A Predictive Model to Analyze the Factors Affecting the Presence of Traumatic Brain Injury in the Elderly Occupants of Motor Vehicle Crashes Based on Korean In-Depth Accident Study (KIDAS) Database.

Traumatic brain injury (TBI), also known as intracranial injury, occurs when an external force injures the brain. This study aimed to analyze the factors affecting the presence of TBI in the elderly occupants of motor vehicle crashes. We defined elderly occupants as those more than 55 years old. Damage to the vehicle was presented using the Collision Deformation Classification (CDC) code by evaluation of photos of the damaged vehicle, and a trauma score was used for evaluation of the severity of the patient's injury. A logistic regression model was used to identify factors affecting TBI in elderly occupants and a predictive model was constructed. We performed this study retrospectively and gathered all the data under the Korean In-Depth Accident Study (KIDAS) investigation system. Among 3697 patients who visited the emergency room in the regional emergency medical center due to motor vehicle crashes from 2011 to 2018, we analyzed the data of 822 elderly occupants, which were divided into two groups: the TBI patients (N = 357) and the non-TBI patients (N = 465). According to multiple logistic regression analysis, the probabilities of TBI in the elderly caused by rear-end (OR = 1.833) and multiple collisions (OR = 1.897) were higher than in frontal collision. Furthermore, the probability of TBI in the elderly was 1.677 times higher in those with unfastened seatbelts compared to those with fastened seatbelts (OR = 1.677). This study was meaningful in that it incorporated several indicators that affected the occurrence of the TBI in the elderly occupants. In addition, it was performed to determine the probability of TBI according to sex, vehicle type, seating position, seatbelt status, collision type, and crush extent using logistic regression analysis. In order to derive more precise predictive models, it would be needed to analyze more factors for vehicle damage, environment, and occupant injury in future studies.

Comparison of the epidemiology and injury profile among injured patients involved in special purpose vehicle-related incidents in South Korea.

Injuries caused by mobile machinery or special purpose vehicles (SPVs) can lead to high socio-medical cost and fatality. In this descriptive study, we compared the epidemiology and injury profile of injured patients involved in SPVs-related incidents. We analyzed a nationwide database of SPV-related injured patients between January 2011 and December 2016. Injured patients were classified into three groups: pedestrian, motor vehicle occupant (MVO), and SPV operator groups. Of 1,419 cases, the highest number of SPV-related injured patients were found in the age group 40-59 years (671 cases, 47.3%) and at transport area (771 cases, 54.3%). The injury was most severe in the SPV operator group. The lower extremities were the most common fracture site, and intrathoracic injury was the most common visceral regions for SPV-related injured patients. SPV operator could lead to fatal intrathoracic injuries.

Comparison of epidemiology and injury profile between vulnerable road users and motor vehicle occupants in road traffic fatalities.

Objective: Road traffic injuries (RTIs) are a major global health issue causing a global burden of mortality and morbidity. Half of all fatalities on the world's roads are vulnerable road users (VRUs). The targeted intervention strategies based on fatality analysis focusing on VRUs can effectively contribute to reducing RTIs. This study aimed to compare VRUs and motor vehicle occupants (MVOs) in terms of epidemiology and injury profile. Methods: We utilized a nationwide, prospective database of RTI-related mortality cases for patients who visited 23 emergency departments between January 2011 and December 2015. All fatalities due to RTIs in the prehospital phase or in-hospital were eligible, excluding patients with unknown mode of transport and those admitted to general wards. The primary and secondary outcomes were fracture injuries and visceral injuries diagnosed using the International Classification of Diseases, Tenth Revision (ICD-10). We compared fracture injuries between VRUs and MVOs using Abbreviated Injury Scale (AIS) 2- and 2+ classification. Results: Among a total 3,694 road traffic fatalities (RTFs), 43.3% were pedestrians, followed by MVOs (27.0%), motorcyclists (18.9), bicyclists (6.6%), and agricultural vehicle users (4.2%). The elderly (>60 years old) accounted for 54.9% of VRU fatalities. RTFs occurred most frequently in the autumn and the VRU group and the MVO group showed significant differences in weekly and diurnal variation in RTFs. The injury severities (AIS 2+) of the head, neck, and thorax were significantly different between the 2 groups (P < 0.05). Head (32.1%) and intracranial (58.6%) injuries were the most common fracture and visceral injury sites for RTFs, followed by the thorax and intrathoracic organs (25.3 and 28.8%, respectively). Conclusions: Elderly pedestrians should be targeted for decreases in RTFs, and road traffic safety interventions for VRUs should be made based on the analysis of temporal epidemiology and injury profiles of RTFs.

Protective effect of helmet use on cervical injury in motorcycle crashes: A case-control study.

INTRODUCTION: Helmet use during motorcycle crashes (MCCs) has been shown to reduce traumatic brain injury and mortality. However, preventive effects of its use on cervical spine injury remain controversial. In this study, we evaluated whether helmet use can reduce cervical spine injury during MCCs. PATIENTS AND METHODS: A case-control study using data from the Emergency Department-based Injury In-depth Surveillance (EDIIS) registry was conducted. Cases were defined as patients with cervical spine injury [≥2 points in the Abbreviated Injury Scale (AIS)] in MCCs from 2011 to 2016. Four controls were matched to one case with strata which included age and sex from the EDIIS registry. Primary outcome was cervical spine injury, secondary outcome was intensive care unit (ICU) admission, and tertiary outcomes was mortality. Multivariable logistic regression analysis was used to calculate odds ratios (OR) with 95% confidence intervals (CIs) to evaluate the associations between helmet use and related outcomes. RESULTS: In total, 2600 patients were analysed; among these, 1145 (44.0%) used helmets at the time of crashes. The helmet group showed lower alcohol consumption and mortality rates than the no helmet group (alcohol: 3.2% vs. 9.2%, respectively, and mortality: 2.4% vs. 7.1%, respectively; p < 0.01). Compared with the no helmet group, the helmet group was less likely to have cervical spine injury [adjusted OR, 0.62 (0.51-0.77)]. In addition, helmet use has been shown to help prevent ICU admission and mortality [adjusted OR, 0.45 (0.36-0.56) and 0.32 (0.21-0.51), respectively]. CONCLUSION: Helmet use was found to have significant preventive effects on cervical spine injury during MCCs.