Patterns of Injury in Belted and Unbelted Individuals Presenting to a Trauma Center After Motor Vehicle Crash: Seat Belt Syndrome Revisited

Porter, Robert S.; Zhao, Ning

doi:10.1016/s0196-0644(98)70169-6

Cited by 76 publications

(56 citation statements)

References 25 publications

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“…Belt use significantly contributed to a reduction in risk for 13 of the 23 specific injuries yet was a nonsignificant predictor for rib, sternum, lumbar spine transverse process, carpus/metacarpus, and clavicle fractures associated with higher risk for belted occupants. Sternum and clavicle fracture incidence is known to be increased for belted compared to unbelted occupants due to belt loading (Hill et al 1994;Kemper et al 2009;Porter and Zhao 1998). Thoracolumbar spine fracture incidence has also increased over time despite increasing rates of belt use (Doud et al 2015), and belt use has been linked to an increased odds of lumbar compression fractures (Kaufman et al 2013).…”

Section: Discussionmentioning

confidence: 99%

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Weaver

Talton

Barnard

et al. 2015

Traffic Injury Prevention

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Objective: Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data.Methods: Logistic regression analysis of NASS-CDS single-impact frontal MVCs involving front seat occupants with frontal airbag deployment was used to produce 23 risk curves for specific injuries and 17 risk curves for Abbreviated Injury Scale (AIS) 2+ to 5+ body region injuries. Risk curves were produced for the following body regions: head and thorax (AIS 2+, 3+, 4+, 5+), face (AIS 2+), abdomen, spine, upper extremity, and lower extremity (AIS 2+, 3+). Injury risk with 95% confidence intervals was estimated for 15-105 km/h longitudinal delta-V s and belt status was adjusted for as a covariate.Results: Overall, belted occupants had lower estimated risks compared to unbelted occupants and the risk of injury increased as longitudinal delta-V increased. Belt status was a significant predictor for 13 specific injuries and all body region injuries with the exception of AIS 2+ and 3+ spine injuries. Specific injuries and body region injuries that occurred more frequently in NASS-CDS also tended to carry higher risks when evaluated at a 56 km/h longitudinal delta-V . In the belted population, injury risks that ranked in the top 33% included 4 upper extremity fractures (ulna, radius, clavicle, carpus/metacarpus), 2 lower extremity fractures (fibula, metatarsal/tarsal), and a knee sprain (2.4-4.6% risk). Unbelted injury risks ranked in the top 33% included 4 lower extremity fractures (femur, fibula, metatarsal/tarsal, patella), 2 head injuries with less than one hour or unspecified prior unconsciousness, and a lung contusion (4.6-9.9% risk). The 6 body region curves with the highest risks were for AIS 2+ lower extremity, upper extremity, thorax, and head injury and AIS 3+ lower extremity and thorax injury (15.9-43.8% risk).Conclusions: These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.

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Section: Discussionmentioning

confidence: 99%

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Weaver

Talton

Barnard

et al. 2015

Traffic Injury Prevention

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“…In addition, other studies suggest that seat belt use is not a stand-alone factor that increases the risk for intra-abdominal injuries, but rather changes the spectrum and patterns of injuries. 32,33 The current study indicates that the seat belt sign is associated with a higher rate of gastrointestinal injuries whereas the rate of solid organ injuries remains unchanged. In addition, proper restraint at the time of the crash is important, as the risk of intra-abdominal injury is higher in children whom are suboptimally restrained.…”

Section: Discussionmentioning

confidence: 61%

Association Between the Seat Belt Sign and Intra‐abdominal Injuries in Children With Blunt Torso Trauma in Motor Vehicle Collisions

Borgialli

Ellison

Ehrlich

et al. 2014

Academic Emergency Medicine

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Objectives: The objective was to determine the association between the abdominal seat belt sign and intra-abdominal injuries (IAIs) in children presenting to emergency departments with blunt torso trauma after motor vehicle collisions (MVCs).Methods: This was a planned subgroup analysis of prospective data from a multicenter cohort study of children with blunt torso trauma after MVCs. Patient history and physical examination findings were documented before abdominal computed tomography (CT) or laparotomy. Seat belt sign was defined as a continuous area of erythema, ecchymosis, or abrasion across the abdomen secondary to a seat belt restraint. The relative risk (RR) of IAI with 95% confidence intervals (CIs) was calculated for children with seat belt signs compared to those without. The risk of IAI in those patients with seat belt sign who were without abdominal pain or tenderness, and with Glasgow Coma Scale (GCS) scores of 14 or 15, was also calculated.Results: A total of 3,740 children with seat belt sign documentation after blunt torso trauma in MVCs were enrolled; 585 (16%) had seat belt signs. Among the 1,864 children undergoing definitive abdominal testing (CT, laparotomy/laparoscopy, or autopsy), IAIs were more common in patients with seat belt signs than those without (19% vs. 12%; RR = 1.6, 95% CI = 1.3 to 2.1). This difference was primarily due to a greater risk of gastrointestinal injuries (hollow viscous or associated mesentery) in those with seat belt signs (11% vs. 1%; RR = 9.4, 95% CI = 5.4 to 16.4). IAI was diagnosed in 11 of 194 patients (5.7%;

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“…[10][11][12] These protective devices can also cause injuries, especially if an air bag deploys when a patient is unrestrained. 13,14 Similarly, the direction of impact can play a role in the injury pattern. [15][16][17] Prior research has helped to determine how to effectively triage patients as well as how to efficiently allocate resources.…”

Section: Discussionmentioning

confidence: 99%

A Comparison of Data Sources for Motor Vehicle Crash Characteristic Accuracy

Grant

Gregor

Beck

et al. 2000

Academic Emergency Medicine

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Abstract. Objective: To determine the accuracy of police reports (PRs), ambulance reports (ARs), and emergency department records (EDRs) in describing motor vehicle crash (MVC) characteristics when compared with an investigation performed by an experienced crash investigator trained in impact biomechanics. Methods: This was a cross-sectional, observational study. Ninety-one patients transported by ambulance to a university emergency department (ED) directly from the scene of an MVC from August 1997 to April 1998 were enrolled. Potential patients were identified from the ED log and consent was obtained to investigate the crash vehicle. Data describing MVC characteristics were abstracted from the PR, AR, and medical record. Variables of interest included restraint use (RU), air bag deployment (AD), and type of impact (TI). Agreements between the variables and the independent crash investigation were compared using kappa. Interrater reliability was determined using kappa by comparing a random sample of 20 abstracted reports for each data source with the originally abstracted data. Results: Agreement using kappa between the crash investigation and each data source was 0.588 (95% CI = 0.508 to 0.667) for the PR, 0.330 (95% CI = 0.252 to 0.407) for the AR, and 0.492 (95% CI = 0.413 to 0.572) for the EDR. Variable agreement was 0.239 (95% CI = 0.164 to 0.314) for RU, 0.350 (95% CI = 0.268 to 0.432) for AD, and 0.631 (95% = 0.563 to 0.698) for TI. Interrater reliability was excellent (kappa > 0.8) for all data sources. Conclusions: The strength of the agreement between the independent crash investigation and the data sources that were measured by kappa was fair to moderate, indicating inaccuracies. This presents ramifications for researchers and necessitates consideration of the validity and accuracy of crash characteristics contained in these data sources.

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Patterns of Injury in Belted and Unbelted Individuals Presenting to a Trauma Center After Motor Vehicle Crash: Seat Belt Syndrome Revisited

Cited by 76 publications

References 25 publications

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Association Between the Seat Belt Sign and Intra‐abdominal Injuries in Children With Blunt Torso Trauma in Motor Vehicle Collisions

A Comparison of Data Sources for Motor Vehicle Crash Characteristic Accuracy

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