Estimated injury risk for specific injuries and body regions in frontal motor vehicle crashes

Rib and sternum fracture risks for restrained occupants in frontal car crashes

OBJECTIVE

Most car occupant fatalities occur in frontal crashes and the thorax is the most frequently injured body region. The objectives of the study were, firstly, to quantify the relation between risk factors (such as speed and occupant age) and rib and sternum fracture injury probability in frontal car crashes, and, secondly, to evaluate whether rib fracture occurrence can predict sternum fractures.

METHODS

Weighted German data from 1999-2021 were used to create the injury risk curves to predict both, at least moderate and at least serious, rib and sternum fracture risks. A contingency table for rib and sternum fractures allowed the calculation of sensitivity, specificity, and precision, as well as testing for the association.

RESULTS

Elderly occupants (≥65 years old) had increased rib and sternum fracture risk compared to mid aged occupants (18-64 years old). Besides occupant age, delta-V was always and sex sometimes a significant predictor for skeletal thoracic injury. Sternum fractures were more common than rib fractures and more likely to occur at any given delta-V. Sternum fractures occurred often in isolation. Female occupants were at higher risk than males to sustain at least moderate rib and sternum fractures together and sternum fractures in isolation. Rib and sternum fractures were associated, but low sensitivity and precision show that rib fractures do not predict sternum fractures well.

CONCLUSIONS

Elderly and female occupants were at the highest risk and should be targeted by thoracic injury criteria and thresholds for frontal crash occupant protection. Rib and sternum fractures were not associated. Therefore, sternum fractures need to be predicted and evaluated separately from rib fractures.

Injury risk functions for the four primary knee ligaments

The purpose of this study was to develop injury risk functions (IRFs) for the anterior and posterior cruciate ligaments (ACL and PCL, respectively) and the medial and lateral collateral ligaments (MCL and LCL, respectively) in the knee joint. The IRFs were based on post-mortem human subjects (PMHSs). Available specimen-specific failure strains were supplemented with statistically generated failure strains (virtual values) to accommodate for unprovided detailed experimental data in the literature. The virtual values were derived from the reported mean and standard deviation in the experimental studies. All virtual and specimen-specific values were thereafter categorized into groups of static and dynamic rates, respectively, and tested for the best fitting theoretical distribution to derive a ligament-specific IRF. A total of 10 IRFs were derived (three for ACL, two for PCL, two for MCL, and three for LCL). ACL, MCL, and LCL received IRFs in both dynamic and static tensile rates, while a sufficient dataset was achieved only for dynamic rates of the PCL. The log-logistic and Weibull distributions had the best fit (p-values: >0.9, RMSE: 2.3%-4.7%) to the empirical datasets for all the ligaments. These IRFs are, to the best of the authors' knowledge, the first attempt to generate injury prediction tools based on PMHS data for the four knee ligaments. The study has summarized all the relevant literature on PHMS experimental tensile tests on the knee ligaments and utilized the available empirical data to create the IRFs. Future improvements require upcoming experiments to provide comparable testing and strain measurements. Furthermore, emphasis on a clear definition of failure and transparent reporting of each specimen-specific result is necessary.

Spinal injury rates and specific causation in motor vehicle collisions

Motor vehicle collisions (MVCs) are a leading cause of acute spinal injuries. Chronic spinal pathologies are common in the population. Thus, determining the incidence of different types of spinal injuries due to MVCs and understanding biomechanical mechanism of these injuries is important for distinguishing acute injuries from chronic degenerative disease. This paper describes methods for determining causation of spinal pathologies from MVCs based on rates of injury and analysis of the biomechanics require to produce these injuries. Rates of spinal injuries in MVCs were determined using two distinct methodologies and interpreted using a focused review of salient biomechanical literature. One methodology used incidence data from the Nationwide Emergency Department Sample and exposure data from the Crash Report Sample System supplemented with a telephone survey to estimate total national exposure to MVC. The other used incidence and exposure data from the Crash Investigation Sampling System. Linking the clinical and biomechanical findings yielded several conclusions. First, spinal injuries caused by an MVC are relatively rare (511 injured occupants per 10,000 exposed to an MVC), which is consistent with the biomechanical forces required to generate injury. Second, spinal injury rates increase as impact severity increases, and fractures are more common in higher-severity exposures. Third, the rate of sprain/strain in the cervical spine is greater than in the lumbar spine. Fourth, spinal disc injuries are extremely rare in MVCs (0.01 occupants per 10,000 exposed) and typically occur with concomitant trauma, which is consistent with the biomechanical findings 1) that disc herniations are fatigue injuries caused by cyclic loading, 2) the disc is almost never the first structure to be injured in impact loading unless it is highly flexed and compressed, and 3) that most crashes involve predominantly tensile loading in the spine, which does not cause isolated disc herniations. These biomechanical findings illustrate that determining causation when an MVC occupant presents with disc pathology must be based on the specifics of that presentation and the crash circumstances and, more broadly, that any causation determination must be informed by competent biomechanical analysis.

Mechanism of injury and special considerations as predictive of serious injury: A systematic review

OBJECTIVES

The Centers for Disease Control and Prevention's field triage guidelines (FTG) are routinely used by emergency medical services personnel for triaging injured patients. The most recent (2011) FTG contains physiologic, anatomic, mechanism, and special consideration steps. Our objective was to systematically review the criteria in the mechanism and special consideration steps that might be predictive of serious injury or need for a trauma center.

METHODS

We conducted a systematic review of the predictive utility of mechanism and special consideration criteria for predicting serious injury. A research librarian searched in Ovid Medline, EMBASE, and the Cochrane databases for studies published between January 2011 and February 2021. Eligible studies were identified using a priori inclusion and exclusion criteria. Studies were excluded if they lacked an outcome for serious injury, such as measures of resource use, injury severity scores, mortality, or composite measures using a combination of outcomes. Given the heterogeneity in populations, measures, and outcomes, results were synthesized qualitatively focusing on positive likelihood ratios (LR+) whenever these could be calculated from presented data or adjusted odds ratios (aOR).

RESULTS

We reviewed 2418 abstracts and 315 full-text publications and identified 42 relevant studies. The factors most predictive of serious injury across multiple studies were death in the same vehicle (LR+ 2.2-7.4), ejection (aOR 3.2-266.2), extrication (LR+ 1.1-6.6), lack of seat belt use (aOR 4.4-11.3), high speeds (aOR 2.0-2.9), concerning crash variables identified by vehicle telemetry systems (LR+ 4.7-22.2), falls from height (LR+ 2.4-5.9), and axial load or diving (aOR 2.5-17.6). Minor or inconsistent predictors of serious injury were vehicle intrusion (LR+ 0.8-7.2), cardiopulmonary or neurologic comorbidities (LR+ 0.8-3.1), older age (LR+ 0.6-6.8), or anticoagulant use (LR+ 1.1-1.8).

CONCLUSIONS

Select mechanism and special consideration criteria contribute positively to appropriate field triage of potentially injured patients.

Influence of a Passenger Position Seating on Recline Seat on a Head Injury during a Frontal Crash

Presently, most passive safety tests are performed with a precisely specified seat position and carefully seated ATD (anthropomorphic test device) dummies. Facing the development of autonomous vehicles, as well as the need for safety verification during crashes with various seat positions such research is even more urgently needed. Apart from the numerical environment, the existing testing equipment is not validated to perform such an investigation. For example, ATDs are not validated for nonstandard seatback positions, and the most accurate method of such research is volunteer tests. The study presented here was performed on a sled test rig utilizing a 50cc Hybrid III dummy according to a full factorial experiment. In addition, input factors were selected in order to verify a safe test condition for surrogate testing. The measured value was head acceleration, which was used for calculation of a head injury criterion. What was found was an optimal seat angle −117°—at which the head injury criteria had the lowest represented value. Moreover, preliminary body dynamics showed a danger of whiplash occurrence for occupants in a fully-reclined seat.

The relationship between road traffic collision dynamics and traumatic brain injury pathology

Road traffic collisions are a major cause of traumatic brain injury. However, the relationship between road traffic collision dynamics and traumatic brain injury risk for different road users is unknown. We investigated 2065 collisions from Great Britain’s Road Accident In-depth Studies collision database involving 5374 subjects (2013–20). Five hundred and ninety-five subjects sustained a traumatic brain injury (20.2% of 2940 casualties), including 315 moderate–severe and 133 mild–probable injuries. Key pathologies included skull fracture (179, 31.9%), subarachnoid haemorrhage (171, 30.5%), focal brain injury (168, 29.9%) and subdural haematoma (96, 17.1%). These results were extended nationally using >1 000 000 police-reported collision casualties. Extrapolating from the in-depth data we estimate that there are ∼20 000 traumatic brain injury casualties (∼5000 moderate–severe) annually on Great Britain’s roads, accounting for severity differences. Detailed collision investigation allows vehicle collision dynamics to be understood and the change in velocity (known as delta-V) to be estimated for a subset of in-depth collision data. Higher delta-V increased the risk of moderate–severe brain injury for all road users. The four key pathologies were not observed below 8 km/h delta-V for pedestrians/cyclists and 19 km/h delta-V for car occupants (higher delta-V threshold for focal injury in both groups). Traumatic brain injury risk depended on road user type, delta-V and impact direction. Accounting for delta-V, pedestrians/cyclists had a 6-times higher likelihood of moderate–severe brain injury than car occupants. Wearing a cycle helmet during a collision was protective against overall and mild-to-moderate-to-severe brain injury, particularly skull fracture and subdural haematoma. Cycle helmet protection was not due to travel or impact speed differences between helmeted and non-helmeted cyclist groups. We additionally examined the influence of the delta-V direction. Car occupants exposed to a higher lateral delta-V component had a greater prevalence of moderate–severe brain injury, particularly subarachnoid haemorrhage. Multivariate logistic regression models created using total delta-V value and whether lateral delta-V was dominant had the best prediction capabilities (area under the receiver operator curve as high as 0.95). Collision notification systems are routinely fitted in new cars. These record delta-V and automatically alert emergency services to a collision in real-time. These risk relationships could, therefore, inform how routinely fitted automatic collision notification systems alert the emergency services to collisions with a high brain injury risk. Early notification of high-risk scenarios would enable quicker activation of the highest level of emergency service response. Identifying those that require neurosurgical care and ensuring they are transported directly to a centre with neuro-specialist provisions could improve patient outcomes.

The Impact of Seatbelt Use on Trauma Outcomes in Adult Motor Vehicle Collision Patients With Rib Fractures: A National ACS-TQP-PUF Database Analysis

BACKGROUND

Motor vehicle collisions (MVCs) are a leading cause of morbidity and mortality. However, there is limited evidence examining the effects seatbelt use has on MVC-related injuries and outcomes in patients with rib fractures. We aim to assess how seatbelt use affects associated injuries and outcomes in adult MVC patients with ≥2 rib fractures.

METHODS

This retrospective study utilized the American College of Surgeons (ACS) Trauma Quality Programs (TQP) Participant Use File (PUF) Database. Drivers/passengers who sustained ≥2 rib fractures following an MVC and had an AIS ≤2 for extra-thoracic body regions were analyzed. Patients were then subdivided by presence of flail chest into two cohorts, which were subdivided according to injury severity score (ISS) and seatbelt use. Logistic and linear regression was used to assess the impact of seatbelt use on outcomes.

RESULTS

Among both low and intermediate ISS classifications, restrained patients in the non-flail chest cohort had decreased incidence of pneumothorax, pulmonary contusion, and liver injury (P < 0.001). After adjusting for confounders, restrained patients (versus unrestrained) had decreased odds of pneumothorax (aOR = 0.91, P = <0.001) and acute respiratory distress syndrome (aOR=0.65, P = 0.02), while having increased odds of splenic laceration (aOR = 1.18, P = 0.003) (intermediate ISS group). Compared to unrestrained patients, restrained non-flail chest patients had a significantly decreased hospital length of stay (LOS) and intensive care unit LOS (P < 0.05).

CONCLUSIONS

Seatbelt use may be protective against serious injuries in patients with ≥2 rib fractures, resulting in improved outcomes. Education programs should be developed to bolster seatbelt compliance.

Occupant-Based Injury Severity Prediction

Road traffic injuries continue to be a leading cause of death around the world. Rapid emergency response is a key factor in improving occupant outcomes. Over the past ten years, Injury Severity Prediction (ISP) models have been developed and deployed to assist in effective dispatch of emergency medical services (EMS). Prior versions of ISP have relied on driver-based scenarios that are not relevant in many of the possible autonomous vehicle (AV) contexts. This paper describes the development and validation of occupant-based ISP models that predict injury severity for specific vehicle seat positions. Models show improved predictive performance, sensitivity 80% and specificity over 95%, for front row occupants. Second row occupant models have similar specificity, but sensitivity scores dropped due to occupant heterogeneity and small sample sizes of seriously injured occupants.

The Association of Body Mass Index and Outcomes in Adult Patients with Chest Wall Injuries

BACKGROUND

Thoracic injury secondary to rib fractures following motor vehicle collisions (MVCs) significantly contribute to morbidity and mortality. While obesity has reached epidemic proportions, little is known regarding how BMI impacts outcomes in MVCs. The aim of this study was to examine how BMI impacts outcomes in MVC patients with rib fractures.

METHODS

The ACS-TQIP Database was utilized to evaluate adult MVC patients with ≥3 rib fractures. Patients with a non-thoracic AIS ≥3 were excluded, to focus on chest injuries. Patients were sorted according to the presence or absence of flail chest injuries and BMI into groups with a low (<15), intermediate (15-24), or severe (≥25) ISS.

RESULTS

Overweight and obese patients in the non-flail cohort had decreased odds of pneumothorax in all ISS groups (P < 0.05). Overweight (P = 0.049) and obese (P = 0.011) patients in the low ISS non-flail cohort had decreased odds of splenic laceration. In the non-flail cohort, obese patients with a low and intermediate ISS had decreased odds of pulmonary contusion (P < 0.01). Obese patients in the low and intermediate ISS non-flail cohorts had increased odds of PE (P < 0.05). In both the flail and non-flail cohorts, obese patients with an intermediate ISS had decreased odds of liver laceration (P < 0.05), as well as a longer HLOS, ICU-LOS, and mechanical ventilation time (P < 0.01).

CONCLUSION

Obesity affects associated injuries, complications, and hospital outcomes in a complex way after MVC related chest wall trauma. Thus, the effect of BMI should be taken into consideration when assessing and treating obese MVC trauma patients.

A comparison of rib cortical bone compressive and tensile material properties: Trends with age, sex, and loading rate

The objectives of this study were to develop novel methods for quantifying human rib cortical bone material properties in compression and to compare the compressive material property data to existing tensile data for matched subjects. Cylindrical coupons were obtained from the rib cortical bone of 30 subjects (M = 19, F = 11) ranging from 18 to 95 years of age (Avg. = 48.5 ± 24.3). Two coupons were obtained from each subject. One coupon was tested in compression at 0.005 strain/s, while the other coupon was tested in compression at 0.5 strain/s. Load and displacement data were recorded so that the elastic modulus, yield stress, yield strain, ultimate stress, ultimate strain, elastic strain energy density (SED), plastic SED, and total SED could be calculated. All compressive material properties were significantly different between the two loading rates. An ANOVA revealed that sex alone had no significant effect on the compressive material properties. The interaction between sex and age was significant for some material properties, but this may have been a consequence of the lack of older females in the subject pool. None of the compressive material properties were significantly correlated with age, but were more correlated with sample density. This finding differed for the tensile material properties, which showed stronger correlations with age. When comparing between tension and compression, significant differences were observed for all material properties except for the total SED, once the effects of loading rate and age had been accounted for. This was the first study to quantify the material properties of human rib cortical bone in compression. The results of this study demonstrated that rib and thorax finite element models should consider the effects of loading rate, loading mode, and age when incorporating material properties published in the literature.

Rib Cortical Bone Fracture Risk as a Function of Age and Rib Strain: Updated Injury Prediction Using Finite Element Human Body Models

To evaluate vehicle occupant injury risk, finite element human body models (HBMs) can be used in vehicle crash simulations. HBMs can predict tissue loading levels, and the risk for fracture can be estimated based on a tissue-based risk curve. A probabilistic framework utilizing an age-adjusted rib strain-based risk function was proposed in 2012. However, the risk function was based on tests from only twelve human subjects. Further, the age adjustment was based on previous literature postulating a 5.1% decrease in failure strain for femur bone material per decade of aging. The primary aim of this study was to develop a new strain-based rib fracture risk function using material test data spanning a wide range of ages. A second aim was to update the probabilistic framework with the new risk function and compare the probabilistic risk predictions from HBM simulations to both previous HBM probabilistic risk predictions and to approximate real-world rib fracture outcomes. Tensile test data of human rib cortical bone from 58 individuals spanning 17-99 years of ages was used. Survival analysis with accelerated failure time was used to model the failure strain and age-dependent decrease for the tissue-based risk function. Stochastic HBM simulations with varied impact conditions and restraint system settings were performed and probabilistic rib fracture risks were calculated. In the resulting fracture risk function, sex was not a significant covariate-but a stronger age-dependent decrease than previously assumed for human rib cortical bone was evident, corresponding to a 12% decrease in failure strain per decade of aging. The main effect of this difference is a lowered risk prediction for younger individuals than that predicted in previous risk functions. For the stochastic analysis, the previous risk curve overestimated the approximate real-world rib fracture risk for 30-year-old occupants; the new risk function reduces the overestimation. Moreover, the new function can be used as a direct replacement of the previous one within the 2012 probabilistic framework.

The Effects of Body Mass Index and Seatbelt Use on Pediatric Chest and Abdominal Injuries after Motor Vehicle Collisions

BACKGROUND

Motor vehicle collisions (MVCs) are a major cause of pediatric morbidity and mortality. However, the effect of body mass index (BMI) and seatbelt use on thoracic injuries and outcomes in pediatric patients with rib fractures remains unexplored. We aim to assess how seatbelt use and BMI affect thoracic injuries and outcomes in pediatric patients who sustained ≥3 rib fractures following an MVC.

METHODS

The Trauma Quality Improvement Program (TQIP) database (2013-2017) was queried for pediatric patients (8-17 years and >4 feet 9 inches tall) admitted secondary to MVCs, with ≥3 rib fractures and all non-thoracic Abbreviated Injury Scale ≤2. Patients were then divided by Injury Severity Score (ISS) into low (<15) and intermediate-severe (≥15) groups, which were further subdivided according to seatbelt use and BMI. Logistic and linear regression was performed to assess the effects of seatbelt use and BMI on outcomes.

RESULTS

Seatbelt compliance varied from 39.6 to 50.7%. Belted patients (intermediate-severe ISS) had a reduced hospital length of stay (HLOS), intensive care unit length of stay(ICU-LOS), and mechanical ventilation time but had increased odds of splenic laceration vs. unbelted patients (aOR = 2.46, 95% CI: 1.03-5.93, P = .044). Obese patients (low ISS) had lower incidences of hemothorax, pneumothorax, pulmonary contusion, splenic laceration, and liver injury compared to normal-weight patients. Overweight patients (intermediate-severe ISS) had a significantly reduced ICU-LOS vs. normal-weight patients (β = -.17, 95% CI: -.33,-.01, = .041).

CONCLUSIONS

Seatbelt use may improve outcomes for pediatric MVC patients with ≥3 rib fractures. Higher BMI may be associated with reduced thoracic injury and decreased ICU-LOS. Effective educational initiatives are needed to increase pediatric seatbelt compliance.

Emergency Response to Vehicle Collisions: Feedback from Emergency Medical Service Providers

(1) Background: The purpose of this study is to identify emergency medical technicians’ perceptions of the most pressing issues that they experience when responding to motor vehicle collisions and record their opinions about what information is needed to improve the efficiency and effectiveness of the care they provide. (2) Methods: Emergency medical technicians participated in one-on-one structured interviews about their experiences responding to motor vehicle collisions. Their feedback on dispatching procedures and protocols, travel to and from the scene, and the response process was collected. (3) Results: Participants reported experiencing difficulties related to lack of or inaccuracies in information, interactions with traffic, incompatibility in communication technology, scene safety, resource management, and obtaining timely notifications of motor vehicle collisions. Regarding the type of information most needed to improve emergency medical response, respondents indicated a desire for additional data related to the vehicle and its occupants. (4) Conclusions: The early and widespread availability of this information is expected to aid emergency responders in coordinating necessary resources faster and more optimally, help service optimization in situations with multiple motor vehicle collisions in close temporal proximity, and improve on-scene safety for first responders and other necessary personnel.

Injury risk curves in far-side lateral motor vehicle crashes by AIS level, body region and injury code

OBJECTIVE

The objective of this study was to develop injury risk curves as a function of change in vehicle velocity for occupants in far-side lateral motor vehicle crashes (MVCs) by AIS level, body region, and specific AIS codes that commonly occur in this crash mode.

METHODS

The National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) years 2000-2015 database was queried, resulting in 4,495 non-weighted far-side crashes. For each case, occupant age, sex, and the following metadata were collected: vehicle model year, vehicle body type, lateral delta-v, normalized PDOF, multiple impacts, belt use, seat position, object contacted, striking vehicle body type, maximum crush extent and side airbag deployment. Multivariable logistic regression was used to develop risk curves for AIS 2+ through 5+ injuries, AIS 2+ injuries by body region (head, thorax, lower extremity), and for each of the 10 most frequent far-side AIS 2+ injuries. Significant covariates were determined by backwards elimination (p < 0.05). The full dataset and a subsampled dataset of only cases with side airbag deployment were used to develop risk curves.

RESULTS

For AIS 2+ through 5+ injury, greater delta-V was associated with greater injury risk (OR's: 2.48-3.66 per 11.9 kph increase) and belt use was associated with lower risk (OR's: 0.04-0.36 compared to unbelted). Multiple impacts were significant predictors of increased AIS 3+, 4+ and 5+ injury risk (OR's: 2.56, 2.27 and 2.83 compared to single impact). For AIS 2+ body region injuries, lateral delta-V and maximum CDC extent were positively associated with increased head, thorax and lower extremity injury risk while belt use was associated with lower risk. Increased lateral delta-v, unbelted status, and greater maximum CDC extent frequently increased injury risk for the most common far-side injuries. Side airbag deployment was not a significant covariate for the injury risk models.

CONCLUSIONS

The resulting risk models expand upon previous literature gaps to provide a more comprehensive view of contributors to injury risk for occupants in far-side MVCs. This study yields risk curves based on the latest available NASS-CDS data.

Automatic collision notification availability and emergency response times following vehicle collision-an analysis of the 2017 crash investigation sampling system

OBJECTIVE

To determine whether occupants of collisions involving at least one vehicle with an available Automatic Collision Notification (ACN) system have quicker times from collision to 1) Emergency Medical Services (EMS) notification and 2) arrival to a medical center.

METHODS

Using data from the 2017 Crash Investigation Sampling System, vehicles were categorized as whether ACN was available using data from the CISS's dataset of crash avoidance system availability (in which ACN is included though notably not a crash avoidance system). A Cox proportional hazards model-overall and stratified by urbanization-was used to compare the time from collision to both EMS notification and EMS arrival to a medical center.

RESULTS

A total of 2,034 collisions (weight n: 2,775,512) involving 4235 occupants (weighted n: 4,987,669) were included. An estimated 259,021 (9.3%) and 546,223 occupants (11.0%) were in a collision in which one vehicle had ACN equipped. The median time to EMS notification was longer for collisions in which no involved vehicles had ACN available (median 4, IQR 2-9 minutes) than ACN-exposed collisions (median 2, IQR 1-5 minutes). There was a marginally significant higher hazard (i.e., instantaneous risk) of EMS notification for collisions with at least one vehicle having ACN available (HR 1.77, 95% CI 0.99-3.15). Likewise, there was a higher instantaneous risk of medical center arrival for occupants (HR 1.80, 95% CI 1.41-2.30) involved in collisions in which at least one vehicle had ACN available. ACN was associated with quicker EMS notification only in urban areas (HR 3.06, 95% CI 1.57-5.97) and associated with a greater reduction in time to medical facility in less urban areas (median 36 vs 45 minutes, HR 2.12, 95% CI 1.22-3.63).

CONCLUSIONS

This is the first study to directly compare EMS response-related times between collisions involving vehicles with and without ACN available. The current data corroborate prior literature reporting quicker EMS notification times among collisions involving ACN-equipped vehicles. This is the first study to find that ACN is also associated to quicker times to medical center arrival, particularly for collisions occurring in less urban areas. Future research examining whether these decreased times are associated with better clinical outcomes are needed in order to fully assess ACN's ability to prevent trauma-related mortality and morbidity.

Numerical investigation of occupant injury risks in car-to-end terminal crashes using dummy-based injury criteria and vehicle-based crash severity metrics

Guardrails were designed to deter vehicle access to off-road areas and consequently prevent hitting rigid fixed objects alongside the road (e.g. trees, utility poles, traffic barriers, etc.). However, guardrails cause 10 % of deaths in vehicle-to-fixed-object crashes, which recently attracted attention in the highway safety community on the vehicle-based injury criteria used in regulations. The objectives of this study were to investigate both full-body and body-region driver injury probabilities using finite element (FE) simulations, to quantify the influence of pre-impact conditions on injury probabilities, and to analyze the relationship between the vehicle-based crash severity metrics currently used in regulations and the injury probabilities assessed using dummy-based injury criteria. A total of 20 FE impact simulations between a car (Toyota Yaris) with a Hybrid III M50 dummy model in the driver seat and an end terminal model (ET-Plus) were performed in various configurations (e.g. pre-impact velocities, offsets, and angles). The driver's risk of serious injuries (AIS 3+) was estimated based on kinematic and kinetic responses of the dummy during the crashes. A non-linear regression approach was used to compare the injury probabilities assessed in this study to the vehicle-based crash severity metrics used in the testing regulations. In particular, the US Manual for Assessing Safety Hardware (MASH) guideline and European procedures (EN1317) were used for the study. All the recorded dummy-based injury criteria values pass the Federal Motor Vehicle Safety Standard (FMVSS) 208 limits which indicated a low driver risk of serious injury. Overall, the pre-impact vehicle velocity showed to have the highest influence in almost all injury probabilities (59 %, 79 %, 62 %, and 44 % in full-body, head, neck, and chest injuries, respectively). The offset between vehicle midline and the guardrail barrier was the most important variable for thigh injuries (56 %). The assessed injury probabilities were compared to vehicle-based severity metrics. The full-body and chest injuries showed the highest correlation with Occupant Impact Velocity (OIV), Acceleration Severity Index (ASI), and Theoretical Head Impact Velocity (THIV) (R² > 0.6). Lower correlations of thigh injuries were recorded to OIV (R² = 0.59) and THIV (R² = 0.46). Meanwhile, weak correlations were observed between all the other regressions which indicated that no vehicle-based criteria could be used to predict head and neck injuries. Car-to-end terminal crash FE simulations involving a dummy model were performed for the first time in this study. The results pointed out the limitations of the standard vehicle-based injury methods in terms of head and neck injury prediction. The dummy-based injury assessment methodology presented in this study could supplement the crash tests for various impact conditions. In addition, the models could be used to design new advanced guardrail end terminals.

Occupant injuries in light passenger vehicles-A NASS study to enable priorities for development of injury prediction capabilities of human body models

To prioritize how the development of mathematical human body models for injury prediction in crash safety analysis should be made, the most frequent injuries in the NASS CDS data from 2000 to 2015 were analyzed. The crashes were divided into seven types, from front to side. Non-minor injuries (AIS2+) were analyzed in two steps. In the first step, a grouping was made according to the AIS definition of body regions: head, face, neck, thorax, abdomen and pelvic contents, spine, upper extremities (including shoulder girdle) and lower extremities (including pelvis). In a second step, the body regions were divided in organs, parts of the spine, and parts of the extremities. The three most often injured anatomical structures of each body region were estimated for drivers and front seat passengers in each type of crash. For drivers, an injury risk greater than 2.4 % was found for the lower extremities (pelvis) and the head (concussion) in side oblique near side impacts, for the head in frontal oblique near side impacts (concussion) and for the lower extremities (ankle joint) in frontal impacts. For passengers, an injury risk greater than 2.4 % was found for the thorax (lungs) in side near side impacts, for the head (concussion) in front oblique near side impacts, and for the thorax (sternum) and the upper extremities (wrist, hand) in frontal impacts. Future development of human body models should focus on injuries to the head, thorax and the lower extremities. More specifically, it should focus on concussion in all impact directions and on rib and pelvic fractures in side near side impacts and in side oblique near side impacts.

Estimated crash injury risk and crash characteristics for motorsport drivers

OBJECTIVE

Motorsport crash events are complex and driver restraint systems are unique to the motorsport environment. The National Association for Stock Car Auto Racing, Incorporated (NASCAR®) crash and medical datasets provide an opportunity to assess crash statistics and the relationship between crash characteristics and driver injury. Injury risk curves can estimate driver injury risk and can be developed using vehicle incident data recorder information as inputs. These relationships may provide guidance and insight for at-track emergency response, driver triage and treatment protocols.

METHOD

Eight race seasons of crash and medical record data (including Association for the Advancement of Automotive Medicine Abbreviated Injury Scale (AIS) scores) from the Monster Energy NASCAR Cup Series & NASCAR Xfinity Series were processed and analyzed. Multiple logistic regression modeling was used to produce injury risk curves from longitudinal and lateral resultant change in velocity, resultant peak acceleration, principal direction of force and the number of impacts per incident.

RESULTS

2065 Unique IDR data files were matched with 246 cases of driver injury or sub-injury (severity below AIS 1) and 1819 no-injury cases. Multiple logistic regression modeling showed increasing resultant change in velocity, resultant peak acceleration and the number of impacts during a crash event all increase estimated driver injury risk. After accounting for the other predictors in the model, right lateral impacts were found to have a lower estimated injury risk. The model produced an Area Under the Receiver Operating Characteristics curve of 0.80. Across the eight race seasons in this study the overall average resultant change in velocity was 34.4 kph (21.4 mph) and the average resultant peak acceleration was 19.0 G for an average of 258 crashes per season. For 2011 through 2015, full time drivers experienced 134 times more crashes per mile traveled than passenger vehicles, but experienced 9.3 times fewer injuries per crash.

CONCLUSION

Multiple logistic regression was used to estimate AIS 1+ injury only and AIS 1+ with sub-injury risk for motorsport drivers using motorsport-specific crash and medical record databases. The injury risk estimate models can provide future guidance and insight for at-track emergency medical response dispatch immediately following an on-track crash. These models may also inform future driver triage protocols and influence future expenditures on motorsports safety research.

Accuracy of algorithms to predict injury severity in older adults for trauma triage

Objective: Older adults make up a rapidly increasing proportion of motor vehicle occupants and previous studies have demonstrated that this population is more susceptible to traumatic injuries. The CDC recommends that patients anticipated to have severe injuries (Injury Severity Score [ISS] ≥ 16) be transported to a trauma center. The recommended target rate for undertriage is ≤ 5% and for overtriage is ≤ 50%. Several regression-based algorithms for injury prediction have been developed in order to predict severe injury in occupants involved in a motor vehicle collision (MVC). The objective of this study to was to determine if the accuracy of regression-based injury severity prediction algorithms decreases for older adults.Methods: Data were obtained from the National Automotive Sampling System - Crashworthiness Data System (NASS-CDS) from the years 2000-2015. Adult occupants involved in non-rollover MVCs were included. Regression-based injury risk models to predict severe injury (ISS ≥ 16) were developed using random split-samples with the following variables: age, delta-V, direction of impact, belt status, and number of impacts. Separate models were trained using data from the following age groups: (1) all adults, (2) 15-54 years, (3) ≥45 years, (4) ≥55 years, and (5) ≥65 years. The models were compared using the mean receiver operating characteristic area under curve (ROC-AUC) after 1,000 iterations of training and testing. The predicted rates of overtriage were then determined for each group in order to achieve an undertriage rate of 5%.Results: There were 24,577 occupants (6,863,306 weighted) included in this analysis. The injury prediction model trained using data from all adults did not perform as well when tested on older adults (ROC-AUC: 15-54 years: 0.874 [95% CI: [0.851-0.895]; 45+ years: 0.837 [95% CI: 0.802-869]; 55+ years: 0.821 [95% CI: 0.775-0.864]; and 65+ years: 0.813 [95% CI: 0.754-0.866]). The accuracy of this model decreased in each decade of life. The performance did not change significantly when age-specific data were used to train the prediction models (ROC-AUC: 18-54 years: 0.874 [95% CI: 0.851-0.896]; 45+ years: 0.836 [95% CI: 0.798-0.871]; 55+ years: 0.822 [95% CI: 0.779-0.864]; and 65+ years: 0.808 [95% CI: 0.748-0.868]). In order to achieve an undertriage rate of 5%, the predicted overtriage rate by these models were 50% for occupants 15-54 years, 61% for occupants ≥ 55 years, 70% for occupants ≥ 55 years, and 71% for occupants ≥ 65 years.Conclusion: The results of this study indicate that it is more difficult to accurately predict severe injury in older adults involved in MVCs, which has the potential to result in significant overtriage. This decreased accuracy is likely due to variations in fragility in older adults. These findings indicate that special care should be taken when using regression-based prediction models to determine the appropriate hospital destination for older occupants.

Motorcyclist injury risk as a function of real-life crash speed and other contributing factors

The Vision Zero approach advocates for a road transport system designed with human injury tolerance and human fallibility as its basis. While biomechanical limits and the relationship between speed and injury outcome has been extensively investigated for car occupants and pedestrians, research analyzing this relationship for motorcyclists remains limited. The aim of this study was to address this issue by developing multivariate injury risk models for motorcyclists that estimate the relationship between speed and injury severity. For that purpose, motorcycle injury crashes from the German In-Depth Accident Study (GIDAS) database for the period 1999-2017 (n = 1037) were extracted. Different models were tested using logistic regression and backwards elimination of non-significant variables. The best fitting model in the current study included relative speed, type of crash opponent, impact location on the motorcycle and impact mechanism of the rider during the crash. A strong and significant relationship between relative speed and injury severity in motorcycle crashes was demonstrated. At 70 km/h, the risk for at least serious injuries in collisions with wide objects, crash barriers and narrow objects was 20%, 51%, and 64%, respectively. Further, it was found that head-on collisions between motorcycles and passenger cars, with both vehicles traveling at 60 km/h (a relative speed at 120 km/h), present 55% risk of at least serious injury to the motorcycle rider. More research is needed to fully understand the boundary conditions needed to design a safe road transport system for motorcyclists. However, this study provides important insights into the relationship between speed and injury severity for riders in various crash situations. The results may be useful in the discussion of appropriate speed limits and in determining the benefits of countermeasures which aim to reduce crash speed.

Coherence assessment of accident database kinematic data

The analysis and research of accidents aimed at improving the safety of vehicles and infrastructures are typically based on the retrospective investigation of data that are collected in in-depth accident databases. In particular, kinematic data related to accidents (impact velocity, velocity change of the vehicles, etc.) make possible the identification of correlations between impact severity and injury risk (IR), as well as assessing the effectiveness of vehicle protection systems. The necessary condition to conduct suitable and significant analyses is to utilise data which are correct and representative of national statistics, i.e., congruent with physical laws governing the accident phenomena. Whereas representativeness can generally be retrospectively verified, the checks on kinematic data coherence during codification are rarely performed. The present work describes a procedure to verify the internal coherence of kinematic data collected in in-depth accident databases. The introduced checks allow the identification of parameters, which are not internally coherent because the accident reconstruction model employed is inappropriate or improperly used. These checks pertain to physical laws on which road accident reconstruction is based, i.e., momentum conservation, compatibility of velocity triangles, and energy conservation. Moreover, they can be modified and expanded to consider other parameters, making the methodology virtually applicable to any database. In the case of vehicle-to-vehicle collisions, the application of the procedure to detect incongruent data inside two real databases demonstrates how their number is often not negligible. Furthermore, consequences can be substantial for both direct and secondary analysis, i.e., determining IR curves (for example, logistic regression on input data) and identifying IR associated to an accident. Accordingly, the application of checks is particularly recommended during both analysis and collection phases to confirm the congruence of collected data; consequently, the quality of investigation is enhanced.

Nonlinear models of injury risk and implications in intervention targeting for thoracic injury mitigation

OBJECTIVE

Field data analyses often use either parametric or nonparametric means to describe the relationship between risk and various predictor variables. This study sought to evaluate a hybrid approach using semiconstrained multivariate nonlinear spline-based analysis.

METHODS

Data were compiled from NASS-CDS years 1998-2015, selecting belted occupants age 16+ in collisions with a principal direction of force (PDOF) from 10 o'clock to 2 o'clock. Outcome measures included the incidence of Maximum Abbreviated Injury Scale (MAIS) 3+ injury in general and Abbreviated Injury Scale (AIS) 3+ rib fracture injury. Multivariate logistic regression models were fit controlling for PDOF, ΔV, vehicle model year, collision year, occupant age, occupant body mass index (BMI), and other select factors. Within the logistic regression models, each of the continuous variables was modeled with a 4-knot spline. These were compared to models treating ΔV and BMI linearly.

RESULTS

A total of 29,667 occupants were observed from the query, representing approximately 13,608,398 occupants when weighted. Sixty percent of the AIS 3+ rib fracture cases occurred at ΔVs at or below 40 km/h. The median age for cases without AIS 3+ rib fracture was 34 years old. The median age for cases with AIS 3+ rib fracture was 62 years old. When modeled via nonlinear spline, the risk of MAIS 3+ injury in general and AIS 3+ rib fracture injury specifically exhibited a relationship with ΔV similar in shape to that observed in the linear model. In both cases, the spline model exhibited greater risk prediction over ΔVs from 25 to 50 km/h compared to the linear model (20-33% greater risk at ΔVs below 40 km/h) and less risk than the linear model at greater ΔVs. BMI exhibited a nonlinear, nonmonotonic relationship with both injury types studied. The risk tended to be a minimum at BMIs of 22-24 kg/m², with an increase in risk at both higher and lower BMIs. For AIS 3+ rib fracture, the risk for a person with a BMI of 18 was approximately equal to the risk for a person with a BMI of 30, both being approximately 40% greater than the risk associated with a BMI of 24.

CONCLUSIONS

Nonlinear multivariate regression methods have the potential to convey information about the risk-predictor relationship that cannot be captured through traditional linear modeling. These results suggest that traditional linear logistic regression models may underestimate the risk of AIS 3+ rib fracture injury in the ΔV range where they most frequently occur (below 50 km/h). Due to its nonmonotonic effect, traditional linear models may underestimate injury risk at both high and low BMIs.

Development of injury risk models to guide CT evaluation in the emergency department after motor vehicle collisions

OBJECTIVE

The clinical evaluation of motor vehicle collision (MVC) victims is challenging and commonly relies on computed tomography (CT) to detect internal injuries. CT scans are financially expensive and each scan exposes the patient to additional ionizing radiation with an associated, albeit low, risk of cancer. Injury risk prediction based on regression modeling has been to be shown to be successful in estimating Injury Severity Scores (ISSs). The objective of this study was to (1) create risk models for internal injuries of occupants involved in MVCs based on CT body regions (head, neck, chest, abdomen/pelvis, cervical spine, thoracic spine, and lumbar spine) and (2) evaluate the performance of these risk prediction models to predict internal injury.

METHODS

All Abbreviated Injury Scale (AIS) 2008 injury codes were classified based on which CT body region would be necessary to scan in order to make the diagnosis. Cases were identified from the NASS-CDS. The NASS-CDS data set was queried for cases of adult occupants who sought medical care and for which key crash characteristics were all present. Forward stepwise logistic regression was performed on data from 2010-2014 to create models predicting risk of internal injury for each CT body region. Injury risk for each region was grouped into 5 levels: very low (<2%), low (2-5%), medium (5-10%), high (10-20%), and very high (20%). The models were then tested using weighted data from 2015 in order to determine whether injury rates fell within the predicted risk level.

RESULTS

The inclusion and exclusion criteria identified 5,477 cases in the NASS-CDS database. Cases from 2010-2014 were used for risk modeling (n = 4,826). Seven internal injury risk models were created based on the CT body regions using data from 2010-2014. These models were tested against data from 2015 (n = 651). In all CT body regions, the majority of occupants fell in the very low or low predicted injury rate groups, except for the head. On average, 57% of patients were classified as very low risk and 15% as low risk for each body region. In most cases the actual rate of injury was within the predicted injury risk range. The 95% confidence interval overlapped with predicting injury risk range in all cases.

CONCLUSION

This study successfully demonstrated the ability for internal injury risk models to accurately identify occupants at low risk for internal injury in individual body regions. This represents a step towards incorporating telemetry data into a clinical tool to guide physicians in the use of CT for the evaluation of MVC victims.

Reference PMHS Sled Tests to Assess Submarining of the Small Female

In the last decade, extensive efforts have been made to understand the physics of submarining and its consequences in terms of abdominal injuries. For that purpose, 27 Post Mortem Human Subject (PMHS) tests were performed in well controlled conditions on a sled and response corridors were provided to assess the biofidelity of dummies or human body models. All these efforts were based on the 50th percentile male. In parallel, efforts were initiated to transfer the understanding of submarining and the prediction criteria to the THOR dummies. Both the biofidelity targets and the criteria were scaled down from the 50th percentile male to the 5th percentile THOR female. The objective of this project was to run a set of reference PMHS tests in order to check the biofidelity of the THOR F05 in terms of submarining. Three series of tests were performed on nine PMHS, the first one was designed to avoid submarining, the second and third ones were designed to result in submarining. In the first configuration, no submarining was observed in 3 cases out of 4 and only one iliac wing fracture occurred in one subject. In the second and third configurations, all subjects but one sustained submarining. In addition, two subjects out of three in the third configuration sustained substantial iliac wing fractures. Nevertheless, all configurations can be represented by at least one or several cases without any pelvis fracture. Corridors were constructed for the external forces and the PMHS kinematics. They are provided in this paper as new experimental references to assess the biofidelity of small female human surrogates in different configurations where submarining did or did not occur.

Mechanisms and Mitigation of Head and Spinal Injuries Due to Motor Vehicle Crashes

Synopsis Head and spinal injuries commonly occur during motor vehicle crashes (MVCs). The goal of this clinical commentary is to discuss real-life versus simulated MVCs and to present clinical, biomechanical, and epidemiological evidence of MVC-related injury mechanisms. It will also address how this knowledge may guide and inform the design of injury mitigation devices and assist in clinical decision making. Evidence indicates that there exists no universal injury tolerance applicable to the entire population of the occupants of MVCs. Injuries sustained by occupants depend on a number of factors, including occupant characteristics (age, height, weight, sex, bone mineral density, and pre-existing medical and musculoskeletal conditions), pre-MVC factors (awareness of the impending crash, occupant position, usage of and position of the seatbelt and head restraint, and vehicle specifications), and MVC-related factors (crash orientation, vehicle dynamics, type of active or passive safety systems, and occupant kinematic response). Injuries resulting from an MVC occur due to blunt impact and/or inertial loading. An S-shaped curvature of the cervical spine and associated injurious strains have been documented during rear-, frontal-, and side-impact MVCs. Data on the injury mechanism and the quantification of spinal instability guide and inform the emergent and subsequent conservative or surgical care. Such care may require determining optimal patient positioning during transport, which injuries may be treated conservatively, whether reduction should be performed, optimal patient positioning intraoperatively, and whether bracing should be worn prior to and/or following surgery. The continued improvement of traditional injury mitigation systems, such as seats, seatbelts, airbags, and head restraints, together with research of newer collision-avoidance technologies, will lead to safer motor vehicles and ultimately more effective injury management strategies. J Orthop Sports Phys Ther 2016;46(10):826-833. Epub 3 Sep 2016. doi:10.2519/jospt.2016.6716.