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Pelvic fracture, cracking or breaking of a portion of the pelvis are extremely common injuries in the side impact collisions of motor vehicles. Due to both its shape and structural architecture, mechanics of the pelvic bone is complicated. There is a lack of knowledge regarding the dynamic behavior of the pelvis and its biomechanical tolerance under impact environment. Hence this study is aimed at the understanding of the mechanical response of the human pelvis with three-dimensional finite element (FE) models, under side impact load, applied through a structure, equivalent to a car door. The door structure was modeled, considering few layers, consisting of foam (Styrodur®, 3035 CS), plastic (UHMWPE), steel, glass and steel, putting them in series. A soft tissue layer (equivalent to fat) was also considered on the greater trochanter location. These FE models (with and without the car door structure) were analyzed with ANSYS-LS-DYNA-® dynamic finite element software to compare the effect of the car door padding system for shock absorption. It was observed that with proper combination of shock absorbing material (foam, etc.) and its thickness, the transmission of impact load to the body part (pelvis, etc.) from the outer surface of the car door could be reduced.
Description of road traffic related knee injuries in published investigations is very heterogeneous. The purpose of this study was to estimate the risk of knee injuries in real world car impacts in Germany focusing vulnerable road users (pedestrians, bicyclists and motorcyclists) and restrained car drivers. The accident research unit analyses technical and medical data collected shortly after the accident at scene. Two different periods (years 1985-1993 and 1995-2003) were compared focusing on knee injuries (Abbreviated Injury Scale (AISKnee) 2/3). In order to determine the influences type of collision, direction and speed as well as the injury pattern and different injury scores (AIS, MAIS, ISS) were examined. 1.794 pedestrians, 742 motorcyclists, 2.728 bicyclists and 1.116 car drivers were extracted. 2% had serious ligamentous or bony injuries in relation to all injured. The risk of injury is higher for twowheelers than for pedestrians, but knee injury severity is higher for the latter group. Overall the current knee injury risk is low and significant reduced comparing both time periods (27%, p<0,0001). Severe injuries (AISKnee 2/3) were below 1%). Improved aerodynamic design of car fronts reduced the risk for severe knee injuries significantly (p=0,0015). Highest risk of injury is for motorcycle followed by pedestrians, respectively. Knee protectors could prevent injuries by reducing local forces. The classically described dashboard injury was rarely identified. The overall injury risk for knee injuries in road traffic is lower than estimated and reduced comparing both periods. The aerodynamic shape of current cars compared to older types reduced the incidence and severity of knee injuries. Further modification and optimization of the interior and exterior design could be a proper measurement. Classic described injury mechanisms were rarely identified. It seems that the AIS is still underestimating extremity injuries and their long term results.
Pedestrians represent about 20% of the overall fatalities in Europe- road traffic accidents. In this paper a methodology is proposed to understand why the numbers are so high, especially in the south of Europe and particularly in Portugal, . First a detailed statistical analysis using Ordinal Logistic Regression model (OLR) was applied to the gathered data from all Portuguese accidents with victims in the period 2010-2012. In a second stage accident reconstruction computational techniques using pedestrian biomechanical models are used to evaluate the accident conditions that lead to the injuries, such as the speed and the impact location. For biomechanical injury criterions, the AIS (Abbreviated Injury Scale), the HIC (Head Injury Criterion) and other injury criterions based on the resulting accelerations in the pedestrian's body are used. The statistical model reported that there were several predictors that significantly influenced the pedestrian injury severity in the event of a road accident, such as Pedestrian's age, Pedestrian's gender, Vehicle Design/Category or Driver's gender. The use of injury scales and biomechanical criterions in in-depth investigation of road accidents, such as AIS, can significantly improve the quality of the reconstruction process.
Road accidents are typically analyzed to address influences of human, vehicle, and environmental (primarily infrastructure) factors. A new methodology, based on a "Venn diagram" analysis, gives a broader perspective on the probable factors, and combinations of factors, contributing both to the occurrence of a crash and to sustaining injuries in that crash. The methodology was applied to 214 accidents on the Mumbai-Pune expressway. Factors contributing to accidents and injuries were addressed. The major human factors influencing accidents on this roadway were speeding (30%) and falling asleep (29%), while injuries were primarily due to lack of seat belt use (46%). The leading infrastructure factor for injuries was impact with a roadside manmade structure (28%), and the main vehicle factor for injuries was passenger compartment intrusion (73%). This methodology can help identify effective vehicle and infrastructure-related solutions for preventing accidents and mitigating injuries in India.
While many medical studies have dealt with the incidence, nature and treatment of polytrauma the injury-causing accident mechanisms are rarely discussed in detail, mostly due to the lack of documentation of the technical aspects. The present prospective study was started in late 2007 and collects data from traffic accidents with most severely injured in six south- German counties and two larger cities for the duration of one year. It is aimed at identifying and documenting all polytrauma cases (ISS ≥ 16) caused by traffic accidents and their crash circumstances. The data collection is based on an interdisciplinary concept to include both the police, emergency dispatch centers, hospitals and fire departments in the region and is completely anonymous. Potentially relevant cases where an emergency physician was called to the scene of a traffic accident are provided by the dispatch center. All three hospitals in the region suited for the treatment of polytraumatised patients record injuries, major diagnostic and surgery data. Data and images from the accident scene are provided by the police and by fire departments. The latter provide information which is usually not available from the police, like deployed airbags, vehicle extrication measures and detailed views of car interiors. The main objective of the study is to determine the structure of road users who sustain a polytrauma, their crash opponents and the injury patterns found in relation to the collision configuration and the protection by seat belts, air bags and other devices. With detailed documentation of vehicle damage and extrication measures the study is also intended to support the development of injury predictors for pre-hospital treatment and provide field data regarding further improvement of technical rescue.
The objective of the study is to measure the risk of pedestrian and bicyclist in urban traffic through an analysis of real-world accident data. The kinematics and injury mechanisms for both pedestrian and bicyclists are investigated to find the correlation of injury risks with injury related parameters. For this purpose, firstly 338 cases are selected as a sample from an IVAC accident database based on the In-depth Investigation of Vehicle Accident in Changsha of China. A statistic measurement of the fatality and serious injury risks with respect to impact speed was carried out by logistic regression analysis. Secondly, 12 pedestrian and 12 bicyclist accidents were further selected for reconstruction with MADYMO program. A comparative analysis was conducted based on the results from accident analysis and computer reconstructions for the injury risk, head impact conditions and dynamic response of pedestrians and bicyclists. The results indicate that bicyclists suffered lower risks of severe injuries and fatalities compared with pedestrians. The risks of AIS 3+ injury and fatality are 50% for pedestrians at impact speeds of 53.2 km/h and 63.3 km/h, respectively, while that for bicyclists at 62.5 km/h and 71.1 km/h, respectively. The findings could have a contribution to get a better understanding of pedestrians" and bicyclists" exposures in urban traffic in China, and provide background knowledge to generate strategies for pedestrian protection.
This study aimed at prediction of long bone fractures and assessment of lower extremity injury mechanisms in real world passenger car to pedestrian collision. For this purpose, two pedestrian accident cases with detail recorded lower limb injuries were reconstructed via combining MBS (Multi-body system) and FE (Finite element) methods. The code of PC Crash was used to determine the boundary conditions before collision, and then MBS models were used to reproduce the pedestrian kinematics and injuries during crash. Furthermore, a validated lower limb FE model was chosen to conduct reconstruction of injuries and prediction of long bone fracture via physical parameters of von Mises stress and bending moment. The injury outcomes from simulations were compared with hospital recorded injury data and the same long bone fracture patterns and positions can be observed. Moreover, the calculated long bone fracture tolerance corresponded to the outcome from cadaver tests. The result shows that FE model is capable to reproduce the dynamic injury process and is an effective tool to predict the risk of long bone fractures.
The paper aims to study the injury risk and kinematics of pedestrians involved in different passenger vehicle collisions. Furthermore, the difference of pedestrian kinematics in the accidents involved minivan and sedan was analyzed. The 18 sample cases of passenger car to pedestrian collisions were selected from the database of In-depth Investigation of Vehicle Accident in Changsha of China (IVAC),of which the 12 pedestrian accidents involved in a minivan impact for each case, and the 6 accidents in a sedan impact for each. The selected cases were reconstructed by using mathematical models of pedestrians and accident vehicles in a multi-body dynamic code MADYMO environment. The logistic regression models of the risks for pedestrian AIS 3+ injuries and fatalities were developed in terms of vehicle impact speed by analyzing the minivan-pedestrian and sedan-pedestrian accidents. The difference of pedestrian kinematics was identified by comparing the results from reconstructed pedestrian accidents between the minivans and sedans collisions. The result shows that there is a significant correlation among the impact speed and the severity of pedestrian injuries. The minivan poses greater risk to pedestrian than sedan at the same impact speed. The kinematics of pedestrian was greatly influenced by vehicle front shape.
Abschätzung der Gesamtzahl Schwerstverletzter in Folge von Straßenverkehrsunfällen in Deutschland
(2010)
Die Zahlen der im Straßenverkehr Getöteten, Schwer- und Leichtverletzten werden in Deutschland seit Jahren in amtlichen Statistiken geführt. Über die Gruppe der besonders schwer betroffenen Patienten liegen jedoch nur vage Schätzungen vor. Auch werden unterschiedliche Kriterien zur Definition dieser so genannten Schwerstverletzten verwendet, die zumeist auf einer Beschreibung der Art und der Schwere der Verletzungen beruhen. In der vorliegenden Arbeit sollen mit Daten aus dem Trauma-Register der DGU sowohl die unterschiedlichen Definitionen dargestellt werden, als auch über verschiedene Methoden die Gesamtzahl dieser Personen in Deutschland geschätzt werden. Das TraumaRegister DGU (TR-DGU) ist eine freiwillige Dokumentation von Unfallopfern, die lebend eine Klinik erreichen, dort behandelt werden und intensivmedizinisch betreut werden müssen. Das Register besteht seit 1993 und erfasst derzeit etwa 6.000 Fälle pro Jahr aus über 100 Kliniken. Pro Patient werden ca. 100 Angaben einschließlich der Codierung seiner Verletzungen gemäß Abbreviated Injury Scale (AIS) erfasst. Dieser Codierung erlaubt die Berechnung des Injury Severity Score (ISS) und des New ISS (NISS). Zum Vergleich werden folgende Definitionen eines Schwerstverletzten betrachtet: Maximum AIS ≥ 3; Maximum AIS ≥ 4; ISS ≥ 9; ISS ≥ 16; NISS ≥ 16, Polytrauma sowie die Notwendigkeit der Intensivtherapie. Am Beispiel des Kriteriums "ISS ≥ 16" werden schließlich auf drei verschiedene Arten die Gesamtzahl Schwerstverletzter Verkehrsunfallopfer geschätzt: 1.) in fünf ausgewählten Regionen werden die Schwerstverletzten aus dem TR-DGU mit der Anzahl Schwerverletzter aus der amtlichen Statistik verglichen, um den Anteil der besonders schwer betroffenen Patienten zu bestimmen. 2.) Aus dem TR-DGU wird je nach Versorgungsstufe des Krankenhauses (lokales, regionales oder überregionales Zentrum) die durchschnittliche Anzahl Schwerstverletzter ermittelt und dann über die Anzahl solcher Kliniken in Deutschland hochgerechnet. 3.) Die Zahl der Schwerstverletzten wird aus der Zahl der Getöteten Verkehrsunfallopfer geschätzt. Dazu nutzt man das Verhältnis von in der Klinik verstorbenen zu überlebenden Schwerstverletzten aus dem TR-DGU. Mit Literaturangaben zum Anteil von präklinisch Verstorbenen wird dann auf der Basis der Anzahl der Getöteten aus der amtlichen Statistik die Gesamtzahl Schwerstverletzter geschätzt. Je nach Definition eines Schwerstverletzten konnten zwischen 9.213 und 17.425 Fälle aus dem TR-DGU der letzten 10 Jahre berücksichtigt werden. Von diesen Patienten sind zwischen 12,7% und 20,2% im Krankenhaus verstorben. Die Krankenhaus Liegedauer der Überlebenden liegt zwischen 30 und 35 Tagen. Nimmt man die Definition "ISS -³ 16" als Basis (n=13.467), so reduziert sich die Zahl Schwerstverletzter um 37%, wenn man stattdessen den Begriff des Polytraumas wählt; betrachtet man hingegen die Intensivpflichtigkeit als Kriterium so erhöht sich die Zahl um 22%. Der erste Schätzansatz kommt zum Ergebnis, dass etwa 8-10% der Schwerverletzten zu den besonders schwer Verletzten zählen. Für ganz Deutschland erhält man damit Schätzwerte zwischen 6.300 und 7.900 Fälle pro Jahr. Die zweite Methode ergab, dass die Krankenhäuser der drei unterschiedlichen Versorgungsstufen jeweils 30,2, 11,5 oder 3,3 Fälle pro Jahr behandeln. Bezogen auf die 874 deutschen Kliniken ergeben sich geschätzte Gesamtzahlen von 6.800 bis 10.400 Fälle. Die dritte Methode zeigt, dass pro Patient, der im Krankenhaus verstirbt, 6,3 Schwerstverletzte überleben. Im Krankenhaus versterben jedoch etwa nur 25% bis 40% der insgesamt Getöteten; der Großteil der Getöteten verstirbt unmittelbar an der Unfallstelle. Damit müssen noch 1,5 bis 3 Todesfälle hinzugerechnet werden, was schließlich zu einem Verhältnis von 6,3 Schwerstverletzten zu 2,5 bis 4 Todesfällen führt. Bei einer Gesamtzahl von 5.595 Getöteten (Mittelwert 2002-2008) ergeben sich so Gesamtzahlen von 8.800 bis 14.000 Schwerstverletzte pro Jahr. Die Ergebnisse der angewendeten Schätzmethoden variieren stark und lassen auf eine Gesamtzahl von etwa 10.000 schwerstverletzten Verkehrsunfallopfern pro Jahr in Deutschland schließen. Bei Anwendung der Definition Intensivtherapie ergeben sich sogar etwa 12.500 Fälle. Alle Schätzmethoden sind gewissen Unsicherheiten ausgesetzt, die wenn möglich in Variationsrechnungen berücksichtigt wurden. Eine deutlich verbesserte Schätzung dieser Zahl ist jedoch erst möglich, wenn in wenigen Jahren vollzählige Erfassungen aus den derzeit entstehenden regionalen TraumaNetzwerken der DGU im TraumaRegister vorliegen.
Motorcycle riders are one of the most vulnerable road users. Annually, on estimate 6000 people are killed in motorcycle accidents in the former 15 EU countries. The objective of this research was to investigate and analyze the main aspects and causes of this vulnerability and the accidents in general. For this aim around 70 accidents in The Netherlands were investigated in the framework of an international research program (MAIDS). Also a control group of motorcycles with riders was investigated so that exposure could be taken into account. An important result is that human failure is in 82% of the cases the main cause of the accident, in 52% this is due the other vehicle driver. Perception and decision failures are the most common failures. The most injuries are caused by the environment but they are typically only less severe (AIS1). Injuries caused by the car (front and side) are typically severe injuries (AIS4+). Previous convictions of the MC rider seem to be related to the chance to get involved in an accident. It was shown that the Dutch and the total MAIDS accident sample are comparable.