Bicycle Injuries Research Articles

Some features of the formation of injuries in cyclists with different types of bicycle injuries

Some features of the formation of injuries in cyclists with different types of bicycle injuries

Epidemiology of Downhill Mountain Biking Injuries: 178 Injuries in 129 Patients

Epidemiology of Downhill Mountain Biking Injuries: 178 Injuries in 129 Patients

The Analysis of the Factors Influencing the Severity of Bicyclist Injury in Bicyclist-Vehicle Crashes

Transportation and technological development have for centuries strongly influenced the shaping of urbanized areas. On one hand, it undoubtedly brings many benefits to their residents. However, also has a negative impact on urban areas and their surroundings. Many transportation and technological solutions lead, for example, to increased levels of pollution, noise, excessive energy use, as well as to traffic accidents in cities. So, it is important to safe urban development and sustainability in all city aspects as well as in the area of road transport safety. Due to the long-term policy of sustainable transport development, cycling is promoted, which contributes to the increase in the number of this group of users of the transport network in road traffic for short-distance transport. On the one hand, cycling has a positive effect on bicyclists’ health and environmental conditions, however, a big problem is an increase in the number of serious injuries and fatalities among bicyclists involved in road incidents with motor vehicles. This study aims to identify factors that influence the occurrence and severity of bicyclist injury in bicyclist-vehicle crashes. It has been observed that the factors increasing the risk of serious injuries and deaths of bicyclists are: vehicle driver gender and age, driving under the influence of alcohol, exceeding the speed limit by the vehicle driver, bicyclist age, cycling under the influence of alcohol, speed of the bicyclist before the incident, vehicle type (truck), incident place (road), time of the day, incident type. The obtained results can be used for activities aimed at improving the bicyclists’ safety level in road traffic in the area of analysis.

Impact of the COVID-19 Pandemic on road traffic collision injury patterns and severity in Al-Ain City, United Arab Emirates

BackgroundThe COVID-19 Pandemic lockdowns restricted human and traffic mobility impacting the patterns and severity of road traffic collisions (RTCs). We aimed to study the effects of the COVID-19 Pandemic on incidence, patterns, severity of the injury, and outcomes of hospitalized RTCs trauma patients in Al-Ain City, United Arab Emirates.MethodsWe compared the data of two cohorts of patients which were collected over two periods; the Pandemic period (28 March 2020 to 27 March 2021) and the pre-pandemic period (28 March 2019 to 27 March 2020). All RTCs trauma patients who were hospitalized in the two major trauma centers (Al-Ain and Tawam Hospitals) of Al-Ain City were studied.ResultsOverall, the incidence of hospitalized RTC trauma patients significantly reduced by 33.5% during the Pandemic compared with the pre-pandemic period. The mechanism of injury was significantly different between the two periods (p < 0.0001, Fisher’s Exact test). MVCs were less during the Pandemic (60.5% compared with 72%), while motorcycle injuries were more (23.3% compared with 11.2%). The mortality of hospitalized RTC patients was significantly higher during the Pandemic (4.4% compared with 2.3%, p = 0.045, Fisher’s Exact test). Logistic regression showed that the significant factors that predicted mortality were the low GCS (p < 0.0001), admission to the ICU (p < 0.0001), and the high ISS (p = 0.045). COVID-19 Pandemic had a very strong trend (p = 0.058) for increased mortality.ConclusionsOur study has shown that the numbers of hospitalized RTC trauma patients reduced by 33.5% during the COVID-19 Pandemic compared with the pre-pandemic period in our setting. This was attributed to the reduced motor vehicle, pedestrian and bicycle injuries while motorcycle injuries increased. Mortality was significantly higher during the Pandemic, which was attributed to increased ISS and reduced GCS.

The significance of a concomitant clavicle fracture in flail chest patients: incidence, concomitant injuries, and outcome of 12,348 polytraumata from the TraumaRegister DGU®

PurposeIsolated clavicle fractures (CF) rarely show complications, but their influence in the thorax trauma of the seriously injured still remains unclear. Some authors associate CF with a higher degree of chest injuries; therefore, the clavicle is meant to be a gatekeeper of the thorax.MethodsA retrospective analysis of the TraumaRegister DGU® (project 2017-10) was carried out involving the years 2009–2016 (ISS ≥ 16, primary admission to a trauma center). Cohort formation: unilateral and bilateral flail chest injuries (FC), respectively, with and without a concomitant CF.Results73,141 patients (26.5% female) met the inclusion criteria and 12,348 had flail chest injuries (FC; 20.0% CF; 67.7% monolateral FC), 25,425 other rib fractures (17.7% CF), and 35,368 had no rib fractures (6.5% CF). On average, monolateral FC patients were 56.0 ± 17.9 years old and bilateral FC patients were 57.7 ± 19 years old. The ISS in unilateral and bilateral FC were 29.1 ± 11.7 and 42.2 ± 12.9 points, respectively. FC with a CF occurred more frequently with bicycle and motorbike injuries in monolateral FC and pedestrians in bilateral FC injuries and less frequently due to falls. Patients with a CF in addition to a FC had longer hospital and ICU stays, underwent artificially respiration for longer periods, and died less often than patients without a CF. The effects were highly significant in bilateral FC. CF indicates more relevant concomitant injuries of the lung, scapula, and spinal column. Moreover, CF was associated with more injuries of the extremities in monolateral CF.ConclusionDue to the relevance of a concomitant CF fracture in FC, diagnostics should focus on finding CFs or rule them out. Combined costoclavicular injuries are associated with a significantly higher degree of thoracic injuries and longer hospital stays.

Weekday bicycle traffic and crash rates during the COVID-19 pandemic

IntroductionOne of the most consequential effects of the COVID-19 lockdowns was a dramatic reduction in travel during peak hours. Transportation modes also shifted—in particular, travel by car became more rare while bicycling saw a resurgence. Given that a typical year sees the most severe bicycle crashes in peak commuter traffic, the shift toward bicycle travel that occurred in 2020 will likely have been accompanied by unique changes in rider behavior (e.g., where and when they choose to ride) as well as the frequency and severity of vehicle-bicycle crashes. MethodsThe current study compared weekday bicycle traffic and crashes in Arlington, VA from March–December 2020 with the same period from years prior, 2013–2019. Bicycle traffic data were obtained from 16 embedded counters placed throughout the study area, in both off-road trails and on-road bike lanes. ResultsWe found that 2020 midday traffic nearly doubled compared to the year before, increasing from an average of 68 riders per hour to 120 (+76%). By contrast, morning traffic fell from an average of 87 riders per hour to just 45 (−49%). Change in evening traffic depended on the location of the counters: more evening bicycles were counted on off-road, multi-use trails (+6%) but fewer on on-road lanes (−27%). The changes to 2020 bicycle traffic patterns were also associated with a 28% reduction in bicycle injury crash rate per counted cyclist. ConclusionThe reduced crash risk observed in 2020 was likely due in part to the reduction of morning, on-road bicycle travel, which past research has found to be particularly dangerous for riders. Conversely, the availability of multi-use off-road trails seems to have been a protective factor against bicycle-motor vehicle crash risk in the face of greater bicycle travel volume.

Electric Bicyclist Injury Severity during Peak Traffic Periods: A Random-Parameters Approach with Heterogeneity in Means and Variances.

Accidents involving electric bicycles, a popular means of transportation in China during peak traffic periods, have increased. However, studies have seldom attempted to detect the unique crash consequences during this period. This study aims to explore the factors influencing injury severity in electric bicyclists during peak traffic periods and provide recommendations to help devise specific management strategies. The random-parameters logit or mixed logit model is used to identify the relationship between different factors and injury severity. The injury severity is divided into four categories. The analysis uses automobile and electric bicycle crash data of Xi’an, China, between 2014 and 2019. During the peak traffic periods, the impact of low visibility significantly varies with factors such as areas with traffic control or without streetlights. Furthermore, compared with traveling in a straight line, three different turnings before the crash reduce the likelihood of severe injuries. Roadside protection trees are the most crucial measure guaranteeing riders’ safety during peak traffic periods. This study reveals the direction, magnitude, and randomness of factors that contribute to electric bicycle crashes. The results can help safety authorities devise targeted transportation safety management and planning strategies for peak traffic periods.

Bicycle injuries presenting to the emergency department during COVID-19 lockdown.

AimSince the start of the COVID‐19 pandemic, there have been many changes in the presenting complaints in paediatric emergency departments (EDs). We sought to characterise the impact of the COVID‐19 pandemic on bicycle‐related injuries in children presenting to a tertiary care paediatric ED.MethodsWe conducted a descriptive, cross‐sectional study of ED visits to a large urban tertiary children's hospital, comparing March to October 2020 (the study period) to the same date range 2 years prior (i.e. March to October 2018–2019). We included children 0–17.99 years presenting for a bicycle‐related injury. We compared absolute visit counts of bike injuries per month, demographics, triage acuity, injury type and disposition.ResultsA total of 1215 bike‐related visits were analysed. There were 234 presentations in 2018 (March to October), 305 in 2019, and 676 in 2020. Overall, the mean age was 9.5 years (standard deviation 5.5–13.5), there were 67% males, median Canadian Emergency Department Triage and Acuity Scale score was 3 (interquartile range 3–4) and the most common injuries were fractures (n = 471, 38.8%). There were significantly more bike injuries presenting to the ED per month in the COVID group, 33.7(17.9) versus 84.5(61.4) (two‐tailed P value = 0.041). There was no statistical difference in ‘severe injuries’ pre‐ versus post‐COVID (odds ratio 0.815 (95% confidence interval 0.611–1.088), P = 0.165).ConclusionThere was a significant increase in bicycle‐related injuries presenting to our ED during the pandemic, compared to previous years. Evaluating these trends will allow for the exploration of harm reduction strategies for preventing future bicycle‐related injuries.

Impact of alcohol and drug use on bicycle and electric scooter injuries and hospital admissions in the United States

Introduction Bicycles and electric scooters (e-scooters) are convenient and accessible means of transportation. Participant safety is contingent on available infrastructure and safe riding practices including not riding while intoxicated. Understanding national prevalence and injury characteristics of bicycle and e-scooter riders who ride while intoxicated may promote awareness campaigns for safe riding practices and decrease morbidity. Methods The National Electronic Injury Surveillance System (NEISS) provides national estimates of injuries that present to emergency departments across the United States. We obtained case information on admitting status, body part injured, diagnosis of injury, age, sex, alcohol usage, and drug usage. We then queried NEISS for injuries related to bicycles and e-scooters in 2019. Results A weighted total of 270,571 (95% confidence interval (CI): 204,517–336,625) bicycle injuries occurred in the United States during 2019; alcohol and drug use were associated with 7% (95% CI: 6–9) and 2% (95% CI: 2–3) of all injuries, respectively. Twenty-four percent (CI: 18--31) of alcohol- and 29% (95% CI: 20–41) of drug-related bicycle injuries resulted in hospital admissions, compared to 15% (95% CI: 12–17) of non–alcohol- and 15% (95% CI: 13–18) of non–drug-related injuries ( p &lt; .001 and p = .002, respectively). A total of 28,702 (95% CI: 13,975–43,428) e-scooter injuries occurred in 2019; alcohol and drug use were associated with 8% (95% CI: 5–12) and 1% (95% CI: 1–2) of injuries, respectively. Sixty percent (95% CI: 47–72) of alcohol-related e-scooter injuries resulted in head trauma, compared to 28% (95% CI: 24–32) of non–alcohol-related injuries ( p &lt; .001). Conclusions Intoxication is associated with increasingly severe injuries, hospital admissions, and head trauma in bicycle and e-scooter riders. The findings support awareness campaigns to educate riders about risky practices, improve non-auto infrastructure, and promote helmet usage.

Changes in pediatric major trauma epidemiology, injury patterns, and outcome during COVID-19-associated lockdown.

The COVID-19 pandemic and its associated preventive measures such as national and regional lockdowns have dramatically changed the epidemiology of pediatric admissions to the emergency department. Nevertheless, there are scant data on the epidemiology and injury patterns of major pediatric trauma injuries during these lockdown periods. A single-center retrospective study of data obtained from a tertiary level 1 trauma hospital trauma registry. The data included demographics, injury mechanisms, injury severity and type, treatment, and resource utilization in children aged 0-18years who required trauma team activation upon arrival. The analysis compares the data from the 5-week lockdown period from March to May 2020 in Jerusalem, Israel, to its parallel periods in 2018-2019. A total of 187 trauma visits that required trauma team activation (TTA) were analyzed: 48 visits during the lockdown period vs. 139 in 2018-2019, corresponding to a 40% drop in TTA. There was a significant decrease of 34% in MVA-related injuries (p = 0.0001) but a significant increase of 14% in burns (p = 0.01) and a 16% increase in bicycle-related injuries (p = 0.001). No changes in ISS, injury patterns, admission rate, PICU utilization, or need for interventions were observed. There was a significant decrease in the number of overall pediatric trauma visits during the 2020 lockdown, mainly in MVA-associated trauma, but an increase in burns and bicycle injuries. These findings can thus inform policy makers as to the need to formulate prevention awareness programs alerting the public to indoor hazards and the dangers of activities outside the home. Furthermore, it can inform hospital policy decision-making in future lockdowns. The fact that PICU admissions and the need for operating rooms stayed unchanged suggests that it is vital to maintain trauma team capabilities even during lockdowns.

What factors impact pedestrian and cyclist fatalities? A state level analysis

BackgroundPedestrian and bicyclist injuries and fatalities have increased since 2010 after a long downward trend. Trucks and SUVs, collectively called light trucks, have also increased in sales and size, which may affect pedestrians and bicyclists. Additionally, pedestrian and cyclist commuters vary by state and it has been speculated that an increase in such commuters may affect fatalities. Studying vulnerable road users can bestow clues on best practices for infrastructure and public health.MethodsState level pedestrian and cyclist fatality data was obtained from the National Highway Transportation Safety Administration for 2018. Light truck registration by state was obtained from the Office of Highway Policy Information for 2018. Commuters who walk or bike to work were obtained from the American Community Survey from 2009 to 2011, from the latest Centers for Disease Control report. We performed multiple linear regression, accounting for total motor vehicle lane miles per 100 people, also obtained from the Office of Highway Policy Information for 2018. Multiple regression analysis was performed to assess predictors for pedestrian and cyclist fatalities with the predictors variables of light truck registration, lane miles per 100 people, and proportion of commuters who are vulnerable road users. Secondary analysis included simple linear regression of the predictor variables against each other.ResultsThe multiple regression model, including proportion of light truck registration, lane miles per 100 people, and proportion of commuters who are vulnerable road users, accounted for 18% of the variability in the outcome variable (p = 0.03). An increased number of vulnerable road users were negatively associated with pedestrian and bicyclist fatality. Additionally, there appeared to be an association between motor vehicle lane miles per 100 people and proportion of light truck registrations that was also significant (p < 0.01).ConclusionThe variables affecting vulnerable road user deaths are important to understand given their increased risk exposure on the road. This state level study identifies a potential protective variable with increased vulnerable road users being associated with a decrease in pedestrian and bicyclist death rates. Additionally, light truck proportions do not appear to have a significant effect on death rates.

Analysis of Bicycle-Motor Vehicle Crashes in San Antonio, Texas.

Bicycling is inexpensive, environmentally friendly, and healthful; however, bicyclist safety is a rising concern. This study investigates bicycle crash-related key variables that might substantially differ in terms of the party at fault and bicycle facility presence. Employing 5 year (2014–2018) data from the Texas Crash Record and Information System database, the effect of these variables on bicyclist injury severity was assessed for San Antonio, Texas, using bivariate analysis and binary logistic regression. Severe injury risk based on the party at fault and bicycle facility presence varied significantly for different crash-related variables. The strongest predictors of severe bicycle injury include bicyclist age and ethnicity, lighting condition, road class, time of occurrence, and period of week. Driver inattention and disregard of stop sign/light were the primary contributing factors to bicycle-vehicle crashes. Crash density heatmap and hotspot analyses were used to identify high-risk locations. The downtown area experienced the highest crash density, while severity hotspots were located at intersections outside of the downtown area. This study recommends the introduction of more dedicated/protected bicycle lanes, separation of bicycle lanes from the roadway, mandatory helmet use ordinance, reduction in speed limit, prioritization of resources at high-risk locations, and implementation of bike-activated signal detection at signalized intersections.

Factors related to youth self-efficacy for injury prevention bicycle skills

Introduction: Bicycle riding is a common activity for children, but they are prone to bicycle-related injuries. It is well-established that injury prevention measures such as wearing a helmet and correctly riding a bicycle can reduce the severity of an injury and the likelihood of having an accident. However, how to increase bicycle injury prevention behaviors among children, who collectively fail to engage in injury prevention behaviors, is less well understood. Self-efficacy is consistently predictive of injury prevention behavior, making it an important approach to understanding injury prevention skills among this key population. The objective of this study was to explore and identify factors internal to the child as well as factors about his or her environment that predict a child’s self-efficacy for injury prevention skills. Method: Two generalized linear mixed effects models were created from survey data collected from elementary school students (n = 2,255) as part of a school-based bicycle education program. Models focused on self-efficacy for riding a bicycle and self-efficacy for wearing a helmet correctly. Results: In both models, road safety knowledge, opportunity for skill building through owning appropriate equipment (a bicycle or helmet), and situation through perception of neighborhood safety were predictive. The analyses reveal these variables as key factors for greater confidence, with feeling safe riding in the neighborhood, in particular, emerging as highly predictive of self-efficacy for injury prevention skills. Conclusions: These findings highlight the interplay of individual and environmental factors within confidence for injury prevention behavior. Given self-efficacy’s strong relationship to prevention behavior, these findings indicate actionable strategies. Practical Applications: The key factors highlighted in this study can be used by policymakers to target specific areas (e.g., neighborhood safety) to promote self-efficacy and thus improve injury prevention. These factors can also inform strategies for establishing safety skills in bicycle-safety education programs.

Retrospective Analysis of Dento-alveolar Injuries at a Swiss University Clinic (2011-2015).

The aim of this study was to evaluate all dento-alveolar injuries occurring within a period of 5 years that were examined at the Department of Oral Surgery and Stomatology at the University of Bern. The case histories of 852 patients (522 males and 330 females) were assessed retrospectively. The mean age was 17 years and 9 months. The youngest patient was 10 months old, the oldest was 91 years old. Most accidents were recorded in the months of March and July. Friday was observed as the weekday when accidents were at their peak. 54% of trauma patients were first examined on the day of the accident. The most frequent causes of accident were falls, cycling or sports accidents. Injury types included concussion (72.4%), subluxation (14%) and luxation (7.7%). Crown fractures without pulp exposure were recorded in 522 teeth (10.7%). Rare types of trauma were crown fractures with pulp exposure (3.7%), and avulsion injuries (3.2%). The most frequently affected teeth were central incisors (40%), followed by lateral incisors (35.6%) and canines (19.5%). 71.5% of the patients with dento-alveolar trauma also had soft-tissue injuries (from abrasions to lacerations), mostly lip (51.6%), gingival (19%), and chin injuries (10.9%). The multivariate analysis showed that age had a significant impact on concussions, subluxations, intrusions, crown fractures, root fractures and non-oral injuries. For concussions and subluxations, the probability of an injury was the highest for the mixed dentition group. For intrusions, the probability of an injury decreased with age, but it was vice versa for crown fractures, root fractures and non-oral injuries. It was found that bicycle injuries had the highest injury probability for avulsions, luxations, subluxations, soft tissue - and non-oral injuries.

Retrospective Analysis of Dento-alveolar Injuries at a Swiss University Clinic (2011-2015).

The aim of this study was to evaluate all dento-alveolar injuries occurring within a period of 5 years that were examined at the Department of Oral Surgery and Stomatology at the University of Bern. The case histories of 852 patients (522 males and 330 females) were assessed retrospectively. The mean age was 17 years and 9 months. The youngest patient was 10 months old, the oldest was 91 years old. Most accidents were recorded in the months of March and July. Friday was observed as the weekday when accidents were at their peak. 54% of trauma patients were first examined on the day of the accident. The most frequent causes of accident were falls, cycling or sports accidents. Injury types included concussion (72.4%), subluxation (14%) and luxation (7.7%). Crown fractures without pulp exposure were recorded in 522 teeth (10.7%). Rare types of trauma were crown fractures with pulp exposure (3.7%), and avulsion injuries (3.2%). The most frequently affected teeth were central incisors (40%), followed by lateral incisors (35.6%) and canines (19.5%). 71.5% of the patients with dento-alveolar trauma also had soft-tissue injuries (from abrasions to lacerations), mostly lip (51.6%), gingival (19%), and chin injuries (10.9%). The multivariate analysis showed that age had a significant impact on concussions, subluxations, intrusions, crown fractures, root fractures and non-oral injuries. For concussions and subluxations, the probability of an injury was the highest for the mixed dentition group. For intrusions, the probability of an injury decreased with age, but it was vice versa for crown fractures, root fractures and non-oral injuries. It was found that bicycle injuries had the highest injury probability for avulsions, luxations, subluxations, soft tissue - and non-oral injuries.

The National Interscholastic Cycling Association (NICA) Mountain Biking Injury Surveillance System (ISS): Analysis of 66,588 Student Athlete-Years of Injury Data.

Interscholastic youth cross-country mountain bike racing in the United States has grown significantly over the past decade, yet little is known about the risk profile in this age group. Aiming to protect participants, we implemented a prospective, longitudinal injury surveillance system for the purpose of better understanding youth mountain biking injuries and implementing safety measures. Data were collected during competition years 2018–2020, totaling 66,588 student athlete-years. Designated reporters from each team received weekly emails with exposure and incident report forms. Variables analyzed included demographic, rider-related, trail-related, and other data. Injury characteristics during the COVID-19 pandemic in 2020 were compared to the years 2018 and 2019. More student athletes participated in the 2020 season (25,261) than in prior seasons (18,575 in 2018 and 22,752 in 2019). During competition year 2020, overall injury proportion was lower (1.7% versus 3.0% in 2018 and 2.7% in 2019). Variables associated with injury, body part injured, type of injury, time-loss, and disposition following injury were similar between all years. Despite the pandemic and resultant changes to competition, student athletes continued to ride their bikes and become injured, but the proportion of injuries differed. This report details injury characteristics in youth mountain bike racing, including a comparison of before and during the pandemic.

Patterns of orthopaedic injury among hospitalised personal mobility device users and bicycle riders: a comparative study.

Introduction:Personal mobility devices (PMDs), such as electronic scooters or motorised bicycles, are efficient modes of transportation. Their recent popularity has also resulted in an increase in PMD-related injuries. We aimed to characterise and compare the nature of injuries sustained by PMD users and bicycle riders.Methods:This retrospective study compared injury patterns among PMD and bicycle users. 140 patients were admitted between November 2013 and September 2018. Parameters studied included patients’ demographics (e.g. age, gender and body mass index), type of PMD, nature of injury, surgical intervention required, duration of hospitalisation and time off work.Results:Of 140 patients, 46 (32.9%) patients required treatment at the department of orthopaedic surgery. 19 patients were PMD users while 27 were bicycle riders. 16 (84.2%) patients with PMD-related injuries were men. PMD users were significantly younger (mean age 45 ± 15 years) when compared to bicycle riders (mean age 56 ± 17 years; P <0.05). A quarter (n = 5, 26.3%) of PMD users sustained open fractures and over half (n = 10, 52.6%) required surgical intervention. Among 27 bicycle users, 7.4% (n = 2) of patients sustained open fractures and 70.4% (n = 19) required surgical intervention. Both groups had comparable inpatient stay duration and time off work.Conclusion:PMD-related orthopaedic traumas are high-energy injuries, with higher rates of open fractures, when compared to bicycle injuries. In addition, PMD users are significantly younger and of economically viable age. Prolonged hospitalisation and time off work have socioeconomic implications. Caution should be exercised when using PMDs.

An Application of Fuzzy Value Assignment In A Relation In Two Wheeler Road Accident Non Wearing Helmet Death Details

The most important feature of data manipulation is the valve assignment in relation to the similarity method. When it comes to changing values and specifying direction, this method is extremely accurate. The primary source of data for this study is the 2019 two-wheeler non-helmet death list. Every day, there is a new accident. On the other hand, bicycle injuries are at an all-time high among this generation's riders. In this article, we'll examine the number of non-helmet two-wheeler accidents each month, month by month, and rotation by rotation.

Comparing orthopaedic paediatric trauma in a rural district general hospital and an urban major trauma centre: A retrospective cohort study

BackgroundStudies from countries such as Australia and South Africa have demonstrated a difference in the types of injury managed in rural hospitals compared to larger, urban hospitals and so conclude staff require a different skill-set to work in these environments. There is some evidence this attitude may be prevalent amongst UK surgical trainees, resulting in difficulty recruiting to rural settings. In addition, studies have compared mortality in paediatric trauma patients in rural and urban hospitals, but none have described types of injury or orthopaedic operations required.We hypothesise the distribution of operative, orthopaedic paediatric trauma in a rural district general and an urban major trauma centre will not differ significantly in terms of patterns and mechanism of injury, orthopaedic intervention or time to theatre. Materials/methodsAll operative paediatric patients (0–15yrs) seen during an acute orthopaedic take at a rural district general and an urban major trauma centre were included. Non-operative admissions were excluded. Patients were identified using daily trauma work lists from each site. Outcomes were age, injury type, operation, time to theatre, seasonality and mechanism. Results183 patients from the urban hospital and 103 from the rural were identified. There were no significant differences found in age of patient, seasonality or time to theatre between cohorts (p > 0.05). There were also broadly similar patterns of injury and operations performed in both groups, although k-wiring was more often employed in the rural cohort than the urban (27% vs 17% of total operations). There were more bicycle and shinty related injuries in the rural cohort, and equine related in the urban. ConclusionsPaediatric trauma admissions do not vary significantly between rural and urban trauma centres, although the types of procedure performed may be less conservative in a rural hospital. This may be due to geography or differences in ED practice.

Comparison of motor vehicle-involved e-scooter and bicycle crashes using standardized crash typology

Introduction: The market share of e-scooters in the United States has proliferated in cities: 86 million trips were made on shared e-scooters in 2019, a more than 100% increase compared to 2018. However, the interaction of e-scooters with other road users and infrastructure remains uncertain. Method: This study scrutinized 52 e-scooter and 79 bicycle police-reported crashes in Nashville, Tennessee, from April 2018 to April 2020 from the Tennessee Integrated Traffic Analysis Network (TITAN) database. We used descriptive analysis and a recent prototype version of the Pedestrian and Bicycle Crash Analysis Tool (PBCAT) to classify crashes based on the locations of the crashes relative to roadway segments or intersections, as well as the maneuver of the motor vehicle and e-scooter/bicycle relative to the motor vehicle. Results: Two crash typologies can explain the majority of e-scooter crashes, while bicycle crashes are distributed over several crash typologies. Additionally, 1 in 10 e-scooter- and bicycle-motor vehicle crashes leads to the injury or fatality of the e-scooter rider or bicyclist. Furthermore, we noted statistically significant differences in spatial and temporal distribution, demographics, lighting conditions, and crash distance from home for e-scooter and bicycle crashes. Conclusions: The police crash report provides a comprehensive picture of e-scooter safety complementing existing literature. We found that e-scooter crash characteristics do not fully overlap with features of bicycle crashes. Practical Implications: A generalized engineering, education, and enforcement treatment to reduce and prevent e-scooter and bicycle crashes, injuries, and fatalities might not result in equal outcomes for each mode. More rigorous enforcement could be implemented to deter e-scooters riders under the age of 18 years and e-scooter safety campaigns could target female riders.