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OBJECTIVE Obesity has important implications for motor vehicle safety due to altered crash injury responses from increased mass and improper seatbelt placement. Abdominal seatbelt signs (ASBS) above the anterior superior iliac spine (ASIS) in motor vehicle crashes (MVCs) often correlate with abdominopelvic trauma. We investigated the relationship of body mass index (BMI), lap belt placement, and the incidence of abdominopelvic injury using computed tomography (CT) evaluation for subcutaneous ASBS mark and its location relative to the ASIS. METHODS A retrospective analysis of 235 Crash Injury Research and Engineering Network (CIREN) cases and their associated abdominal injuries was conducted. CT Scans were analyzed to visualize fat stranding. 150 positive ASBS were found and their ASBS mark location was classified as superior, on, or inferior to the ASIS. RESULTS Obese occupants had a higher incidence rate of belt placement superior to the ASIS, and occupants with normal BMI had a higher incidence of proper belt placement (p

OBJECTIVE: Prehospital non-transport events occur when emergency medicine service (EMS) providers respond to a scene, but the patient is ultimately not transported to a hospital for evaluation. The objective of this study was to determine the rate of non-transport of pediatric patients who were involved in a motor vehicle collision (MVC) and the factors associated with non-transport decisions. METHODS: We searched the National Emergency Medical Services Information System (NEMSIS) database using ICD-10 mechanism of injury codes to identify cases in which EMS responded to a pediatric occupant (age < 18 years) who had been involved in an MVC. We excluded interfacility transports, scene assists, deaths at the scene, and collisions that occurred outside the US. The outcome of interest was if pediatric patients were not transported to a hospital for evaluation. We performed univariate and multivariate analysis to identify which risk factors were associated with non-transport. We also analyzed regional variation and the reasons recorded for not transporting patients. RESULTS: We identified 92,254 pediatric patients who were evaluated by EMS after an MVC, of which 31,404 (34.0%) were not transported to a hospital for evaluation. In our adjusted analysis, the factors associated with non-transport were age 16 years, male sex, normal Glasgow Coma Scale (GCS = 15), level of training of EMS providers, response time later than 6 a.m., and region of the country. GCS was the most important factor, with only 3.0% (108/3,616) of patients not transported who had abnormal GCS (< 15). In cases of non-transport, 32.7% (10257) were due to patient or caregiver refusal, and 33.3% (10,442) were due to patients being discharged against medical advice. Only 11.5% (3,627) pediatric patients who were not transported were discharged based on an established protocol. CONCLUSIONS: Pediatric patients were not transported after EMS responded to an MVC in approximately one-third of cases, and there was considerable variation in the rate of non-transports based on geographic region, provider level, and time of day. The majority of non-transports occurred because patients were discharged against medical advice or the patient/caregiver refused transport, which may indicate conflicting priorities between EMS providers and patients.

Misidentification of illness severity may lead to patients being admitted to a ward bed then unexpectedly transferring to an ICU as their condition deteriorates. Our objective was to develop a predictive analytic tool to identify emergency department (ED) patients that required upgrade to an intensive or intermediate care unit (ICU or IMU) within 24 h after being admitted to an acute care floor. We conducted a single-center retrospective cohort study to identify ED patients that were admitted to an acute care unit and identified cases where the patient was upgraded to ICU or IMU within 24 h. We used data available at the time of admission to build a logistic regression model that predicts early ICU transfer. We found 42,332 patients admitted between January 2012 and December 2016. There were 496 cases (1.2%) of early ICU transfer. Case patients had 18.0-fold higher mortality (11.1% vs. 0.6%, p

OBJECTIVE Transporting severely injured pediatric patients to a trauma center has been shown to decrease mortality. A decision support tool to assist emergency medical services (EMS) providers with trauma triage would be both as parsimonious as possible and highly accurate. The objective of this study was to determine the minimum set of predictors required to accurately predict severe injury in pediatric patients. METHODS Crash data and patient injuries were obtained from the NASS and CISS databases. A baseline multivariable logistic model was developed to predict severe injury in pediatric patients using the following predictors: age, sex, seat row, restraint use, ejection, entrapment, posted speed limit, any airbag deployment, principal direction of force (PDOF), change in velocity (delta-V), single vs. multiple collisions, and non-rollover vs. rollover. The outcomes of interest were injury severity score (ISS) ≥16 and the Target Injury List (TIL). Accuracy was measured by the cross-validation mean of the receiver operator curve (ROC) area under the curve (AUC). We used Bayesian Model Averaging (BMA) based on all subsets regression to determine the importance of each variable separately for each outcome. The AUC of the highest performing model for each number of variables was compared to the baseline model to assess for a statistically significant difference (p

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.

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 (

Previous work has shown that the lap belt moves superior and forward compared to the bony pelvis as body mass index (BMI) increases. The goal of this project was to determine whether the location of lap belt loading is related to BMI for occupants who sustained real-world motor vehicle collisions (MVCs).A national MVC database was queried for vehicle occupants over a 10-year period (2003-2012) who were at least 16 years old, restrained by a 3-point seat belt, sitting in the front row, and involved in a front-end collision with a change in velocity of at least 56 km/h. Cases were excluded if there was not an available computed tomography (CT) scan of the abdomen. CT scans were then analyzed using adipose enhancement of 3-dimensional reconstructions. Scans were assessed for the presence a radiographic seat belt sign (rSBS), or subcutaneous fat stranding due to seat belt loading. In scans in which the rSBS was present, anterior and superior displacement of rSBS from the anterior-superior iliac spine (ASIS) was measured bilaterally. This displacement was correlated with BMI and injury severity.The inclusion and exclusion criteria yielded 151 cases for analysis. An rSBS could definitively be identified in 55 cases. Cases in which occupants were older and had higher BMI were more likely to display an rSBS. There was a correlation between increasing BMI and anterior rSBS displacement (P.01 and P.01, right and left, respectively). There was no significant correlation between BMI and superior displacement of the rSBS (P =.46 and P =.33, right and left, respectively). When the data were examined in terms of relating increasing superior displacement of the lap belt with Injury Severity Scale (P =.34) and maximum Abbreviated Injury Score (AIS) injury severity (P =.63), there was also no significant correlation.The results from this study demonstrated that anterior displacement of the radiographic seat belt sign but not superior displacement increased with higher BMI. These results suggest that obesity may worsen horizontal position but not the vertical position of the lap belt loading during real-world frontal MVCs.

Objective The objective of this study was to describe recent trends in the epidemiology of lawn mower injuries presenting to the Emergency Department in the United States using nationally representative data for all ages. Methods Data for this retrospective analysis were obtained from the U.S. Consumer Product Safety Commission's National Electronic Injury Surveillance System (NEISS), for the years 2005–2015. We queried the system using all product codes under “lawn mowers” in the NEISS Coding Manual. We examined body part injured, types of injuries, gender and age distribution, and disposition. Results There were an estimated 934,394 lawn mower injuries treated in U.S. ED's from 2005 to 2015, with an average of 84,944 injuries annually. The most commonly injured body parts were the hand/finger (22.3%), followed by the lower extremity (16.2%). The most common type of injury was laceration (23.1%), followed by sprain/strain (18.8%). The mean age of individuals injured was 46.5 years, and men were more than three times as likely to be injured as women. Patients presenting to the ED were far more likely to be discharged home after treatment (90.5%) than to be admitted (8.5%). Conclusion Lawn mowers continue to account for a large number of injuries every year in the United States. The incidence of lawn mower injuries showed no decrease during the period of 2005–2015. Preventative measures should take into account the epidemiology of these injuries.

Injuries to the hollow organs of the lower digestive system carry substantial risk of complication due to infection and blood loss, and commonly require invasive abdominal surgery to diagnose and treat. The causes of, and risk factors for, lower abdomen injury in automobile collisions are poorly understood. The goal of this study was to investigate the risk factors and potential mechanisms of hollow-organ, lower abdomen injury in belted automobile occupants in frontal collisions. A field survey data analysis was performed to examine the relationship between various occupant and collision factors and the risk of moderate or greater severity injury (i.e., Abbreviated Injury Scale, AIS 2+) to the small intestine, large intestine, or mesentery among belted occupants involved in frontal collisions. Descriptive and comparative risk factor analyses were performed with data originating from that National Automotive Sampling System Crashworthiness Data System (NASS-CDS) over the years 2000-2011. Multivariable logistic regression models were developed to describe the effects of these factors on hollow-organ injury risk. Potential injury mechanisms were further investigated through in-depth examination of select cases exhibiting hollow-organ injuries from the Crash Investigation Research and Engineering Network (CIREN). The inclusion criteria yielded 25,407 individual cases from NASS-CDS, representing a weighted population of 11,373,358 exposed automobile occupants. Within this dataset, 143 cases (weighted frequency: 7962 occupants) exhibited AIS 2+ injury to hollow abdominal organs. Multivariable regression analysis indicated a statistically significant increased risk of moderate or greater severity injuries to the hollow organs of the abdomen with increased in ΔV (odds ratio (OR) 1.07, 95% confidence interval: 1.06-1.09) and age (OR: 1.03, 1.01-1.06). Albeit non-statistically significant, a positive association between BMI and injury risk was observed, especially among obese individuals (OR: 3.55, 0.82-15.2). No association was observed for gender or seated location within the vehicle. RESULT: from this study indicate that hollow abdominal organ injury is a universal problem in frontal collisions, not confined to a specific gender or seating location. Examination of CIREN cases suggests these types of injuries are associated with direct loading of the lower abdomen by the lap belt, either through poor initial belt positioning or through a "submarining" type of kinematic where the lap belt slips off of the pelvis and loads into the abdomen. Potential countermeasures against hollow-organ abdominal injury should include measures to improve initial lap belt fit, and to retain engagement of the lap belt on the pelvis throughout the collision event. Language: en