Citation

Gorman D, Handy E, Wang S, Irwin AL, Wang S. Stapp Car Crash J. 2016; 60: 287-300.

Affiliation

International Center for Automotive Medicine.

Copyright

(Copyright © 2016, Society of Automotive Engineers SAE)

DOI

unavailable

PMID

27871101

Abstract

Previous studies of frontal crash databases reported that ankle fractures are among the most common lower extremity fractures. While not generally life threatening, these injuries can be debilitating. Laboratory research into the mechanisms of ankle fractures has linked dorsiflexion with an increased risk of tibia and fibula malleolus fractures. However, talus fractures were not produced in the laboratory tests and appear to be caused by more complex loading of the joint. In this study, an analysis of the National Automotive Sampling System - Crashworthiness Data System (NASS-CDS) for the years 2004-2013 was conducted to investigate foot-ankle injury rates in front seat occupants involved in frontal impact crashes. A logistic regression model was developed indicating occupant weight, impact delta velocity and gender to be significant predictors of talus fracture (p<0.05). Separately, a specific set of Computed Tomography (CT) scans from the International Center for Automotive Medicine (ICAM) scan database was used to characterize the talar dome. This control population consisted of 207 adults aged 18 to 84, with no foot or ankle trauma, and scans that had suitable coverage of the talus. Size of the talus was determined using medial-to-lateral width and anterior-to-posterior depth measurements. Geometry was assessed by evaluating the radius of the articulating talus and strength was assessed using a combination of cross sectional area and density. Demographics were studied to investigate correlation with talus measurements from the CT scan database. A multi-variable linear regression model of the morphomics showed gender to be statistically significant (p<0.05) for talus depth, width, cross-sectional area, radius and strength. Body Mass Index (BMI) was significant for depth and radius. Weight was significant for depth, width, density and strength. Stature was significant for depth, cross-sectional area, radius and strength. Age was significant for radius and density.

Language: en