Characterization of electric scooter injuries over 27 months at an urban level 1 trauma center

Understanding e-scooter rider crash severity using a built environment typology: A two-stage clustering and random parameter model analysis

E-scooters are an emerging transport mode that is transforming urban mobility; however, their proliferation has raised concerns about safety. This study combines UK e-scooter crash data with built environment characteristics from the crash locations. A two-stage framework was followed: first, a typology of built environments was developed using K-means++; second, crash severity within each cluster was analysed using a random parameter binary logit model. Four built environment clusters were identified: (1) car-centric and mixed-use zones, (2) commercial and industrial zones, (3) intersection-dense areas, and (4) residential and central areas. Collisions with motor vehicles, younger e-scooter riders, and higher speed limits were the most common risk factors across the clusters, with the first two clusters showing a higher impact of these factors on the likelihood of severe crashes. In the first and second clusters, riding on the carriageway significantly increased injury severity. In the second cluster, three collision types were significant, more than in other clusters where only side-impact collisions were significant. This indicates high e-scooter-motor vehicle friction in the second cluster. Among all collision types, head-on collisions increased the likelihood of severe outcomes more than others. In the third and fourth clusters, peak hours were associated with a lower likelihood of severe crashes, while this variable showed the opposite impact in the first cluster. The results highlight that consideration of the surrounding built environment is paramount when analysing e-scooter crash severity, as unique contributing factors were identified specific to each built environment type, along with varying magnitudes or directions of marginal effects.

Comparative analysis of accident mechanisms and injury patterns of e-moped and e-scooter operators

OBJECTIVE

To compare accident-related injuries and degree of risk for operators/riders of e-mopeds and e-scooters.

METHODS

A retrospective medical charts review in a tertiary medical center was performed. All individuals aged 13 years and older who were referred to a single tertiary referral center after 2 wheels vehicle injury were enrolled. Demographics, injury type, imaging, surgeries, hospital and intensive care unit lengths of stay, mortality, helmet use and hour and day of injury were recorded and analyzed.

RESULTS

A total of 2429 patients were enrolled (1095 e-moped and 1334 e-scooter operators/riders). The mean (±standard deviation) age for operators/riders was 31.5 (±11.7) years. There was a male preponderance in both groups (70.8 % and 60.3 % in the e-moped and e-scooter operators/riders, respectively). Helmet use was poor, with an overall usage rate of 39.7 % among all riders. E-moped operators/riders were more commonly hospitalized in the intensive care unit (1.5 %) than e-scooter operator/riders (0.6 %), p = 0.039. E-moped operators/riders had significantly fewer injuries (35.7 %) compared to e-scooter operators/riders (42.4 %), p < 0.001. E-Scooters were associated with significantly more face and upper extremity injuries compared to e-moped (9.0 % and 23.9 % compared to 5.8 % and 19.4 %, respectively, p = 0.003 and 0.008, respectively). Chest and abdomen injuries were more common in the e-moped operators/riders compared to the e-scooters operators/riders (4.4 % and 1.1 % compared to 2.1 % and 0.3 %, respectively, p = 0.002 and 0.021, respectively).

CONCLUSION

The data in this analysis indicated that e-Scooters are involved in a higher number of accidental injuries that tend to be less severe and result in fewer fatalities than those sustained by e-moped use. In contrast, e-mopeds were linked to more complex injuries, as reflected by higher hospitalization rates, ICU admissions and multi-level injuries among e-moped operators/riders. This finding also corresponded to a higher demand for imaging studies in the emergency department (ED). Additionally, our analysis of a relatively smaller cohort of helmeted versus non-helmeted patients reinforces the critical role of helmets in mitigating head and face injuries.

Injury epidemiology related to personal mobility devices in the pediatric population

BACKGROUND

The use of personal mobility devices (PMDs) in daily life has significantly increased in France over the past two decades. These devices, popular both as a mode of transportation-especially among adolescents-and as a source of leisure or physical activity, are not without risk. The hypothesis of our study was to assess the dangers associated with PMDs in the pediatric population.

OBJECTIVES

The aim of this study was to describe the epidemiology of non-fatal injuries related to the use of both motorized and non-motorized PMDs in children treated in the emergency department of our university hospital in 2019, and to identify factors associated with an increased risk of hospitalization.

PATIENTS AND METHODS

All children presenting to the pediatric emergency department in 2019 for an injury related to a PMD accident (including electric scooters, manual scooters, bicycles, skateboards, hoverboards, and rollerblades) were included in this study. Data collected included age, sex, type of PMD used, location of the accident (roadway or sidewalk), and helmet use. The type of injury (laceration, sprain, fracture) and management (outpatient care, hospitalization, surgery) were also analyzed.

RESULTS

Out of 52,993 emergency consultations at our pediatric center in 2019, 10,417 were trauma-related, and 625 children met the inclusion criteria, with a mean age of 8.47 years. Manual or electric scooters accounted for 50.4% of the accidents. Among the children included, 22.08% sustained fractures, with 7.69% requiring surgical intervention. Helmet use was absent in 87.52% of cases. The most common injuries affected the upper limbs (34.56%) and the face (26.88%). Although the absence of helmet use was not statistically associated with greater injury severity in our study (p = 0.604), it is important to note that our center does not manage severe head trauma. Injury severity was significantly correlated with age (p = 1.724e-06) and was higher in cases involving electric PMDs (p = 1.722e-06).

CONCLUSION

Despite various prevention campaigns, PMD use remains a major source of injury in children and is one of the leading reasons for emergency visits. Helmet and protective gear use should be strongly encouraged. Injuries are more severe among adolescents using electric PMDs.

LEVEL OF EVIDENCE

IV; descriptive epidemiological study. Non-interventional research.

Changes in e-scooter related maxillofacial injuries following legislative measures in Helsinki, Finland

The increasing use of e-scooters globally has resulted in a rise in traffic-related injuries, particularly maxillofacial trauma. This study assesses the potential impact of legislative measures, specifically speed limits and night-time usage restrictions, on reducing maxillofacial injuries from e-scooter accidents. A retrospective cohort study was conducted using data from patients treated for e-scooter-related injuries at Helsinki University Hospital between January 2021 and December 2023. The study included 1275 patients, aged ≥ 16 years, treated in three trauma hospitals. Patients not riding e-scooters at the time of injury were excluded. Injury patterns and the influence of legislative measures were analyzed. Among the 1275 patients, 169 (13.3%) sustained maxillofacial injuries. Legislative restrictions were associated with a significant reduction in maxillofacial injuries, with up to an 88% decrease in some months. Predictors of maxillofacial injuries included older age (OR 1.06, 95% CI 1.04-1.08), alcohol intoxication (OR 3.2, 95% CI 1.5-5.8), and concurrent head and neck injuries (OR 12.1, 95% CI 5.8-25.2). Legislative restrictions on e-scooter use, including speed limits and nighttime riding bans, were associated with a significant reduction in maxillofacial injuries. These findings highlight the importance of targeted policies to mitigate injury risks associated with e-scooter use.

Paediatric e-scooter riders at high risk of life-threatening traffic accidents

BACKGROUND

This study presents the epidemiology and the development of e-scooter and non-electric scooter injuries in children and adolescents to highlight the nature and the severity of such injuries.

METHODS

All children and adolescents with electric or non-electric scooter related injuries between January 2019 until December 2022 were included in this single-centre study and retrospectively evaluated. An epidemiological overview including age, sex, type of scooter, injury mechanism, diagnosed injuries and surgical interventions were presented. Further, statistical comparisons of the means and proportions of injuries and the number of surgical interventions between electric and non-electric scooter riders were made.

RESULTS

The study consists of 633 children and adolescents (9.1 ± 5.0 years; 231 female, 36.5%, 402 male, 63.5%). 80.1% (8.0 ± 4.1 years) used non-electric scooters, while 19.9% (14.2 ± 4.1 years) used e-scooters. In comparison, adolescent e-scooter riders were significantly more likely to be involved in traffic accidents (non-electric scooter: 16/507; e-scooter: 21/126; p = 0.0001) and suffered severe head injuries more often (non-electric scooter: 8/134; e-scooter: 7/37; p = 0.0217) than patients riding non-electric scooters.

CONCLUSION

Adolescent e-scooter riders were more likely to be involved in potentially life-threatening traffic accidents having a higher risk of severe head injuries requiring surgery compared to non-electric scooter riders.

IMPACT

Adolescent e-scooter riders have a higher risk to be involved in potentially life-threatening traffic accidents than riders of non-electric scooters. E-scooter riders have a higher risk of sustaining serious head injuries requiring surgical intervention than non-electric scooter riders. The data highly recommends the implementation of prevention strategies especially educating youth and parents and wearing protective clothing. Legislation and law enforcement could help prevent such injuries and potentially life-threatening traffic accidents involving children and adolescents who ride e-scooters.

E-scooter-related imaging: a new emerging high-energy trauma patient

OBJECTIVES

To quantify the volume and nature of radiological imaging performed for e-scooter related trauma presentations in a tertiary referral centre and to identify common radiological pattern of injuries.

METHODS

Our study received institutional review board approval. We retrospectively reviewed all anonymised radiological imaging studies performed in our institution for the term 'scooter' or 'e-scooter' between July 2020 and July 2021. The patient demographics, number of imaging studies performed and modality type as well as the nature of injuries identified were recorded.

RESULTS

Within the study period, 147 patients with e-scooter-related injuries were referred for radiological imaging. Forty-two (29%) of those patients had positive radiological findings. The vast majority of injuries on radiographs were upper limb injuries typical of a fall on outstretched hand (FOOSH) pattern. Thirty-two patients (22%) required advanced diagnostics with CT or MRI with 11 of these patients having positive findings. Four patients suffered significant head injuries including skull fractures and/or intracranial haemorrhage. Five patients suffered facial bone fractures, and 2 suffered spinal fractures. One patient suffered a handlebar abdominal trauma with a resulting large bowel injury ultimately requiring bowel resection.

CONCLUSION

E-scooter-related injuries represent a new and emerging high-energy trauma patient. These patients demonstrate injury patterns similar to other high-energy trauma such as road traffic accidents. Although the most common injuries are musculoskeletal upper limb injuries typical of FOOSH, a large proportion of these require advanced diagnostic imaging (CT, MRI) which were commonly positive for significant injuries.

Helmet wearing and related factors among electric personal mobility device users in Korea

Using data from the 2022 Korea Community Health Survey (n = 13 320), this study investigated helmet use and related factors among Korean adults using personal mobility devices, without distinguishing between private and hired users. Among mobility device users, 32.1% responded that they always wore a helmet. The proportion of helmet use was 35.2% among men, 25.8% among women, 29.2% among those aged 19-44 years, 42.3% among those aged 45-64 years and 26.6% among those aged 65 years or older. Furthermore, those who drank less frequently and were physically active were more likely to wear helmets. Moreover, people who always wore a seat belt when driving a car or sitting in the rear seat and people who always wore a helmet when riding a motorcycle were more likely to wear a helmet while using electric personal mobility devices. Approximately one-third of users always wore a helmet. The helmet-wearing rate was related to general characteristics such as gender and education level, and to safety behaviors such as wearing a seat belt when driving a car, sitting in the rear seat of a car, or when riding a motorcycle. In addition to considering personal characteristics investigated in this study, the helmet-wearing rate should be improved through policies or systems at the national or regional levels.

Injury Patterns of Electric-Scooter Related Trauma: A Systematic Review With Proportion Meta-Analysis

Electric scooter (ES)-related injuries are increasing but poorly described. Clinicians need more information to be prepared for these patients. We supposed two prevalent patterns of patients: mildly injured (predominant upper-limb injuries) and severely injured (predominant head trauma). This study aims to understand the frequency of ES-related injuries and patients' characteristics despite the heterogeneity of data currently available. A systematic review with a proportion meta-analysis was conducted on studies with a multidisciplinary description of ES-related injuries in adult patients (PROSPERO-ID: CRD42022341241). Articles from inception to April 2023 were identified in MEDLINE, Embase, and Cochrane's databases. The risk of bias was evaluated using ROBINS-I. Twenty-five observational studies with 5387 patients were included in the meta-analysis, depending on reported data. Upper-limb (31.8%) and head (19.5%) injuries are the most frequent (25/25 studies included). When injured while riding, 19.5% of patients are intoxicated with drugs/alcohol, and only 3.9% use a helmet, increasing the possibility of severe injuries. About 80% of patients are victims of spontaneous falls. Half of the patients self-present to the ED, and 69.4% of cases are discharged directly from the ED. Studies' limitations include an overall moderate risk of bias and high heterogeneity. Electric scooter-related accidents are commonly associated with upper-limb injuries but often involve the head. Spontaneous falls are the most common mechanism of injury, probably related to frequent substance abuse and helmet misuse. This hot topic is not adequately investigated due to a lack of data. A prospective registry could fill this gap.

Characteristics and Injury Patterns in Traumatic Brain Injury Related to E-Scooter Use in Riga, Latvia: Multicenter Case Series

Background and Objectives: In recent years, electronic scooters (e-scooters) have gained popularity, whether for private use or as a publicly available transportation method. With the introduction of these vehicles, reports of e-scooter-related accidents have surged, sparking public debate and concern. The aim of this study was to analyze the epidemiological data, characteristics, and severity of traumatic brain injury (TBI) related to e-scooter accidents. Materials and Methods: This retrospective case series evaluated patients who were admitted to the three largest neurosurgery clinics in Riga, Latvia, from the time period of April to October in two separate years-2022 and 2023-after e-scooter-related accidents. The data were collected on patient demographics, the time of the accident, alcohol consumption, helmet use, the type of TBI, other related injuries, and the treatment and assessment at discharge. Results: A total of 28 patients were admitted with TBI related to e-scooter use, with a median age of 30 years (Q1-Q3, 20.25-37.25), four individuals under the age of 18, and the majority (64%) being male. In 23 cases, the injury mechanism was falling, in 5 cases, collision. None were wearing a helmet at the time of the injury. Alcohol intoxication was evident in over half of the patients (51.5%), with severe intoxication (>1.2 g/L) in 75% of cases among them. Neurological symptoms upon admission were noted in 50% of cases. All patients had intracranial trauma: 50% had brain contusions, 43% traumatic subdural hematoma, and almost 30% epidural hematoma. Craniofacial fractures were evident in 71% of cases, and there were fractures in other parts of body in three patients. Six patients required emergency neurosurgical intervention. Neurological complications were noted in two patients; one patient died. Conclusions: e-scooter-related accidents result in a significant number of brain and other associated injuries, with notable frequency linked to alcohol influence and a lack of helmet use. Prevention campaigns to raise the awareness of potential risks and the implementation of more strict regulations should be conducted.

National Trends and Clinical Outcomes after Scooter Injury in the US: 2016 to 2020

BACKGROUND

In recent years, the adoption of electric scooters has been accompanied by a surge of scooter-related injuries in the US, raising concerns for their severity and associated healthcare costs. This study aimed to assess temporal trends and outcomes of scooter-related hospital admissions compared with bicycle-related hospitalizations.

STUDY DESIGN

This was a retrospective cohort study using the 2016 to 2020 National Inpatient Sample for patients younger than 65 years who were hospitalized after bicycle- and scooter-related injuries. The Trauma Mortality Prediction Model was used to quantify injury severity. The primary outcomes of interest were temporal trends of micromobility injuries. In-hospital mortality, rates of long bone fracture, traumatic brain injury, paralysis, length of stay, hospitalization costs, and nonhome discharge were secondarily assessed.

RESULTS

Among 92,815 patients included in the study, 6,125 (6.6%) had scooter-related injuries. Compared with patients with bicycle-related injuries, patients with scooter-related injuries were more commonly younger than 18 years (26.7% vs 16.4%, p < 0.001) and frequently underwent major operations (55.8% vs 48.1%, p < 0.001). After risk adjustment, scooter-related injuries were associated with greater risks of long bone fracture (adjusted odds ratio 1.40, 95% CI 1.15 to 1.70) and paralysis (adjusted odds ratio 2.06, 95% CI 1.16 to 3.69) compared with bicycle-related injuries. Additionally, patients with bicycle- or scooter-related injuries had comparable index hospitalization durations of stay and costs.

CONCLUSIONS

The prevalence and severity of scooter-related injuries have significantly increased in the US, thereby attributing to a substantial cost burden on the healthcare system. Multidisciplinary efforts to inform safety policies and enact targeted interventions are warranted to reduce scooter-related injuries.

Injury severity analysis of single-vehicle and two-vehicle crashes with electric scooters: A random parameters approach with heterogeneity in means and variances

In recent years, the electric scooter has become one of the most popular means of transportation on short trips. Due to the lag in the formulation of transportation policies and regulations, coupled with the increasing number of electric scooter crashes, there has been growing concern about the safety of pedestrians and electric scooter riders. For the first time in the extant literature, this study aims to analyze injury severity of electric scooter crashes by unobserved heterogeneity modeling approaches. A random parameters approach with heterogeneity in means and variances is utilized to examine the factors influencing injury severity, using data collected from the STATS19 road safety database. Electric scooter crashes are classified as single-vehicle crashes and two-vehicle crashes, with injury severity categorized into two groups: fatalities or serious injuries, and slight injuries. The model estimation was conducted by considering several variables including roadway, environment, temporality, vehicle, and rider characteristics, as well as second-party vehicle and driver characteristics and manners of collision specific to two-vehicle crashes. The results of the model estimation reveal that certain factors had relatively stable effects with the varying degree of crash injury severity outcomes in both single-vehicle crashes and two-vehicle crashes. These factors include nighttime incidents, weekdays, male riders, and an increase in rider age, all of which are associated with more severe injury outcomes. Moreover, the random parameters logit model with heterogeneity in means and variances is more flexible in accounting for unobserved heterogeneity and exhibits better goodness of fit. This study improves the understanding of electric scooter safety, and the finding can better inform public policy regarding electric scooter use to improve road safety and reduce injury severity of electric scooter crashes.

Unveiling the Surge: A Comprehensive Analysis of E-Scooter-Related Injuries at an Urban Level 1 Trauma Center in Vilnius, Lithuania (2018-2021)

Background The surge in electric scooter (e-scooter) adoption in 2019 fueled by sharing platforms has raised safety concerns, leading to an increased incidence of e-scooter-related injuries. Despite regulatory efforts, there has been a notable rise in accidents, prompting a comprehensive investigation. This study conducted at the Republican Vilnius University Hospital (RVUH), a level 1 trauma center, is one of the first in the Baltic States aiming to analyze the causes, severity, and frequency of e-scooter injuries from 2018 to 2021. This research addresses a critical gap in understanding e-scooter safety in the Baltic States, providing valuable insights for informed policy and preventive measures. Methodology This retrospective study analyzed e-scooter-related injuries in Vilnius, Lithuania, from April to September during 2018-2021. Data from the RVUH emergency department were examined. Using keywords such as "scooter" and "electric," relevant cases were extracted from the RVUH electronic health system. Included were individuals, both riders and pedestrians, with clear e-scooter involvement, excluding duplicates, those under 18, and users of other types of scooters. Extracted medical records provided data on demographics, injury specifics, helmet use, alcohol consumption, and more. Trauma severity was assessed through the New Injury Severity Score (NISS) and Abbreviated Injury Scale (AIS). Statistical analysis utilized GraphPad Prism software and Excel, adhering to ethical guidelines with RVUH Bioethics Committee approval. Results Over four years, 1,036 e-scooter-related injuries at RVUH revealed a gender-based shift, with males sustaining more injuries. The introduction of rentals in 2019 triggered a 334% surge in injuries compared to 2018. Despite an annual 208% increase from 2018 to 2021, 2021 saw a 710.93% rise. Trauma severity remained consistent, with AIS scores 1 and 2 being prevalent. Non-helmet wearers constituted 97.97%, and soft tissue damage was predominant. Ownership patterns shifted toward rentals (81.15%), reflecting the popularity of sharing platforms. Alcohol influence showed no significant change, but intoxicated patients had a higher surgery rate during four years. Mechanism analysis highlighted tripping as the primary cause. Injury characteristics revealed fractures in 34.56% of cases, primarily affecting upper limbs (53.35%). Soft tissue trauma was prominent (65.44%), with lower limbs being significantly impacted. Conclusions The surge in e-scooter injuries demands urgent preventive action. While most injuries are mild, a significant proportion is moderate to severe, even fatal. Inadequate education, lax enforcement, and uneven infrastructure contribute to the risk. Urgent measures, including road maintenance, speed reduction, and mandatory helmet use, are crucial. Clarity in government directives for designated e-scooter areas is vital. Further research is needed to understand the broader impact of informed policymaking and safer urban mobility. Expanding research to other Lithuanian regions would enhance the current study.

Analysis of dental traumatic patterns in standing electric scooter-related accidents

BACKGROUND

There have been several studies about the increasing accident risks and injuries of standing electric scooters, but there is no study about the dental traumatic injuries related with standing electric scooter so far.

OBJECTIVES

The purpose of this study is to report the overall dental traumatic patterns, and compare the patterns of standing electric scooter-related dental trauma with other traumatic causes. Also, considerations about minimizing the risks of electric scooter-related trauma will be discussed.

METHODS

Data on patients who visited Region Trauma Center of Wonju Severance Christian Hospital with dental emergency from January 2020 to December 2022 were collected.

RESULTS

The crown-root fracture and avulsion occurred significantly higher in electric scooter-related accidents than others. Furthermore, relatively minor dental injuries including concussion and subluxation showed higher percentage to be occurred as combined injuries in electric scooter-related accidents. The prevalence of traumatized posterior teeth was significantly higher in electric scooter-related trauma than others. Most of patients were teenagers and twenties. Also, the electric scooter-related accidents mostly occurred at evening and night. Furthermore, the number of patients wearing a helmet in electric scooter accidents was 1 out of 33.

CONCLUSION

The standing electric scooter-related dental trauma resulted in an increased prevalence of relatively severe dental trauma. Supplementation and reinforcement of the related policies as well as strict enforcement of the laws on electric scooter users will be needed to prevent severe dental and craniofacial trauma.

Lessons learned? Increasing injury severity of electric-scooter accidents over a period of one year: a monocentric follow-up study at a level 1 trauma center

PURPOSE

After major COVID-19 lockdown measures were suspended in 2021, E-scooter mobility regrew rapidly. In the meantime, multiple studies were published on the potential risks for e-scooter drivers and the necessity for wearing protective equipment. But did the drivers learn their lessons?

METHODS

We observed data of E-scooter-related accidents admitted to the emergency department of a level 1 German trauma center in the year 2021 and compared the data with our previous report (July 2019-July 2020).

RESULTS

N = 97 E-scooter-related accidents were included, marking a 50% increase when compared to the previous observation. Most patients were young adults (28.18 ± 1.13 years) with a notable shift towards a male population (25 vs. 63, p = 0.007). While the injury pattern remained unchanged, injury severity, reflected by a significant increase in shock room treatments (p = 0.005), hospital admissions (p = 0.45), and ICU admissions (p = 0.028), increased. Lastly, we report a higher injury severity of patients driving under the influence of alcohol, expressed by significant differences in hospital admissions, shock room treatments, ICU admissions, intracerebral bleeding (p < 0.0001), and injuries requiring surgery (p = 0.0017).

CONCLUSION

The increase in injury severity and especially the substantial number of accidents due to driving under the influence of alcohol, are alarming for both trauma- and neurosurgeons. As the controversy surrounding the general use of E-scooters will continue, we urge representatives to intensify their efforts regarding prevention campaigns focusing on the potential dangers of E-scooters, especially when driving under the influence of alcohol.

Electric scooter-related accidents: a possible protective effect of helmet use on the head injury severity

Despite electric scooter use has proliferated in Italy since 2019, actionable data regarding injury incidence and patterns associated with electric scooter accidents are limited. This study aims at analyzing the rate, clinical, and demographic features of electric scooter accidents accessed to the Emergency Department (ED) of Fondazione Policlinico Universitario A. Gemelli IRCSS (Rome, Italy). This retrospective study included all patients older than 18 years riding an electric scooter in the ED from June 2019 to April 2022. Personal data, injury circumstances, helmet use, and health data were collected. Abbreviated Injury Scale (AIS) codes of all diagnoses were recorded, and the Injury Severity Score (ISS) was calculated for each patient. The analysis includes 92 patients admitted to the ED due to an e-scooter accident during the study period, with an increase in years. Thirty-two patients presented bone fractures especially concerning the extremities and the face districts. The median Injury Severity Score in the study cohort was 3, with the highest AIS represented by AIS Pelvic-Extremity and AIS External. Moreover, statistical significance was found between AIS Head-Neck and severity of trauma. E-scooters have become a familiar sight in cities worldwide recently, with many new companies renting them for use. But their arrival has also brought new safety concerns. Although most injuries reported are minor, the meager rate of helmet use is critical. Implementing compulsory helmet use for electric scooters for all ages could be a protective factor for being patient with head trauma on urban streets.

Western Australian State Trauma Registry analysis of incidence and injury patterns associated with e-Scooter injuries: 5-year retrospective case series

BACKGROUND

Electric scooters (e-Scooters) are a form of motorized vehicle that offers cheap, efficient and environmentally friendly transportation. Increased e-Scooter utilization has been accompanied by increases in e-Scooter related injuries in multiple countries. This project describes the incidence, injury pattern, injury severity and patient factors associated with e-Scooter use from the Western Australian State Trauma Registry.

METHODS

Retrospective cohort of all trauma patients captured by the Western Australian State Trauma Registry between 01 July 2017 and 30 June 2022 were analysed. Patient demographics, helmet use, reported drug use, and injury details (including principal and additional diagnoses, ISS) were collected.

RESULTS

Eighty-one patients sustained e-Scooter related injuries between 2017 and 2022. Fifty-four (66%) of hospital admissions were recorded in 2021-2022, an annual percent change of 385.7% from the previous year. Most patients were male (80%). Median age was 40 years (IQR: 32-50). Helmet use was reported in 43% of patients. Helmet use was associated with a significantly lower odds of head injury (OR = 4.42, CI: 1.38-14.21; P = 0.01). Thirty-five percent of patients were intoxicated with either alcohol or drugs. Forty-four (54%) patients required surgery.

CONCLUSION

E-Scooter crashes are a new mechanism of injury affecting patients captured by the Western Australian State Trauma Registry. Helmet use correlated with a reduced risk of head injury.

Electric scooter accidents leading to emergency department visits: influence of alcohol and outcomes in Stockholm, Sweden

Electric scooters are a popular form of transportation, but accidents have increased with increased usage over the last years with rising health care costs as a consequence. This study aims to quantify accidents associated with the use of alcohol and to compare injuries at the emergency department (ED) among patients who have been involved in an accident involving an electric scooter. We used data from a multi-center retrospective registry-based cohort in the Swedish Traffic Accident Data Acquisition. We included all patients that had been involved in an electric scooter accident needing a visit to all EDs in Stockholm, Sweden during 2019-2020. Data on alcohol intake was manually drawn from medical files. Out of all of the 369 patients, the majority were men (n = 223, 60%) and aged below 30 years (n = 181, 49%). In all, 102 (28%) of the patients had a positive history of alcohol intake prior to the accident. Patients with alcohol intake more often arrived nighttime than those without alcohol, via ambulance (40% and 24%, respectively, p-value < 0.01). Those with alcohol intake needed to be admitted to hospital from the ED instead of being discharged more often than those withour alcohol (17% and 9%, respectively, p-value < 0.05) even if the majority still had minor injuries. Every 33,000 trips on electric scooters are statistically accompanied by an accident leading to an ED visit. We conclude that accidents with electric scooters are often associated with alcohol intake. They often demand more resources, such as an ambulance transfer and admission to hospital, and involve multiple injuries, compared to those without alcohol intake.

Ocular injuries associated with two-wheeled electric transportation devices and motorcycle accidents

Electric bicycles and scooters have gained popularity among riders; studies assessing these device-related injuries have not specified ocular trauma. Our study examined the types and risk factors for ocular and periocular injuries associated with electric devices compared to motorcycle accidents. The study was conducted on the National Trauma Registry database from 20 trauma centers, including patients involved in accidents with electric bicycles, scooters, and motorcycles between 2014 to 2019. Injured riders were assigned into two groups: motorcycle group (M) and electric bicycle & scooter group (E). Data such as gender, age, protective gear use, ocular injury type, injury severity score (ISS), and ocular surgery were captured. Logistic regression models were conducted for injury types and the need for surgery. 8181 M-riders and 3817 E-riders were involved in an accident and hospitalized. E-riders suffered from ocular injury more than M-riders. Males were most vulnerable and the ages of 15-29. Orbital floor fracture was the most common injury, followed by ocular contusion, eyelid laceration, and other ocular wounds. Electric bicycle and scooter riders are more likely to suffer from ocular injury than motorcycle riders. Riders without helmets are at greater risk for injuries, specifically orbital floor fractures. ISS of 16 + was associated with injury demanding ocular surgery.

Characteristics and costs of electric scooter injuries in Helsinki: a retrospective cohort study

Background and purpose

The incidence of electric scooter (e-scooter) injuries has increased drastically in numerous countries after widespread availability of shared e-scooters. The economic impact on society from a broader perspective has not been studied. We aimed to estimate the incidence of e-scooter injuries, describe the injury patterns, and estimate the costs of e-scooter injuries.

Patients and methods:

We performed a retrospective cohort study including all e-scooter-related injuries presented in the three adult emergency departments in Helsinki in 2021. We collected the patient data from the university hospital information system. Injury severity was evaluated based on the Abbreviated Injury Score. The cost of the hospital treatment was analyzed based on our hospital district’s service price listing. In addition, we recorded the total amount of sick leave days and estimated their economic impact.

Results

In total, 446 e-scooter injuries were identified and taken into the analysis (434 affecting riders and 12 non-riders). The median age of the patients was 26 (IQR 22–33), and 59% were male. 257 (58%) of the of the injuries were minor, whereas 155 (35%) were moderate, 30 (7%) serious, 3 (0.7%) severe, and one (0.2%) critical. Furthermore, 220 (49%) of the patients sustained head injuries. A major spike in accident incidence was seen during the weekend (Friday to Sunday) nights, accompanied by a proportional increase in patients with alcohol intoxication. Including both the costs of the hospital care and absence from work, the approximated total cost of e-scooter injuries was 1.7 million euros, with a median cost of a single accident being 1148 euros (IQR 399–4263 €).

Interpretation:

Considerable number of the injuries are moderate, severe, or worse. Comprehensive preventive measures must be conducted to decrease the incidence of e-scooter injuries. The use of helmets should be strongly encouraged to prevent severe head injuries. The nighttime bans during weekends and speed limits on e-scooters appear to be justifiable.

Characteristics and Risk Factors for Electric Scooter-Related Crashes and Injury Crashes among Scooter Riders: A Two-Phase Survey Study

Electric scooters (or e-scooters) are among the most popular micromobility options that have experienced an enormous expansion in urban transportation systems across the world in recent years. Along with the increased usage of e-scooters, the increasing number of e-scooter-related injuries has also become an emerging global public health concern. However, little is known regarding the risk factors for e-scooter-related crashes and injury crashes. This study consisted of a two-phase survey questionnaire administered to a cohort of e-scooter riders (n = 210), which obtained exposure information on riders' demographics, riding behaviors (including infrastructure selection), helmet use, and other crash-related factors. The risk ratios of riders' self-reported involvement in an e-scooter-related crash (i.e., any crash versus no crash) and injury crash (i.e., injury crash versus non-injury crash) were estimated across exposure subcategories using the Negative Binomial regression approach. Males and frequent users of e-scooters were associated with an increased risk of e-scooter-related crashes of any type. For the e-scooter-related injury crashes, more frequently riding on bike lanes (i.e., greater than 25% of the time), either protected or unprotected, was identified as a protective factor. E-scooter-related injury crashes were more likely to occur among females, who reported riding on sidewalks and non-paved surfaces more frequently. The study may help inform public policy regarding e-scooter legislation and prioritize efforts to establish suitable road infrastructure for improved e-scooter riding safety.

Characteristics of Electric Scooter and Bicycle Injuries After Introduction of Electric Scooter Rentals in Oslo, Norway

Importance

When society introduces and accepts new transportation modes, it is important to map risks and benefits.

Objective

To compare electric scooter (e-scooter) and bicycle injuries.

Design, Setting, and Participants

This cohort study is based on prospectively collected data on Norwegian patients who sustained e-scooter or bicycle injuries and presented to an emergency department affiliated with Oslo University Hospital between January 1, 2019, and March 31, 2020.

Main Outcomes and Measures

e-Scooter and bicycle injuries were evaluated for associations with sex, age, time of injury, helmet use, intoxication, body region, and injury severity. Descriptive statistics are presented as mean (SD) or number with percentage, with significance set at P < .05 (2-tailed).

Results

During the study period, 3191 patients were included (850 e-scooter riders, 2341 bicyclists) with 3839 injuries recorded (997 e-scooter, 2842 bicycle). The mean (SD) age of those injured was 34 (17) years, 2026 riders (63.5%) were male, 1474 (46.2%) were helmeted at the time of injury, and 516 (16.2%) were intoxicated by alcohol or other drugs. The annual incidence of injuries was 120 per 100 000 inhabitants for e-scooters and 340 per 100 000 inhabitants for bicycles. Men were overrepresented in both groups (529 e-scooter riders [62.2%] and 1497 bicyclists [63.9%]). e-Scooter riders were younger than bicyclists (mean [SD] age, 31 [12] vs 35 [18] years). Most injured e-scooter riders were aged 20 to 40 years, whereas injured bicyclists had a broader age distribution. e-Scooter injuries commonly occurred on weekends (378 [46.6%]) and during evening (230 [32.3%]) or nighttime (242 [34.1%]) hours. Most bicycle injuries occurred during weekdays (1586 [69.7%]) and daytime (1762 [61.3%]). e-Scooter riders were more often intoxicated (336 [39.5%] vs 180 [7.7%]) and had a lower rate of helmet use (18 [2.1%] vs 1456 [62.2%]). During nighttime, 230 injured e-scooter riders (91.3%) and 86 bicyclists (69.4%) were intoxicated. e-Scooter riders had more head and neck (317 [31.7%] vs 636 [22.4%]) and lower-limb (285 [28.6%] vs 632 [22.2%]) injuries and fewer upper-limb (341 [34.2%] vs 1276 [44.9%]), thoracic (41 [4.1%] vs 195 [6.9%]), and abdominal, pelvic, and lumbar (13 [1.3%] vs 103 [3.6%]) injuries.

Conclusions and Relevance

In this cohort study, e-scooter riders were younger than bicyclists, did not use helmets, were more often intoxicated, and were more often injured during nighttime. The rate of intoxication among e-scooter riders injured at night was high. Preventive measures, including awareness campaigns, regulating e-scooter availability, improving infrastructure, and implementing stricter helmet and alcohol policies, may prove effective for reducing injuries.

Electric Scooter-Related Trauma in Korea

BACKGROUND

The number of users of electric scooters, which provide swift and convenient mobility options, has increased sharply over recent years as their distribution as a shared service has expanded. Although the number of accidents and related damage has increased accordingly, limited research has analyzed data on the new types of accidents arising from electric scooters. This study aimed to analyze data on trauma characteristics due to accidents that occurred during electric scooter use.

METHODS

A retrospective chart review was conducted for patients who visited the regional trauma center of our institute due to electric scooter accidents from April 2018 to October 2021. Information was extracted on helmet-wearing status, sex, age, drinking status, accident timeframe, accident mechanism, electric scooter proficiency (period of use), injury severity, severe trauma, lethality, admission to the intensive care unit, surgery under general anesthesia, and the trauma region.

RESULTS

Among the 108 patients involved in electric scooter accidents, 92 patients were not wearing a helmet. Eighty-nine patients (85.2%) were male. The average age of the patients without a helmet was 31.3 years, while that of patients with a helmet was 34.1 years. The most frequent causes of accidents were lack of electric scooter operation experience and falling off the scooter due to obstacles (90 cases). Whether surgery was performed under general anesthesia was not associated with helmet use or non-use, although all patients who underwent facial fracture surgery were not wearing a helmet.

CONCLUSION

The craniofacial region was most frequently affected in electric scooter accidents and wearing a helmet was the best way to prevent craniofacial trauma. Although helmet-wearing is mandatory, the majority of treated patients were not wearing a helmet at the time of injury. Thus, there is an urgent need to introduce a helmet rental system, as well as strict legal requirements, to improve this situation.

Slow and Steady Wins the Race: A Comparative Analysis of Standing Electric Scooters’ European Regulations Integrated with the Aspect of Forensic Traumatology

Fuel-driven cars are widely considered unsustainable and contrary to the new paradigm of smart growth planning. The need to reform transport behavior, policies, and infrastructure is among the priorities in urban policies around the world. Electric vehicles are an emerging technology that could advance sustainability programs. In the past year, there has been a rapid increase in the diffusion of electric scooters in several European cities, but various states have been unprepared for the rapid spread of green micro-mobility from a regulatory point of view. In addition, in parallel with the spread, there have been numerous road collisions involving standing electric scooters. The aim of this study was to obtain a detailed view of this phenomenon. We focused on the current legislation on electric micro-mobility at the European level to study and summarize the different attitudes adopted by various states whose regulations are present on the web. (It was not possible to evaluate the regulations of all European countries because they are not all available on online platforms.) The elements assessed in the various regulation were age limits, speed limits, compulsory use of helmets, administrative penalties, and the obligation to insure the new e-vehicle (standing scooter). In this study, we analyze the state of the art in electric micro-mobility, highlight the current situation’s limits, and propose new strategies to adequately integrate this new smart vehicle into the urban transport network.

Motor vehicle-related electric scooter injuries in the US: A descriptive analysis of NEISS data

INTRODUCTION

The introduction of scooter-share programs across the United States has led to an increased incidence of electronic scooter (e-scooter) injuries presenting to emergency departments (EDs). As legislation begins to push scooters from the sidewalk to the street, injuries resulting from collisions between e-scooters and motor vehicles are an important, but poorly characterized consideration. This study leverages data from a national injury surveillance system to characterize e-scooter versus motor vehicle collisions resulting in ED presentation.

METHODS

This study utilizes data from the National Electronic Injury Surveillance System (NEISS). NEISS was queried for e-scooter-related injuries from January 1st, 2015 through December 31st, 2019. Injuries were characterized as motor vehicle-related (MV-involved) or non-motor-vehicle-related (MV-uninvolved) based on a manual review by the study investigators. Weighted tabular analyses were used to characterize both types of e-scooter injuries across demographic, diagnostic, and event-related factors.

RESULTS

Over the study period an estimated 60,554 (95% CI: 37,525-84,594) injuries were treated in US EDs. Approximately 19% of these injuries involved motor vehicles. Those sustaining MV-involved injuries were significantly younger (p = 0.01), with a higher proportion of males injured (p = 0.01). Additionally, when compared to MV-uninvolved injuries, a significantly higher proportion of those with MV-involved injuries were admitted to the hospital for treatment (8.8% vs. 14.6%, p < 0.01). MV-involved injuries occurred primarily in the street (96.3%), while MV-uninvolved injuries were split across streets (44.0%), at one's home (~20%), and on public property (~20%) (p < 0.01).

CONCLUSIONS

Electric scooter injuries involving a motor vehicle differed from those that did not across several key categories. As e-scooters and motor vehicles start to share the road more frequently, greater consideration should be made regarding how these two modes of transportation interact with each other. The promotion of thoughtful e-scooter legislation and infrastructure changes could help promote safer travel.

E-scooter related injuries: Using natural language processing to rapidly search 36 million medical notes

Background

Shareable e-scooters have become popular, but injuries to riders and bystanders have not been well characterized. The goal of this study was to describe e-scooter injuries and estimate the rate of injury per e-scooter trip.

Methods and findings

Retrospective review of patients presenting to 180 clinics and 2 hospitals in greater Los Angeles between January 1, 2014 and May 14, 2020. Injuries were identified using a natural language processing (NLP) algorithm not previously used to identify injuries, tallied, and described along with required healthcare resources. We combine these tallies with municipal data on scooter use to report a monthly utilization-corrected rate of e-scooter injuries. We searched 36 million clinical notes. Our NLP algorithm correctly classified 92% of notes in the testing set compared with the gold standard of investigator review. In total, we identified 1,354 people injured by e-scooters; 30% were seen in more than one clinical setting (e.g., emergency department and a follow-up outpatient visit), 29% required advanced imaging, 6% required inpatient admission, and 2 died. We estimate 115 injuries per million e-scooter trips were treated in our health system.

Conclusions

Our observed e-scooter injury rate is likely an underestimate, but is similar to that previously reported for motorcycles. However, the comparative severity of injuries is unknown. Our methodology may prove useful to study other clinical conditions not identifiable by existing diagnostic systems.

Incidence of Electric Scooter-Associated Injuries in Finland From 2019 to 2021

This cross-sectional study examines the incidence of injuries associated with the use of electric scooters in Finland.

Utilization of Automated Keyword Search to Identify E-Scooter Injuries in the Emergency Department

Background and objective Accurate identification and categorization of injuries from medical records can be challenging, yet it is important for injury epidemiology and prevention efforts. Coding systems such as the International Classification of Diseases (ICD) have well-known limitations. Utilizing computer-based techniques such as natural language processing (NLP) can help augment the identification and categorization of diseases in electronic health records. We used a Python program to search the text to identify cases of scooter injuries that presented to our emergency department (ED). Materials and methods This retrospective chart review was conducted between March 2017 and June 2019 in a single, urban academic ED with approximately 80,000 annual visits. The physician documentation was stored as combined PDF files by date. A Python program was developed to search the text from 186,987 encounters to find the string "scoot" and to extract the 100 characters before and after the phrase to facilitate a manual review of this subset of charts. Results A total of 890 charts were identified using the Python program, of which 235 (26.4%) were confirmed as e-scooter cases. Patients had an average age of 36 years and 53% were male. In 81.7% of cases, the patients reported a fall from the scooter and only 1.7% reported wearing a helmet during the event. The most commonly injured body areas were the upper extremity (57.9%), head (42.1%), and lower extremity (36.2%). The most frequently consulted specialists were orthopedic and trauma surgeons with 28% of cases requiring a consult. In our population, 9.4% of patients required admission to the hospital. Conclusions The number of results and data returned by the Python program was easy to manage and made it easier to identify charts for abstraction. The charts obtained allowed us to understand the nature and demographics of e-scooter injuries in our ED. E-scooters continue to be a popular mode of transportation, and understanding injury patterns related to them may inform and guide opportunities for policy and prevention.

Where Have Shared E-Scooters Taken Us So Far? A Review of Mobility Patterns, Usage Frequency, and Personas

The emergence of micromobility services in the form of dockless shared e-scooters has resulted in a wide range of behavioral changes in urban environments. In order to effectively steer these changes towards sustainability targets, the characteristics of e-scooter trips and users’ behaviors should be understood further. However, there is a lack of systematic literature reviews in this domain. To address this gap, we provide a two-fold systematic literature review. The first aspect focuses on the categorization of temporal and spatial patterns of shared e-scooter usage. The second aspect focuses on a deeper understanding of e-scooter users’ behaviors, utilizing the principles of persona design. The analysis of temporal patterns highlights the commonality of midday, evening, and weekend peak usage across cities, while spatial patterns suggest e-scooters are used for traveling to recreational and educational land use, as well as city center areas. The synthesis of findings on users’ behaviors has resulted in six categories, with four user types based on usage frequency (one time, casual, power, and non-adopters), and two motivation-based personas (users who are not satisfied with current mobility options and users who have had positive travel experience from e-scooter usage). The overall findings provide important lessons for evaluating this emerging mobility service, which should be considered for steering its development in public-private stakeholder networks.