- Email: [email protected]
Injury severity of pedestrians, bicyclists and motorcyclists resulting from crashes with reversing cars
Accident Analysis and Prevention 94 (2016) 46–51
Contents lists available at ScienceDirect
Accident Analysis and Prevention journal homepage: www.elsevier.com/locate/aap
Injury severity of pedestrians, bicyclists and motorcyclists resulting from crashes with reversing cars Sebastian Decker a,∗ , Dietmar Otte b , Dana Leslie Cruz a , Christian Walter Müller a , Mohamed Omar a , Christian Krettek a , Stephan Brand a a b
Trauma Department, Hannover Medical School, Carl-Neuberg-Str. 1, 30625 Hannover, Germany Accident Research Unit, Hannover Medical School, Karl-Wiechert-Allee 3, 30625 Hannover, Germany
a r t i c l e
i n f o
Article history: Received 9 November 2015 Received in revised form 4 May 2016 Accepted 12 May 2016 Keywords: Collision Reversing AIS MAIS Injury severity Road traffic accident (RTA)
a b s t r a c t Objective: Pedestrians, bicyclists and motorcyclists can suffer serious injury in road traffic crashes. To date, no studies examine the injury severity within this vulnerable cohort following collisions with reversing cars. Material and methods: Our institution prospectively maintains a database including medical and technical information regarding traffic accidents in our area, including urban and suburban regions. In a retrospective review of this database, the authors describe the injury severity of pedestrians, bicyclists and motorcyclists following traffic crashes involving reversing cars. Injury severity was described using the abbreviated injury scale (AIS) as well as the maximum abbreviated injury scale (MAIS). Results: This study included 234 crashes occurring between 1999 and 2012. The lower extremity was injured most often while also suffering more severe injuries with a median AIS of 1 compared to 0 in all other documented body regions. The upper extremity was injured second most often. AIS ranging from 4 to 6 were infrequent. AIS 3 however, was documented for the legs in 4.3% of patients. MAIS 0, 1, 2, 3, 5 and 9 were found in 1, 164, 46, 14, 1, and 8 patients in the study cohort, respectively. Pedestrians and motorcyclists were seriously injured in 9.1% and 9.6% of cases, respectively. In contrast, no bicyclists suffered serious injuries. As to the zone of impact, most collisions occurred at the rear center of the vehicle (35%) followed by rear left (26%), rear right (20%), side rear (11%), side center (4%) and side front (3%). 204 (87.2%) collisions occurred during the day, 19 (8.1%) at night and 11 (4.7%) at twilight. Speed was similar in crashes involving pedestrians, bicyclists and motorcyclists, being as high as 7.0 ± 3.6, 7.0 ± 4.0 and 7.9 ± 4.2 km/h respectively. Conclusions: This is the first study that analyzes injury severity among these vulnerable road users following collisions with reversing vehicles. The majority of collisions occur at low impact speed during the day. Most injuries resulting from these collisions are not serious, however pedestrians are at greatest risk of severe injury to any body region. The lower extremities suffer the most serious and frequent injuries within this cohort. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction Numerous factors influence the injury severity attributed to motor vehicle crashes including those involving non-passengers. Previous studies involving pedestrians struck by vehicles for
∗ Corresponding author. E-mail addresses: [email protected] (S. Decker), [email protected] (D. Otte), [email protected] (D.L. Cruz), [email protected] (C.W. Müller), [email protected] (M. Omar), [email protected] (C. Krettek), [email protected] (S. Brand). http://dx.doi.org/10.1016/j.aap.2016.05.010 0001-4575/© 2016 Elsevier Ltd. All rights reserved.
example have demonstrated an association between high-energy collisions and risk of death as well as the correlation between impact speed and injury severity. (Rosen et al., 2011; Tefft, 2013). In a 2013 study by Matsui et al., authors demonstrated that an impact speed of less than 30 km/h resulted in serious injury in less than 27% of collisions with pedestrians and fatalities in less than 5% (Matsui et al., 2013a,b). In addition to factors related to impact, vehicle type has also been shown to influence injury severity. The risk of pedestrian fatality for example, is greater in collisions involving vans or sport utility vehicles (SUVs) compared with passenger vehicles (Desapriya et al., 2010; Lefler and Gabler, 2004). Meanwhile, vehicle safety features such as passenger detection systems
S. Decker et al. / Accident Analysis and Prevention 94 (2016) 46–51
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Fig. 1. Collision location type, frequency given vulnerable road users.
including automatic braking strongly influence pedestrian safety. (Matsui et al., 2013a,b). Like pedestrians, bicyclists as well as motorcyclists are vulnerable road users with high risk of severe injury following collisions with vehicles. In a study by Räsänen and Summala, of 188 motor vehicle collisions involving bicyclists, 21 were seriously injured while an additional 13 resulted in fatality. Similar to previous studies involving collisions with pedestrians, lack of attention was attributed to the majority of these collisions with cyclists (Rasanen and Summala, 1998). Furthermore, complementary studies assessing risk of severe injury within this cohort have predictably demonstrated a positive correlation between impact speed and injury severity. (Stone and Broughton 2003; Haleem et al., 2015). When comparing a speed of 80 km/h to 32 km/h for example, risk of death increases 16 times amongst bicyclists involved in collisions with motor vehicles. Due to a wide range in collision variables and circumstances, numerous studies have investigated injury severity amongst pedestrians, bicyclists and motorcyclists however few studies analyze injury severity attributed to collisions with reversing vehicles. In a 2001 retrospective analysis by Mayr et al., authors identified 32 children whom were hit by reversing cars. This analysis demonstrated that the most common injuries included contusions of the head, face or extremities (n = 12) and long bone fractures (n = 7). Of note, authors even found two children suffering from pelvic fractures. While this study illustrates the potential for serious injuries resulting from collisions with reversing cars, the study cohort was limited to those patients admitted to the department of pediatric surgery and therefore prevents the extrapolation of these findings to the general population. (Mayr et al., 2001) With a better understanding of injury patterns resulting from collisions with reversing vehicles and their severity, clinicians including rescue workers and emergency department personnel will be better prepared to quickly triage patients without underestimation of injuries, ultimately improving care (Davidson et al., 2014; Mckay, 2005; Stefanopoulos et al., 2003). Previous studies have demonstrated patterns of injury and severity amongst this vulnerable cohort, including pedestrians, bicyclists and motorcyclists, however no studies to our knowledge examine these adult patients in the setting of collisions with reversing vehicles. In a retrospective analysis of a prospectively maintained database, the goals of this study were therefore to 1) examine the incidence of reversing motor vehicle crashes involv-
ing pedestrians, bicyclists and motorcyclists and 2) examine the patterns and severity of those collisions. 2. Material and Methods Our local accident research unit prospectively maintains the German In-Depth Accident Study (GIDAS) registry including technical investigations of motor vehicle collisions combined with medical data relevant to crash victims. The registry includes a cohort collected from both urban and suburban communities and is representative of national motor vehicle collision statistics in Germany. GIDAS was established in 1999 for the detailed analysis of crashes in Germany (Otte et al., 2012) and is supported by BASt (Bundesanstalt für Straßenwesen) and FAT (Forschungsvereinigung für Automobiltechnik). The accident research unit is staffed with personnel highly trained to investigate and document circumstances of automobile crashes. These staff members are notified by police radio immediately after a crash and arrive at the scene with or shortly after police and rescue personnel. Details of the collision are collected at the scene (including measurements by photography, stereo photography, three dimensional-laser technique, etc.), as well as clinical information regarding those involved. Clinical information is additionally collected at the treating hospital including demographic data, x-ray examination, injury type and severity. (Brand et al., 2012; Richter et al., 2007). Of note, patients are not followed beyond admission or thereafter. Impact speed is reconstructed using the software PC-Crash (MEA Forensic). A retrospective query of the GIDAS database was performed for collisions involving reversing cars as well as pedestrians, bicyclists or motorcyclists. All crashes that did not involve pedestrians, bicyclists or motorcyclists were excluded from this study. Injury severity was documented using the abbreviated injury scale 2005 (AIS) (Haasper et al., 2010). Briefly, AIS is a scoring system that classifies injury severity according to body region (i.e. head, abdomen, upper and lower extremities, etc.) and involved structures. Severity ranges from 1 to 6 including minor, moderate, serious, severe, critical and fatal respectively with a score of 9 describing an injury for which insufficient information is available. For standardization, detailed lists are available which classify severity for various injuries. A femur fracture for example, is an AIS 3 according to AIS 2005. In addition to the documentation of AIS, the maximum abbreviated injury scale (MAIS) was determined as well.
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MAIS is derived from AIS and represents the highest AIS identified amongst all body regions. The MAIS also ranges from 1 to 6. Like Räsänen and Summala as well as Lefler and Gabler, serious injuries are defined as those with AIS 3–5 (Rasanen and Summala, 1998). In addition to AIS, the following parameters were documented: crash location, type of vehicle, estimated impact speed, the nonpassenger involved as well as his or her age. The study was approved by the local ethical committee and follows the ethical standards of the Helsinki Declaration of 1975, as revised in 1983. 2.1. Statistical analysis Statistical analysis was performed using SPSS 22 for Windows (IBM). Correlations were determined using the spearmancoefficient rho. Means, medians and frequencies were analyzed. p-values of ≤0.05 were considered significant. 3. Results Of 25,822 crashes documented between 1999 and 2012, 315 involved reversing cars of which 234 involved pedestrians (n = 141, 60.3%), bicyclists (n = 70, 29.9%) or motorcyclists (n = 23, 9.8%). The mean age of the vulnerable road users was 57 ± 23 (<1–94) years. Injuries occurred on straight streets with drivers reversing for various reasons (n = 81; 34.6%), in parking areas (n = 59; 25.2%), driveways (n = 36; 15.4%), crossroads (n = 24; 10.3%) and t-junctions (n = 23; 9.8%). Eight locations were unclassified (3.4%). Details of crash location are summarized in Fig. 1. The vast majority of crashes occurred in urban areas accounting for 98.6% of crashes with motorcyclists, 98.6% of crashes with bicyclists and 100% of crashes with pedestrians. 204 (87.2%) collisions occurred during the day, 19 (8.1%) at night and 11 (4.7%) at twilight. The zone of impact was identified as follows: rear center (35%), rear left (26%), rear right (20%), side back (11%), side center (4%) and side front (3%) (see Fig. 2). The zone of impact could not be determined in 3 cases (1%). A detailed description of the zone of impact is presented in Fig. 3. Frequencies of MAIS levels are presented in Fig. 4, with MAIS 0, 1, 2, 3, 5 and 9 being documented in 1, 164, 46, 14, 1, and 8 patients, respectively. MAIS was found to correlate significantly positive with age (rho: 0.247; p < 0.001). In patients aged 65 years and older (n = 105), MAIS 3 ≤ was found 8×, versus 6× in patients being younger than 65 years (n = 129). The impact zone “side center” corresponded to the highest median MAIS (2 vs. 1 for all other impact zones). The lower extremities suffered the most injuries (64.1% of collisions) followed by the upper extremities (41.5% of collisions). The lower extremities also suffered serious injuries most often, with AIS ≥ 3, occurring in 4.3% of collisions. Injury to the head resulted in an AIS ≥ 3 in 4 (1.7%) collisions and in 1 (0.4%) event was severe (AIS 4). Injury severity did not differ between children, adolescents and adults. Detailed information of AIS is presented in Table 1. Pedestrians were seriously injured (AIS 3–6) in 9.1% of cases while 9.6% of motorcyclists suffered injuries classified AIS 3–4. In contrast no bicyclist suffered serious injuries. MAIS scores were greatest amongst pedestrians. Impact speed was documented in 222 cases. It was similar in crashes involving pedestrians, bicyclists and motorcyclists being as high as 7.0 ± 3.6, 7.0 ± 4.0 and 7.9 ± 4.2 km/h respectively with a mean value of 7.1 ± 3.8 km/h. Differential speed was significantly correlated with the MAIS (rho = 0.162; p = 0.015). Table 2 presents
Fig. 2. Schematic description of impact zone: frequency of collisions by impact zone.
the impact speed of the vehicle and corresponding MAIS score of the vulnerable road users. A positive correlation between MAIS level and impact speed was only found in pedestrians (rho = 0.376; p ≤ 0.001). Fig. 5 demonstrates the relation of speed and risk to become injured in pedestrians. 4. Discussion The ability to predict injury severity following specific crashes is important to a) appropriately triage patients at the site of collision as well as the hospital and b) to improve prevention measures. The focus of this study included injury severity of pedestrians, bicyclists and motorcyclists after collisions with reversing cars. Pedestrians and motorcyclists were at greatest risk for severe injuries. This study also demonstrates that the lower extremities are at greatest risk of serious injury followed by the upper extremities. These findings were not unforeseen given evidence
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Fig. 3. Impact zone given injured participant.
Fig. 4. MAIS given involved vulnerable road users. Table 1 AIS for all non-passengers involved. AIS
head
thorax
pelvis
legs
arms
abdomen
neck
0 1 2 3 4 5 6 9
147 (62.8%) 58 (24.8%) 20 (8.5%) 3 (1.3%) 1 (0.4%) 0 (0.0%) 0 (0.0%) 5 (2.1%)
171 (73.1%) 48 (20.5%) 11 (4.7%) 1 (0.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (1.3%)
195 (83.3%) 31 (13.2%) 5 (2.1%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (1.3%)
81 (34.6%) 128 (54.7%) 12 (5.1%) 10 (4.3%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (1.3%)
134 (57.3%) 81 (34.6%) 15 (6.4%) 1 (0.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (1.3%)
223 (95.3%) 5 (2.1%) 1 (0.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 5 (2.1%)
216 (92.3%) 15 (6.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (1.3%)
Table 2 MAIS score and impact speed. impact speed (km/h)
0–5 6–10 11–15 ≥16
pedestrian
bicyclist
motorcyclist
MAIS 1
MAIS 2+
MAIS 1
MAIS 2+
MAIS 1
MAIS 2+
81.2% 61.7% 35.7% –
18.8% 38.3% 64.3% 100%
80.0% 84.6% 87.5% 100%
20.0% 15.4% 12.5% –
71.4% 81.8% 100% –
28.6% 18.2% – 100%
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Fig. 5. Logistic regression model of speed and the risk to become injured in pedestrians.
from studies involving cars moving in the forward direction. Several studies agree that in collisions involving pedestrians or cyclists, the lower extremities are at high risk of injury, and that most fatalities occur secondary to severe head injury (Schmucker et al., 2010). Complementary studies of collisions with forward facing velocities less than 20 km/h demonstrate that pedestrians’ lower extremities are at increased risk of injury compared to the chest and the head, and result in low severity. (Watanabe et al., 2012; Lefler and Gabler, 2004). One study investigating velocities exceeding 20 km/h in an urban area demonstrated a mean lower extremity AIS of ∼2 for pedestrians illustrating still a moderate severity at greater speed. (Schmucker et al., 2010). The lower extremities are especially exposed to the bumper and primarily suffer from direct contact in low speed collisions such as those encountered with reversing cars. In contrast, one might infer from the data presented that injuries to the head primarily occur secondary to impact with the ground rather than with the colliding vehicle. Within this series of patients nearly 65% of patients sustained injury to the lower extremities while 35% sustained some injury to the head. It should also be noted that though injury to the lower and upper extremities occurred more frequently compared to those to the head, nearly 5% of head injuries were serious. Despite this observation only a single case of severe head injury was documented in this series of patients, suggesting that the risk of life-threatening injuries is likely low in this setting. Injury to the upper extremities occurred second most frequently which these authors ascribe to protective posturing prior the collision or impact with the ground. Similar to previous investigations that demonstrate the correlation between impact speed and injury severity (Rosen et al., 2011; Tefft, 2013), this study found that at least in pedestrians speed did correlate with the risk of injury (s. Fig. 5). Moreover our data support conclusions made by Matsui et al. who stated that the risk of serious injury or fatality is comparably low in collisions with impact speeds less than 30 km/h (Matsui et al., 2013a,b). In agreement with previous studies that demonstrate that the elderly are at greater risk of serious injuries (Siram et al., 2011), this study found a positive correlation between age and MAIS. This increased risk can be easily attributed to poor bone quality, poor balance and slower reaction time. Increasingly within urban regions, motorcyclists and bicyclists are at significant risk of injury in road traffic accidents. (Bil et al., 2010; Cunningham et al., 2012). Whereas the present study illustrates the highest AIS scores amongst pedestrians and motorcyclists, bicyclists overwhelmingly presented with minor trauma
without a single case of serious injury. This finding is in conflict with previously published data which suggest that bicyclists are at significant risk of serious injuries including death (Nicaj et al., 2009). While previous studies do not include collisions with reversing cars, authors concede that these findings are particularly curious as differential velocities were similar in all cases, and bicyclists, similar to motorcyclists, present in the sitting position with a common physical relationship to the vehicle. Altogether this study demonstrates that pedestrians, bicyclists and motorcyclists are at risk of serious injury following collisions with reversing vehicles therefore prevention measures are of great importance. The present study demonstrates that the vast majority of collisions occur at the rear of the vehicle compared to side, suggesting perhaps a feasible target for future safety innovations. Active safety systems for the technical support of drivers have already been introduced, however functional benefits resulting in fewer collisions have yet to be illustrated (Matsui et al., 2013a,b; Habibovic and Davidsson, 2012). These available technologies include backup cameras, automatic breaking as well as features like side view assistance which alarms the driver of approaching objects in a blindspot. Despite these technological advances in improved driver support, special awareness of pedestrians, bicyclists and motorcyclists remains crucial in prevention. (Rasanen and Summala 1998; Haleem et al., 2015). There were some notable limitations to our study. Although we report data from a prospectively collected database, the study itself was performed retrospectively. Additionally, impact speed was estimated using the vehicles speed, without consideration for the speed of the bicyclist or motorcyclist, potentially confounding the true impact speed and its influence on injury severity. Moreover, GIDAS data are collected from two areas in Germany with the inclusion of collisions occurring all days of the week as well as all times of the day. Nevertheless, the extrapolation of these findings to different countries may be difficult due to differences in traffic systems and safety features. And finally, the GIDAS database includes only those collisions that resulted in police notification, therefore there are an unknown number of minor crashes which may have occurred without any injuries. 5. Conclusion Collisions involving reversing cars and pedestrians, motorcyclists or bicyclists are especially relevant in urban areas. This is the first study that analyzes injury severity amongst these vulnerable road users after collisions with reversing vehicles. The majority of
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collisions occur at low impact speed during the day. Most injuries resulting from these collisions are not severe, however pedestrians are at greatest risk of serious injury to any body region. The lower extremities are injured most often amongst all non-passengers and suffer the most serious injuries of all body regions. While authors consider awareness to be most important to prevent injuries, technological advancements such as passenger detection systems and automatic braking may reduce the incidence of these injuries in future. Conflict of interest Authors declare, that they do not have any conflict of interest. Acknowledgements Crash data from the German In-Depth Accident Study (GIDAS) were used. GIDAS is supported by the Federal Highway Research Institute (BASt) and the German Research Association for Automotive Technology, a department of the VDA (German Association of the Automotive Industry). This study was supported by the Working Group Injury Prevention of the German Trauma Society (DGU). References Bil, M., Bilova, M., Muller, I., 2010. Critical factors in fatal collisions of adult cyclists with automobiles. Accid. Anal. Prev. 42 (6), 1632–1636. Brand, S., Otte, D., Mueller, C.W., Petri, M., Haas, P., Stuebig, T., Krettek, C., Haasper, C., 2012. Injury patterns of seniors in traffic accidents: a technical and medical analysis. World J. Orthoped. 3 (9), 151–155. Cunningham, G., Chenik, D., Zellweger, R., 2012. Factors influencing motorcycle crash victim outcomes: a prospective study. ANZ J. Surg. 82 (7–8), 551–554. Davidson, G.H., Rivara, F.P., Mack, C.D., Kaufman, R., Jurkovich, G.J., Bulger, E.M., 2014. Validation of prehospital trauma triage criteria for motor vehicle collisions. J. Trauma Acute Care Surg. 76 (3), 755–761. Desapriya, E., Subzwari, S., Sasges, D., Basic, A., Alidina, A., Turcotte, K., Pike, I., 2010. Do light truck vehicles (LTV) impose greater risk of pedestrian injury than passenger cars? A meta-analysis and systematic review. Traffic Inj. Prev. 11 (1), 48–56. Haasper, C., Junge, M., Ernstberger, A., Brehme, H., Hannawald, L., Langer, C., Nehmzow, J., Otte, D., Sander, U., Krettek, C., Zwipp, H., 2010. The abbreviated injury scale (AIS): options and problems in application. Der Unfallchirurg 113 (5), 366–372.
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Habibovic, A., Davidsson, J., 2012. Causation mechanisms in car-to-vulnerable road user crashes: implications for active safety systems. Accid. Anal. Prev. 49, 493–500. Haleem, K., Alluri, P., Gan, A., 2015. Analyzing pedestrian crash injury severity at signalized and non-signalized locations. Accid. Anal. Prev. 81, 14–23. Lefler, D.E., Gabler, H.C., 2004. The fatality and injury risk of light truck impacts with pedestrians in the United States. Accid. Anal. Prev. 36 (2), 295–304. Matsui, Y., Hitosugi, M., Takahashi, K., Doi, T., 2013a. Situations of car-to-pedestrian contact. Traffic Inj. Prev. 14 (1), 73–77. Matsui, Y., Oikawa, S., Ando, K., 2013b. Risks of pedestrian serious injuries and fatalities associated with impact velocities of cars in car-versus-pedestrian accidents in Japan. Stapp Car Crash J. 57, 201–217. Mayr, J.M., Eder, C., Wernig, J., Zebedin, D., Berghold, A., Corkum, S.H., 2001. Vehicles reversing or rolling backwards: an underestimated hazard. Inj. Prev. 7 (4), 327–328. Mckay, M.P., 2005. Can the car tell us who needs the trauma team after a motor vehicle crash? Ann. Emerg. Med. 45 (1), 51–52. Nicaj, L., Stayton, C., Mandel-Ricci, J., Mccarthy, P., Grasso, K., Woloch, D., Kerker, B., 2009. Bicyclist fatalities in New York City: 1996–2005. Traffic Inj. Prev. 10 (2), 157–161. Otte, D., Jansch, M., Haasper, C., 2012. Injury protection and accident causation parameters for vulnerable road users based on German In-Depth Accident Study GIDAS. Accid. Anal. Prev. 44 (1), 149–153. Rasanen, M., Summala, H., 1998. Attention and expectation problems in bicycle-car collisions: an in-depth study. Accid. Anal. Prev. 30 (5), 657–666. Richter, M., Otte, D., Haasper, C., Knobloch, K., Probst, C., Westhoff, J., Sommer, K., Krettek, C., 2007. The current injury situation of bicyclists–a medical and technical crash analysis. J. Trauma 62 (5), 1118–1122. Rosen, E., Stigson, H., Sander, U., 2011. Literature review of pedestrian fatality risk as a function of car impact speed. Accid. Anal. Prev. 43 (1), 25–33. Schmucker, U., Beirau, M., Frank, M., Stengel, D., Matthes, G., Ekkernkamp, A., Seifert, J., 2010. Real-world car-to-pedestrian-crash data from an urban centre. J. Trauma Manage. Outcomes 4 (1) (2-2897-4-2). Siram, S.M., Sonaike, V., Bolorunduro, O.B., Greene, W.R., Gerald, S.Z., Chang, D.C., Cornwell, E.E., Oyetunji, 3rd, 2011. Does the pattern of injury in elderly pedestrian trauma mirror that of the younger pedestrian? J. Surg. Res. 167 (1), 14–18. Stefanopoulos, N., Vagianos, C., Stavropoulos, M., Panagiotopoulos, E., Androulakis, J., 2003. Deformations and intrusions of the passenger compartment as indicators of injury severity and triage in head-on collisions of non-airbag-carrying vehicles. Injury 34 (7), 487–492. Stone, M., Broughton, J., 2003. Getting off your bike: cycling accidents in Great Britain in 1990–1999. Accid. Anal. Prev. 35 (4), 549–556. Tefft, B.C., 2013. Impact speed and a pedestrian’s risk of severe injury or death. Accid. Anal. Prev. 50, 871–878. Watanabe, R., Katsuhara, T., Miyazaki, H., Kitagawa, Y., Yasuki, T., 2012. Research of the relationship of pedestrian injury to collision speed, car-type: impact location and pedestrian sizes using human FE model (THUMS Version 4). Stapp Car Crash J. 56, 269–321.
Contents lists available at ScienceDirect
Accident Analysis and Prevention journal homepage: www.elsevier.com/locate/aap
Injury severity of pedestrians, bicyclists and motorcyclists resulting from crashes with reversing cars Sebastian Decker a,∗ , Dietmar Otte b , Dana Leslie Cruz a , Christian Walter Müller a , Mohamed Omar a , Christian Krettek a , Stephan Brand a a b
Trauma Department, Hannover Medical School, Carl-Neuberg-Str. 1, 30625 Hannover, Germany Accident Research Unit, Hannover Medical School, Karl-Wiechert-Allee 3, 30625 Hannover, Germany
a r t i c l e
i n f o
Article history: Received 9 November 2015 Received in revised form 4 May 2016 Accepted 12 May 2016 Keywords: Collision Reversing AIS MAIS Injury severity Road traffic accident (RTA)
a b s t r a c t Objective: Pedestrians, bicyclists and motorcyclists can suffer serious injury in road traffic crashes. To date, no studies examine the injury severity within this vulnerable cohort following collisions with reversing cars. Material and methods: Our institution prospectively maintains a database including medical and technical information regarding traffic accidents in our area, including urban and suburban regions. In a retrospective review of this database, the authors describe the injury severity of pedestrians, bicyclists and motorcyclists following traffic crashes involving reversing cars. Injury severity was described using the abbreviated injury scale (AIS) as well as the maximum abbreviated injury scale (MAIS). Results: This study included 234 crashes occurring between 1999 and 2012. The lower extremity was injured most often while also suffering more severe injuries with a median AIS of 1 compared to 0 in all other documented body regions. The upper extremity was injured second most often. AIS ranging from 4 to 6 were infrequent. AIS 3 however, was documented for the legs in 4.3% of patients. MAIS 0, 1, 2, 3, 5 and 9 were found in 1, 164, 46, 14, 1, and 8 patients in the study cohort, respectively. Pedestrians and motorcyclists were seriously injured in 9.1% and 9.6% of cases, respectively. In contrast, no bicyclists suffered serious injuries. As to the zone of impact, most collisions occurred at the rear center of the vehicle (35%) followed by rear left (26%), rear right (20%), side rear (11%), side center (4%) and side front (3%). 204 (87.2%) collisions occurred during the day, 19 (8.1%) at night and 11 (4.7%) at twilight. Speed was similar in crashes involving pedestrians, bicyclists and motorcyclists, being as high as 7.0 ± 3.6, 7.0 ± 4.0 and 7.9 ± 4.2 km/h respectively. Conclusions: This is the first study that analyzes injury severity among these vulnerable road users following collisions with reversing vehicles. The majority of collisions occur at low impact speed during the day. Most injuries resulting from these collisions are not serious, however pedestrians are at greatest risk of severe injury to any body region. The lower extremities suffer the most serious and frequent injuries within this cohort. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction Numerous factors influence the injury severity attributed to motor vehicle crashes including those involving non-passengers. Previous studies involving pedestrians struck by vehicles for
∗ Corresponding author. E-mail addresses: [email protected] (S. Decker), [email protected] (D. Otte), [email protected] (D.L. Cruz), [email protected] (C.W. Müller), [email protected] (M. Omar), [email protected] (C. Krettek), [email protected] (S. Brand). http://dx.doi.org/10.1016/j.aap.2016.05.010 0001-4575/© 2016 Elsevier Ltd. All rights reserved.
example have demonstrated an association between high-energy collisions and risk of death as well as the correlation between impact speed and injury severity. (Rosen et al., 2011; Tefft, 2013). In a 2013 study by Matsui et al., authors demonstrated that an impact speed of less than 30 km/h resulted in serious injury in less than 27% of collisions with pedestrians and fatalities in less than 5% (Matsui et al., 2013a,b). In addition to factors related to impact, vehicle type has also been shown to influence injury severity. The risk of pedestrian fatality for example, is greater in collisions involving vans or sport utility vehicles (SUVs) compared with passenger vehicles (Desapriya et al., 2010; Lefler and Gabler, 2004). Meanwhile, vehicle safety features such as passenger detection systems
S. Decker et al. / Accident Analysis and Prevention 94 (2016) 46–51
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Fig. 1. Collision location type, frequency given vulnerable road users.
including automatic braking strongly influence pedestrian safety. (Matsui et al., 2013a,b). Like pedestrians, bicyclists as well as motorcyclists are vulnerable road users with high risk of severe injury following collisions with vehicles. In a study by Räsänen and Summala, of 188 motor vehicle collisions involving bicyclists, 21 were seriously injured while an additional 13 resulted in fatality. Similar to previous studies involving collisions with pedestrians, lack of attention was attributed to the majority of these collisions with cyclists (Rasanen and Summala, 1998). Furthermore, complementary studies assessing risk of severe injury within this cohort have predictably demonstrated a positive correlation between impact speed and injury severity. (Stone and Broughton 2003; Haleem et al., 2015). When comparing a speed of 80 km/h to 32 km/h for example, risk of death increases 16 times amongst bicyclists involved in collisions with motor vehicles. Due to a wide range in collision variables and circumstances, numerous studies have investigated injury severity amongst pedestrians, bicyclists and motorcyclists however few studies analyze injury severity attributed to collisions with reversing vehicles. In a 2001 retrospective analysis by Mayr et al., authors identified 32 children whom were hit by reversing cars. This analysis demonstrated that the most common injuries included contusions of the head, face or extremities (n = 12) and long bone fractures (n = 7). Of note, authors even found two children suffering from pelvic fractures. While this study illustrates the potential for serious injuries resulting from collisions with reversing cars, the study cohort was limited to those patients admitted to the department of pediatric surgery and therefore prevents the extrapolation of these findings to the general population. (Mayr et al., 2001) With a better understanding of injury patterns resulting from collisions with reversing vehicles and their severity, clinicians including rescue workers and emergency department personnel will be better prepared to quickly triage patients without underestimation of injuries, ultimately improving care (Davidson et al., 2014; Mckay, 2005; Stefanopoulos et al., 2003). Previous studies have demonstrated patterns of injury and severity amongst this vulnerable cohort, including pedestrians, bicyclists and motorcyclists, however no studies to our knowledge examine these adult patients in the setting of collisions with reversing vehicles. In a retrospective analysis of a prospectively maintained database, the goals of this study were therefore to 1) examine the incidence of reversing motor vehicle crashes involv-
ing pedestrians, bicyclists and motorcyclists and 2) examine the patterns and severity of those collisions. 2. Material and Methods Our local accident research unit prospectively maintains the German In-Depth Accident Study (GIDAS) registry including technical investigations of motor vehicle collisions combined with medical data relevant to crash victims. The registry includes a cohort collected from both urban and suburban communities and is representative of national motor vehicle collision statistics in Germany. GIDAS was established in 1999 for the detailed analysis of crashes in Germany (Otte et al., 2012) and is supported by BASt (Bundesanstalt für Straßenwesen) and FAT (Forschungsvereinigung für Automobiltechnik). The accident research unit is staffed with personnel highly trained to investigate and document circumstances of automobile crashes. These staff members are notified by police radio immediately after a crash and arrive at the scene with or shortly after police and rescue personnel. Details of the collision are collected at the scene (including measurements by photography, stereo photography, three dimensional-laser technique, etc.), as well as clinical information regarding those involved. Clinical information is additionally collected at the treating hospital including demographic data, x-ray examination, injury type and severity. (Brand et al., 2012; Richter et al., 2007). Of note, patients are not followed beyond admission or thereafter. Impact speed is reconstructed using the software PC-Crash (MEA Forensic). A retrospective query of the GIDAS database was performed for collisions involving reversing cars as well as pedestrians, bicyclists or motorcyclists. All crashes that did not involve pedestrians, bicyclists or motorcyclists were excluded from this study. Injury severity was documented using the abbreviated injury scale 2005 (AIS) (Haasper et al., 2010). Briefly, AIS is a scoring system that classifies injury severity according to body region (i.e. head, abdomen, upper and lower extremities, etc.) and involved structures. Severity ranges from 1 to 6 including minor, moderate, serious, severe, critical and fatal respectively with a score of 9 describing an injury for which insufficient information is available. For standardization, detailed lists are available which classify severity for various injuries. A femur fracture for example, is an AIS 3 according to AIS 2005. In addition to the documentation of AIS, the maximum abbreviated injury scale (MAIS) was determined as well.
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MAIS is derived from AIS and represents the highest AIS identified amongst all body regions. The MAIS also ranges from 1 to 6. Like Räsänen and Summala as well as Lefler and Gabler, serious injuries are defined as those with AIS 3–5 (Rasanen and Summala, 1998). In addition to AIS, the following parameters were documented: crash location, type of vehicle, estimated impact speed, the nonpassenger involved as well as his or her age. The study was approved by the local ethical committee and follows the ethical standards of the Helsinki Declaration of 1975, as revised in 1983. 2.1. Statistical analysis Statistical analysis was performed using SPSS 22 for Windows (IBM). Correlations were determined using the spearmancoefficient rho. Means, medians and frequencies were analyzed. p-values of ≤0.05 were considered significant. 3. Results Of 25,822 crashes documented between 1999 and 2012, 315 involved reversing cars of which 234 involved pedestrians (n = 141, 60.3%), bicyclists (n = 70, 29.9%) or motorcyclists (n = 23, 9.8%). The mean age of the vulnerable road users was 57 ± 23 (<1–94) years. Injuries occurred on straight streets with drivers reversing for various reasons (n = 81; 34.6%), in parking areas (n = 59; 25.2%), driveways (n = 36; 15.4%), crossroads (n = 24; 10.3%) and t-junctions (n = 23; 9.8%). Eight locations were unclassified (3.4%). Details of crash location are summarized in Fig. 1. The vast majority of crashes occurred in urban areas accounting for 98.6% of crashes with motorcyclists, 98.6% of crashes with bicyclists and 100% of crashes with pedestrians. 204 (87.2%) collisions occurred during the day, 19 (8.1%) at night and 11 (4.7%) at twilight. The zone of impact was identified as follows: rear center (35%), rear left (26%), rear right (20%), side back (11%), side center (4%) and side front (3%) (see Fig. 2). The zone of impact could not be determined in 3 cases (1%). A detailed description of the zone of impact is presented in Fig. 3. Frequencies of MAIS levels are presented in Fig. 4, with MAIS 0, 1, 2, 3, 5 and 9 being documented in 1, 164, 46, 14, 1, and 8 patients, respectively. MAIS was found to correlate significantly positive with age (rho: 0.247; p < 0.001). In patients aged 65 years and older (n = 105), MAIS 3 ≤ was found 8×, versus 6× in patients being younger than 65 years (n = 129). The impact zone “side center” corresponded to the highest median MAIS (2 vs. 1 for all other impact zones). The lower extremities suffered the most injuries (64.1% of collisions) followed by the upper extremities (41.5% of collisions). The lower extremities also suffered serious injuries most often, with AIS ≥ 3, occurring in 4.3% of collisions. Injury to the head resulted in an AIS ≥ 3 in 4 (1.7%) collisions and in 1 (0.4%) event was severe (AIS 4). Injury severity did not differ between children, adolescents and adults. Detailed information of AIS is presented in Table 1. Pedestrians were seriously injured (AIS 3–6) in 9.1% of cases while 9.6% of motorcyclists suffered injuries classified AIS 3–4. In contrast no bicyclist suffered serious injuries. MAIS scores were greatest amongst pedestrians. Impact speed was documented in 222 cases. It was similar in crashes involving pedestrians, bicyclists and motorcyclists being as high as 7.0 ± 3.6, 7.0 ± 4.0 and 7.9 ± 4.2 km/h respectively with a mean value of 7.1 ± 3.8 km/h. Differential speed was significantly correlated with the MAIS (rho = 0.162; p = 0.015). Table 2 presents
Fig. 2. Schematic description of impact zone: frequency of collisions by impact zone.
the impact speed of the vehicle and corresponding MAIS score of the vulnerable road users. A positive correlation between MAIS level and impact speed was only found in pedestrians (rho = 0.376; p ≤ 0.001). Fig. 5 demonstrates the relation of speed and risk to become injured in pedestrians. 4. Discussion The ability to predict injury severity following specific crashes is important to a) appropriately triage patients at the site of collision as well as the hospital and b) to improve prevention measures. The focus of this study included injury severity of pedestrians, bicyclists and motorcyclists after collisions with reversing cars. Pedestrians and motorcyclists were at greatest risk for severe injuries. This study also demonstrates that the lower extremities are at greatest risk of serious injury followed by the upper extremities. These findings were not unforeseen given evidence
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Fig. 3. Impact zone given injured participant.
Fig. 4. MAIS given involved vulnerable road users. Table 1 AIS for all non-passengers involved. AIS
head
thorax
pelvis
legs
arms
abdomen
neck
0 1 2 3 4 5 6 9
147 (62.8%) 58 (24.8%) 20 (8.5%) 3 (1.3%) 1 (0.4%) 0 (0.0%) 0 (0.0%) 5 (2.1%)
171 (73.1%) 48 (20.5%) 11 (4.7%) 1 (0.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (1.3%)
195 (83.3%) 31 (13.2%) 5 (2.1%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (1.3%)
81 (34.6%) 128 (54.7%) 12 (5.1%) 10 (4.3%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (1.3%)
134 (57.3%) 81 (34.6%) 15 (6.4%) 1 (0.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (1.3%)
223 (95.3%) 5 (2.1%) 1 (0.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 5 (2.1%)
216 (92.3%) 15 (6.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 3 (1.3%)
Table 2 MAIS score and impact speed. impact speed (km/h)
0–5 6–10 11–15 ≥16
pedestrian
bicyclist
motorcyclist
MAIS 1
MAIS 2+
MAIS 1
MAIS 2+
MAIS 1
MAIS 2+
81.2% 61.7% 35.7% –
18.8% 38.3% 64.3% 100%
80.0% 84.6% 87.5% 100%
20.0% 15.4% 12.5% –
71.4% 81.8% 100% –
28.6% 18.2% – 100%
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Fig. 5. Logistic regression model of speed and the risk to become injured in pedestrians.
from studies involving cars moving in the forward direction. Several studies agree that in collisions involving pedestrians or cyclists, the lower extremities are at high risk of injury, and that most fatalities occur secondary to severe head injury (Schmucker et al., 2010). Complementary studies of collisions with forward facing velocities less than 20 km/h demonstrate that pedestrians’ lower extremities are at increased risk of injury compared to the chest and the head, and result in low severity. (Watanabe et al., 2012; Lefler and Gabler, 2004). One study investigating velocities exceeding 20 km/h in an urban area demonstrated a mean lower extremity AIS of ∼2 for pedestrians illustrating still a moderate severity at greater speed. (Schmucker et al., 2010). The lower extremities are especially exposed to the bumper and primarily suffer from direct contact in low speed collisions such as those encountered with reversing cars. In contrast, one might infer from the data presented that injuries to the head primarily occur secondary to impact with the ground rather than with the colliding vehicle. Within this series of patients nearly 65% of patients sustained injury to the lower extremities while 35% sustained some injury to the head. It should also be noted that though injury to the lower and upper extremities occurred more frequently compared to those to the head, nearly 5% of head injuries were serious. Despite this observation only a single case of severe head injury was documented in this series of patients, suggesting that the risk of life-threatening injuries is likely low in this setting. Injury to the upper extremities occurred second most frequently which these authors ascribe to protective posturing prior the collision or impact with the ground. Similar to previous investigations that demonstrate the correlation between impact speed and injury severity (Rosen et al., 2011; Tefft, 2013), this study found that at least in pedestrians speed did correlate with the risk of injury (s. Fig. 5). Moreover our data support conclusions made by Matsui et al. who stated that the risk of serious injury or fatality is comparably low in collisions with impact speeds less than 30 km/h (Matsui et al., 2013a,b). In agreement with previous studies that demonstrate that the elderly are at greater risk of serious injuries (Siram et al., 2011), this study found a positive correlation between age and MAIS. This increased risk can be easily attributed to poor bone quality, poor balance and slower reaction time. Increasingly within urban regions, motorcyclists and bicyclists are at significant risk of injury in road traffic accidents. (Bil et al., 2010; Cunningham et al., 2012). Whereas the present study illustrates the highest AIS scores amongst pedestrians and motorcyclists, bicyclists overwhelmingly presented with minor trauma
without a single case of serious injury. This finding is in conflict with previously published data which suggest that bicyclists are at significant risk of serious injuries including death (Nicaj et al., 2009). While previous studies do not include collisions with reversing cars, authors concede that these findings are particularly curious as differential velocities were similar in all cases, and bicyclists, similar to motorcyclists, present in the sitting position with a common physical relationship to the vehicle. Altogether this study demonstrates that pedestrians, bicyclists and motorcyclists are at risk of serious injury following collisions with reversing vehicles therefore prevention measures are of great importance. The present study demonstrates that the vast majority of collisions occur at the rear of the vehicle compared to side, suggesting perhaps a feasible target for future safety innovations. Active safety systems for the technical support of drivers have already been introduced, however functional benefits resulting in fewer collisions have yet to be illustrated (Matsui et al., 2013a,b; Habibovic and Davidsson, 2012). These available technologies include backup cameras, automatic breaking as well as features like side view assistance which alarms the driver of approaching objects in a blindspot. Despite these technological advances in improved driver support, special awareness of pedestrians, bicyclists and motorcyclists remains crucial in prevention. (Rasanen and Summala 1998; Haleem et al., 2015). There were some notable limitations to our study. Although we report data from a prospectively collected database, the study itself was performed retrospectively. Additionally, impact speed was estimated using the vehicles speed, without consideration for the speed of the bicyclist or motorcyclist, potentially confounding the true impact speed and its influence on injury severity. Moreover, GIDAS data are collected from two areas in Germany with the inclusion of collisions occurring all days of the week as well as all times of the day. Nevertheless, the extrapolation of these findings to different countries may be difficult due to differences in traffic systems and safety features. And finally, the GIDAS database includes only those collisions that resulted in police notification, therefore there are an unknown number of minor crashes which may have occurred without any injuries. 5. Conclusion Collisions involving reversing cars and pedestrians, motorcyclists or bicyclists are especially relevant in urban areas. This is the first study that analyzes injury severity amongst these vulnerable road users after collisions with reversing vehicles. The majority of
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