (4.8) | 40 (3.7) | 6 (0.9) |
| Tibial shaft | 2 (2.0) | 3 (4.8) | 68 (6.3) | 15 (2.2) |
| Tibial plafond | 2 (2.0) | 1 (1.6) | 67 (6.2) | 20 (3.0) |
| Fibula | 4 (4.0) | 4 (6.3) | 150 (13.8) | 33 (4.9) |
| Foot | 2 (2.0) | 0 (0) | 123 (11.3) | 14 (2.1) |
| Spine | 11 (11.0) | 7 (11.1) | 188 (17.3) | 114 (17.1) |
ISS = injury severity score
Table 4.
Surgical Rates by Body Region and Number of Operations Performed During Admission Compared Between Cohorts
| Characteristic | E-bike (n = 100) | E-scooter (n = 63) | Motorcycle (n = 1086) | Bicycle (n = 668) |
| Required surgery (n, %) | ||||
| Any surgery | 19 (19.0) | 17 (27.0) | 367 (33.8) | 115 (17.2) |
| Head/face | 3 (3.0) | 3 (4.8) | 13 (1.2) | 20 (3.0) |
| Chest/ribs | 1 (1.0) | 1 (1.6) | 13 (1.2) | 11 (1.6) |
| Clavicle | 1 (1.0) | 1 (1.6) | 8 (0.7) | 6 (0.9) |
| Scapula | 0 (0) | 0 (0) | 11 (1.0) | 5 (0.7) |
| Humerus | 1 (1.0) | 0 (0) | 25 (2.3) | 3 (0.4) |
| Ulna | 1 (1.0) | 0 (0) | 49 (4.5) | 5 (0.7) |
| Radius | 3 (3.0) | 1 (1.6) | 77 (7.1) | 9 (1.3) |
| Hand | 1 (1.0) | 2 (3.2) | 60 (5.5) | 4 (0.6) |
| Pelvis | 0 (0) | 0 (0) | 49 (4.5) | 9 (1.3) |
| Acetabulum | 2 (2.0) | 0 (0) | 15 (1.4) | 4 (0.6) |
| Femur | 1 (1.0) | 3 (4.8) | 71 (6.5) | 19 (2.8) |
| Tibial plateau | 1 (1.0) | 1 (1.6) | 26 (2.4) | 2 (0.3) |
| Tibial shaft | 2 (2.0) | 2 (3.2) | 64 (5.9) | 11 (1.6) |
| Tibial plafond | 2 (2.0) | 1 (1.6) | 37 (3.4) | 13 (1.9) |
| Fibula | 2 (2.0) | 3 (4.8) | 77 (7.1) | 22 (3.3) |
| Foot | 1 (1.0) | 0 (0) | 38 (3.5) | 1 (0.1) |
| Spine | 0 (0) | 1 (1.6) | 13 (1.2) | 11 (1.6) |
| Arthrotomy | 2 (2.0) | 1 (1.6) | 30 (2.8) | 3 (0.4) |
| No. of operations (n, %) | ||||
| Mean (SD) | 0.2 (0.5) | 0.3 (0.6) | 0.6 (1.3) | 0.2 (0.6) |
| Median | 0 | 0 | 0 | 0 |
| Range | 0-2 | 0-2 | 0-18 | 0-5 |
| 0 | 81 (81.0) | 46 (73.0) | 719 (66.2) | 553 (82.8) |
| 1 | 17 (17.0) | 13 (20.6) | 209 (19.2) | 86 (12.9) |
| 2 | 2 (2.0) | 4 (6.3) | 85 (7.8) | 24 (3.6) |
| 3 | 0 (0) | 0 (0) | 42 (3.9) | 2 (0.3) |
| 4 | 0 (0) | 0 (0) | 11 (1.0) | 1 (0.1) |
| 5 | 0 (0) | 0 (0) | 10 (0.9) | 2 (0.3) |
| >5 | 0 (0) | 0 (0) | 10 (0.9) | 0 (0) |
For overall imaging obtained during admission, 100% of the EB patients received at least one CT scan, with CT cervical spine (98.0%), CT head (96.0%), CTA chest (95.0%), CT pelvis (95.0%), and CT abdomen (94.0%) as most common (Table 5). The high incidence of these scans likely reflect the initial injury survey as part of trauma activation protocols in the ED because CTA neck—the next most frequently completed CT scan—was markedly lower in prevalence (59.0%). Similarly, plain radiographs were obtained in 98.0% of the EB cohort with chest radiographs being most common by far (96.0%), followed by knee (55.0%), hand (45.0%), and elbow (35.0%). When stratifying by extremity, upper and lower extremity CT scans were done with equal prevalence (6.0% each). Radiographs for the upper extremity by order of prevalence included hand (45.0%), elbow (35.0%), shoulder (26.0%), wrist (22.0%), forearm (21.0%), clavicle (10.0%), and humerus (6.0%). Radiographs for the lower extremity by order of prevalence included knee (55.0%), tibia/fibula (24.0%), ankle (22.0%), pelvis (19.0%), femur (15.0%), foot (14.0%), and hip (6.0%). MR imaging was relatively uncommon, with MRI brain obtained in 2 patients (2.0%), and cervical spine and upper extremity each occurring in only one patient (1.0% each).
Table 5.
Incidence of Imaging Studies Obtained During Admission for Evaluation of Injuries Sustained by Each Cohort
| Characteristic | E-bike (n = 100) | E-scooter (n = 63) | Motorcycle (n = 1086) | Bicycle (n = 668) |
| XR (n, %) | ||||
| Any XR | 98 (98.0) | 63 (100.0) | 1076 (99.3) | 659 (98.8) |
| Chest | 96 (96.0) | 63 (100.0) | 1065 (98.2) | 648 (97.2) |
| Shoulder | 26 (26.0) | 28 (44.4) | 378 (34.9) | 217 (32.5) |
| Clavicle | 10 (10.0) | 8 (12.7) | 119 (11.0) | 66 (9.9) |
| Humerus | 6 (6.0) | 6 (9.5) | 190 (17.5) | 64 (9.6) |
| Elbow | 35 (35.0) | 16 (25.4) | 475 (43.8) | 221 (33.1) |
| Forearm | 21 (21.0) | 11 (17.5) | 374 (34.5) | 118 (17.7) |
| Wrist | 22 (22.0) | 12 (19.0) | 366 (33.8) | 104 (15.6) |
| Hand | 45 (45.0) | 20 (31.7) | 459 (42.3) | 223 (33.4) |
| Spine | 5 (5.0) | 5 (7.9) | 84 (7.7) | 55 (8.2) |
| KUB | 5 (5.0) | 1 (1.6) | 39 (3.6) | 28 (4.2) |
| Pelvis | 19 (19.0) | 9 (14.3) | 235 (21.7) | 121 (18.1) |
| Hip | 6 (6.0) | 2 (3.2) | 45 (4.2) | 26 (3.9) |
| Femur | 15 (15.0) | 11 (17.5) | 285 (26.3) | 121 (18.1) |
| Knee | 55 (55.0) | 27 (42.9) | 706 (65.1) | 333 (49.9) |
| Tibia/fibula | 24 (24.0) | 13 (20.6) | 472 (43.5) | 156 (23.4) |
| Ankle | 22 (22.0) | 9 (14.3) | 441 (40.7) | 136 (20.4) |
| Foot | 14 (14.0) | 5 (7.9) | 348 (32.1) | 84 (12.6) |
| Other | 12 (12.0) | 2 (3.2) | 149 (13.8) | 72 (10.8) |
| CT (n, %) | ||||
| Any CT | 100 (100) | 62 (98.4) | 1065 (98.2) | 654 (98.1) |
| Head | 96 (96.0) | 57 (90.5) | 889 (82.0) | 584 (87.6) |
| CTA neck | 59 (59.0) | 37 (58.7) | 482 (44.5) | 298 (44.7) |
| Maxillofacial | 39 (39.0) | 21 (33.3) | 108 (10.0) | 192 (28.8) |
| CTA chest | 95 (95.0) | 58 (92.1) | 1035 (95.5) | 594 (89.1) |
| Abdomen | 94 (94.0) | 59 (93.7) | 1036 (95.6) | 606 (90.9) |
| Pelvis | 95 (95.0) | 59 (93.7) | 1033 (95.3) | 606 (90.9) |
| Cervical spine | 98 (98.0) | 57 (90.5) | 955 (88.1) | 597 (89.5) |
| Thoracic spine | 30 (30.0) | 20 (31.7) | 425 (39.2) | 264 (39.6) |
| Lumbar spine | 29 (29.0) | 20 (31.7) | 426 (39.3) | 263 (39.4) |
| Upper extremity | 6 (6.0) | 1 (1.6) | 115 (10.6) | 24 (3.6) |
| Lower extremity | 6 (6.0) | 6 (9.5) | 185 (17.1) | 33 (4.9) |
| Cystogram | 1 (1.0) | 0 (0) | 62 (5.7) | 14 (2.1) |
| Other | 16 (16.0) | 12 (19.0) | 131 (12.1) | 78 (11.7) |
| MRI (n, %) | ||||
| Any MRI | 5 (5.0) | 8 (12.7) | 88 (8.1) | 64 (9.6) |
| Brain | 2 (2.0) | 2 (3.2) | 23 (2.1) | 25 (3.7) |
| Chest | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| Abdomen | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| Pelvis | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| Cervical spine | 1 (1.0) | 5 (7.9) | 34 (3.1) | 32 (4.8) |
| Thoracic spine | 0 (0) | 3 (4.8) | 12 (1.1) | 14 (2.1) |
| Lumbar spine | 0 (0) | 0 (0) | 9 (0.8) | 11 (1.6) |
| Upper extremity | 1 (1.0) | 1 (1.6) | 10 (0.9) | 2 (0.3) |
| Lower extremity | 0 (0) | 0 (0) | 30 (2.8) | 5 (0.7) |
| Other | 4 (4.0) | 1 (1.6) | 3 (0.3) | 4 (0.6) |
CT = computed tomography; CTA = computed tomography angiogram; KUB = kidney ureter bladder; MRI = magnetic resonance imaging; XR = plain radiograph
Accident Characteristics
EB patients were significantly less likely to wear a helmet and more likely to lose consciousness than MC or PB patients (helmet use: EB 23.0% vs. MC 95.0%, P < 0.0001, vs. PB 34.9%, P = 0.0225; LOC: EB 63.0% vs. MC 23.5%, P < 0.0001, vs. PB 38.2%, P < 0.001) (Table 2). Perhaps unsurprisingly, EB patients were also significantly more likely to present as critical trauma activations than PB patients (14.0% vs. 6.0%, P = 0.0106), although there were no significant differences between groups regarding method of arrival (eg, self-presentation and emergency medical services transport) or time of arrival. Positive alcohol screening on presentation was more common in EB patients than any other group (EB 40.4% vs. ES 23.0%, P = 0.0260, vs. MC 17.1%, P < 0.0001, vs. PB 17.1%, P < 0.0001). Contrastingly, they were significantly less likely to test positive on a urine drug screen than motorcycle users (EB 42.0% vs. MC 47.0%, P = 0.0022) and had no significant difference in drug positivity compared with ES or PB cohorts.
Injury Profile and Severity
Overall, the mean ISS was not markedly different between any of the groups (Table 3). When compared with ES patients, EB patients were only significantly more likely to experience a pelvic injury (8.0% vs. 0.0%, P = 0.0236); however, pelvic fracture rates and any dislocation or laceration rates were not markedly different between the groups.
When compared with MC patients, EB patients were significantly more likely to experience an injury to the head/face (70.0% vs. 26.1%, P < 0.0001) and significantly less likely to experience an injury to the upper extremity (23.0% vs. 44.6%, P < 0.0001) or the lower extremity (18.0% vs. 38.7%, P < 0.0001), or any dislocation (2.0% vs. 8.6%, P = 0.0189). Specifically, EB patients were significantly more likely than MC patients to experience traumatic brain injury (TBI), intracranial hemorrhage (ICH), or fractures of the head/face (54.0% vs. 19.3%, P < 0.0001) and significantly less likely to experience fractures of the ulna (2.0% vs. 8.7%, P = 0.0193), hand (1.0% vs. 13.1%, P < 0.0001), femur (1.0% vs. 7.4%, P = 0.0112), fibula (4.0% vs. 13.8%, P = 0.0029), and foot (2.0% vs. 11.3%, P = 0.0018).
When compared with PB patients, EB patients were significantly more likely to experience an injury to the head/face (70.0% vs. 49.9%, P = 0.0002) and were specifically more likely to experience TBI, ICH, or fractures of the head/face (54.0% vs. 33.5%, P = 0.0001). EB patients were also significantly more likely than PB patients to experience fractures of the humerus (4.0% vs. 0.9%, P = 0.0305).
Surgical Intervention
Overall, patients in the MC group were more likely to receive a surgical intervention (EB 19.0% vs. MC 33.8%, P = 0.0024) and had a greater mean number of operations during the admission (EB mean = 0.21 ± 0.46 vs. MC mean = 0.64 ± 1.3, P = 0.0007) (Table 4). Specifically, the MC group had greater rates of pelvic and femur injuries requiring surgical intervention compared with the EB group (pelvic: EB 0.0% vs. MC 2.5%, P = 0.0299; femur: EB 1.0% vs. MC 6.5%, P = 0.0255).
Imaging Workup During Admission
When compared with ES patients, EB patients were significantly less likely to receive shoulder radiographs (26.0% vs. 44.4%, P = 0.0173) and cervical spine MRI (1.0% vs. 7.9%, P = 0.0325) (Table 5).
When compared with MC patients, EB patients were significantly more likely to receive CT scans of the head (96.0% vs. 82.0%, P < 0.0001), cervical spine (98.0% vs. 88.1%, P = 0.0008), and maxillofacial regions (39.0% vs. 10.0%, P < 0.0001), as well as a CT angiogram of the neck (59.0% vs. 44.5%, P = 0.0062) and “other” MRI scans (4.0% vs. 0.3%, P = 0.0014). EB patients were less likely than MC patients to receive CT scans of the lower extremity (6.0% vs. 17.1%, P = 0.0026) or CT cystography (1.0% vs. 5.7%, P = 0.0368), as well as radiographs of the humerus (6.0% vs. 17.5%, P = 0.0018), forearm (21.0%% vs. 34.5%, P = 0.0055), wrist (22.0% vs. 33.8%, P = 0.0189), femur (15.0% vs. 26.3%, P = 0.0116), knee (55.0% vs. 65.1%, P = 0.0495), tibia/fibula (24.0% vs. 43.5%, P = 0.0001), ankle (22.0% vs. 40.7%, P = 0.0002), and foot (14.0% vs. 32.1%, P < 0.0001).
When compared with PB patients, EB patients were significantly more likely to receive a CT scan of the head (96.0% vs. 87.6%, P = 0.0105), cervical spine (98.0% vs. 89.5%, P = 0.0049), and maxillofacial region (39.0% vs. 28.8%, P = 0.0465), as well as a CT angiogram of the neck (59.0% vs. 44.7%, P = 0.0096), radiograph of the hand (45.0% vs. 33.4%, P = 0.0321), and “other” MRI scans (4.0% vs. 0.6%, P = 0.0126). On the contrary, EB patients were less likely to receive a CT scan of the lumbar spine (29.0% vs. 39.4%, P = 0.0472).
Management and Disposition
Mean hospital LOS was not significantly different between any of the groups; however, EB patients were significantly more likely to be admitted to the ICU than MC patients (25.0% vs. 16.0%, P = 0.0256) (Table 6). No significant differences were observed in ventilator requirements or mean days spent on a ventilator, blood product infusion requirements, or rates of interventional radiology procedures such as arterial embolization. Discharge to home was the most common destination for all groups, and discharge rates to home compared with nonhome locations were not markedly different for any group compared with the EB group.
Table 6.
Medical Management and Hospital Disposition Characteristics for Each Mode of Transport
| Characteristic | E-bike (n = 100) | E-scooter (n = 63) | Motorcycle (n = 1086) | Bicycle (n = 668) |
| Blood/FFP/platelets (n, %) | ||||
| Yes | 1 (1.0) | 1 (1.6) | 59 (5.4) | 21 (3.1) |
| Unknown | 41 (41.0) | 3 (4.8) | 1 (0.1) | 1 (0.1) |
| Interventional radiology procedure (n, %) | ||||
| Yes | 2 (2.0) | 3 (4.8) | 30 (2.8) | 9 (1.3) |
| Unknown | 40 (40.0) | 3 (4.8) | 3 (0.3) | 1 (0.1) |
| Sedation (n, %) | ||||
| Yes | 1 (1.0) | 1 (1.6) | 25 (2.3) | 4 (0.6) |
| Hospital LOS [days, n, (%)] | ||||
| Mean (SD) | 3.7 (4.8) | 3.6 (3.6) | 5.5 (12.7) | 4.2 (7.0) |
| Median | 2 | 2 | 2 | 2 |
| Range | 0-37 | 0-18 | 0-102 | 0-103 |
| 0 | 1 (1.0) | 2 (3.2) | 6 (0.6) | 2 (0.3) |
| 1-5 | 85 (85.0) | 49 (77.8) | 802 (74.3) | 552 (83.1) |
| 6-10 | 7 (7.0) | 8 (12.7) | 142 (13.1) | 59 (8.9) |
| 11-15 | 4 (4.0) | 2 (3.2) | 55 (5.1) | 19 (2.9) |
| 16-20 | 2 (2.0) | 2 (3.2) | 29 (2.7) | 10 (1.5) |
| 21-25 | 0 (0) | 0 (0) | 17 (1.6) | 8 (1.2) |
| 26-30 | 0 (0) | 0 (0) | 8 (0.7) | 5 (0.8) |
| 31-35 | 0 (0) | 0 (0) | 7 (0.6) | 3 (0.5) |
| 36-40 | 1 (1.0) | 0 (0) | 5 (0.5) | 3 (0.5) |
| >40 | 0 (0) | 0 (0) | 9 (0.8) | 3 (0.5) |
| ICU admission (n, %) | ||||
| Yes | 25 (25.0) | 14 (22.2) | 174 (16.0) | 115 (17.2) |
| ICU LOS [days, n, (%)] | ||||
| Mean (SD) | 1.0 (2.7) | 0.6 (1.5) | 1.1 (4.0) | 0.8 (2.7) |
| Median | 0 | 0 | 0 | 0 |
| Range | 0-21 | 0-8 | 0-74 | 0-25 |
| 0 | 75 (75.0) | 49 (77.8) | 912 (84.0) | 553 (82.8) |
| 1-5 | 21 (21.0) | 13 (20.6) | 105 (9.7) | 88 (13.2) |
| 6-10 | 3 (3.0) | 1 (1.6) | 39 (3.6) | 17 (2.5) |
| >10 | 1 (1.0) | 0 (0) | 29 (2.7) | 10 (1.5) |
| Ventilator use (n, %) | ||||
| Yes | 8 (8.0) | 1 (1.6) | 58 (5.3) | 30 (4.5) |
| Days on ventilator (n, %) | ||||
| Mean (SD) | 0.4 (1.7) | 0.0 (0.3) | 0.4 (2.6) | 0.4 (2.5) |
| Median | 0 | 0 | 0 | 0 |
| Range | 0-12 | 0-2 | 0-40 | 0-33 |
| 0 | 92 (92.0) | 62 (98.4) | 1028 (94.7) | 638 (95.5) |
| 1-5 | 5 (5.0) | 1 (1.6) | 31 (2.9) | 16 (2.4) |
| 6-10 | 2 (2.0) | 0 (0) | 15 (1.4) | 5 (0.7) |
| >10 | 1 (1.0) | 0 (0) | 12 (1.1) | 9 (1.3) |
| Discharge destination (n, %) | ||||
| Home | 80 (80.0) | 55 (87.3) | 835 (76.9) | 528 (79.0) |
| Home with home health services | 3 (3.0) | 0 (0) | 17 (1.6) | 4 (0.6) |
| Acute rehabilitation unit | 4 (4.0) | 3 (4.8) | 67 (6.2) | 23 (3.4) |
| SNF/board and care facility | 2 (2.0) | 2 (3.2) | 57 (5.2) | 33 (4.9) |
| Long-term care facility | 0 (0) | 0 (0) | 1 (0.1) | 4 (0.6) |
| Recovery care facility | 0 (0) | 1 (1.6) | 1 (0.1) | 5 (0.7) |
| Acute hospital/transfer to OSH | 0 (0) | 0 (0) | 12 (1.1) | 4 (0.6) |
| Inpatient psychiatry | 0 (0) | 0 (0) | 0 (0) | 1 (0.1) |
| Detention center/jail | 0 (0) | 0 (0) | 5 (0.5) | 0 (0) |
| Left AMA | 6 (6.0) | 1 (1.6) | 52 (4.8) | 35 (5.2) |
| Expired | 4 (4.0) | 0 (0) | 16 (1.5) | 12 (1.8) |
| Other | 0 (0) | 0 (0) | 0 (0) | 4 (0.6) |
| Unknown | 1 (1.0) | 1 (1.6) | 22 (2.0) | 15 (2.2) |
AMA = against medical advice; FFP = fresh frozen plasma; ICU = intensive care unit; LOS = length of stay; OSH = outside hospital; SNF = skilled nursing facility
Discussion
The main aim of this study was to better characterize injury patterns, particularly involving orthopaedics, associated with e-bike accidents and compare injury severity and details with those of pedal bicycle, electric scooter, and motorcycle accidents. This study represents a large cohort of patients (total of 1917 patients) at a level 1 trauma center involved in electric bicycle accidents.
EB patients were markedly less likely to wear a helmet and more likely to lose consciousness than MC or PB patients. Approximately one in four patients (23.0%) reported wearing a helmet and approximately two-thirds reported LOC (63.0%) in the EB group. This is similar to previous studies that have shown traumatic brain injuries in 66-69% of patients.13,14 Other studies have shown TBIs in less than 40% of PB patients.15 EB patients were markedly more likely than MC and PB patients to experience TBI, ICH, or fractures of the head/face. When compared with MC and PB patients, EB patients were markedly more likely to receive CT scans of the head. Previous work has found an increased incidence of head injuries and facial fractures in e-bike and e-scooter accidents compared with standard bike and motorcycle accidents. This is likely due to lack of universal helmeting and falling on one's face because face/head injuries are more than double in e-bike accidents compared with standard bicycle accidents.3,4,16,17 In a study of ES riders in Australia, 46% of riders wore helmets and had reduced risk of head injury.18 Another study showed that compared with riders without helmets, helmeted bicycle riders were less likely to sustain serious head injuries, skull fractures, or facial fractures.19 These are striking findings because they can show the increased need for head protection and safety courses if desired for EB riders.
One study confirmed that cyclists rode an average of 3.6 km/h faster on an EB compared with PB in simple traffic situations.20 Riding at a faster speed and having a higher likelihood of not wearing a helmet as seen in our study can contribute to the higher rates of TBIs. While our study did not have data on the average speed of the EBs, one can argue for potential regulations on speed for EB users, given overall average faster speeds compared with PB riders.
Overall, the injury severity scores were comparable between all groups. There exists variability in the literature with several studies reporting similar findings of little to no difference in injury severity between groups in contrast to other studies showing higher injury severity for EB riders compared with PB riders.21-25 One study of electric scooter injuries found an increase in ISS with an increase in rider age.26
Of the orthopaedic injuries, spine fractures (11.0%) were the most prevalent in the study population, followed by fractures of the acetabulum (6.0%), clavicle (5.0%), scapula (5.0%), and radius (5.0%). This follows another study showing that 65% of EB riders presenting to ED sustained orthopaedic injuries with 63% of them involving the limb, pelvis, or spine.27 When compared with ES patients, EB patients were only markedly more likely to experience a pelvic injury. In another study, EB patients had comparable rates of pelvic injuries with that of motorcycle riders.13 Overall, 19.0% of EB patients sustained injuries requiring surgery. However, patients in the MC group were more likely to have required any surgical intervention overall. The MC group had greater rates of pelvic and femur injuries requiring surgical intervention compared with the EB group.
On presentation, 86.0% of EB patients were treated as critical trauma activations and 14% were treated as moderate trauma activations. This shows the severity of presentation the EB patients present with and the potential strain on the medical system for EB accidents. It has been studied that a median critical trauma activation in California EDs costs $24,057.28 For overall imaging obtained during admission, 100% of the EB patients received at least one CT scan and 98% received plain radiographs. Mean hospital LOS was not markedly different between any of the groups; however, EB patients were significantly more likely to be admitted to the ICU than MC patients (25.0% vs. 16.0%, P = 0.0256). On average, the daily cost of an ICU bed is three times higher than of a regular bed.29
Overall, the cohort of EB riders presenting to the ED aged an average of 49 years, with 34% of patients between 18 and 40 years. They were found to be markedly older than ES and MC cohorts. In a study from 2000 to 2017, EB injuries in the United States have been increasing markedly particularly among older persons. Our study must be seen in light that it did not include patients younger than 18 years. By contrast, one study found that most EB patients were younger than 30 years (56%) although patients older than 30 years were more likely to be hospitalized.30 Positive alcohol screening on presentation was more common in EB patients than any other group. Positive alcohol screening was recorded in 40.0% of patients, and drug testing was positive for 42.0% of patients. As many as one-third of riders in both New Zealand and Australia who presented to the ED/hospital with e-bike/e-scooter–related accidents were found to be intoxicated.16
This study has several limitations because it is a retrospective study. There was variability in the chart on e-scooter description in the chart such as Vespa, Moped, Bird, and Lime Scooters. The lack of clear and consistent verbiage in describing e-scooters is likely a hindrance to researching how these modalities compare with EB/MC/PB. In addition, dirt bikes were common and were placed into motorcycles because of unclear verbiage and similarity in maximum velocity/protective gear worn. The information on the mechanism of trauma such as self-inflicted or collision with other vehicles or pedestrians was absent in the data. This study only includes EB/PB/ES/MC riders without including pedestrians or other road users who may have been injured in these related incidents. Therefore, this study may underestimate the true burden of injury from modes of transportation such as EBs.
Overall, electric bicycles are a growing means of transport within the United States. These results from a level 1 trauma center indicate that electric bicycles can cause severe injuries. They can result in higher rates of critical trauma activations and ICU stays. In particular, they have a higher rate of notable head injuries and lower rate of helmet use. They also sustain notable orthopaedic injuries. As electric bicycle users continue to rise, increased legislation and tighter regulation should be considered to decrease the burden and severity of injury associated with this means of transport. Orthopaedic professional societies may play a notable role in advocating for possible law changes and have a responsibility to educate patients on safety of this new mode of transportation.
Footnotes
None of the following authors or any immediate family member has received anything of value from or has stock or stock options held in a commercial company or institution related directly or indirectly to the subject of this article: Dr. Anderson, Dr. McLellan, Ms. Tedesco, Dr. Callan, Dr. Grabar, Dr. Joe, Dr. Nahmias, Dr. Learned.
Contributor Information
Maddison McLellan, Email: maddisonmclellan@stanford.edu.
Amanda Tedesco, Email: tedescoa@hs.uci.edu.
Kylie Callan, Email: ktcallan@hs.uci.edu.
Christina Grabar, Email: grabarc@uw.edu.
Victor Joe, Email: vcjoe@hs.uci.edu.
Jeffry Nahmias, Email: jnahmias@hs.uci.edu.
James Learned, Email: jlearned@hs.uci.edu.
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