Citation

Burkhart TA, Andrews DM, Dunning CE. J. Biomech. 2013; 46(5): 973-978.

Affiliation

Department of Mechanical and Materials Engineering, Western University, 1151 Richmond Street, London, Ont., Canada, N6A 5B9. Electronic address: tburkhar@uwo.ca.

Copyright

(Copyright © 2013, Elsevier Publishing)

DOI

10.1016/j.jbiomech.2012.12.003

PMID

23352774

Abstract

The purpose of this study was to develop a multivariate distal radius injury risk prediction model that incorporates dynamic loading variables in multiple directions, and interpret the distal radius failure data in order to establish injury probability thresholds. Repeated impacts with increasing intensity were applied to the distal third of eight human cadaveric radius specimens (mean (SD) age=61.9 (9.7)) until injury occurred. Crack (non-propagating damage) and fracture (specimen separated into at least two fragments) injury events were recorded. Best subsets analysis was performed to find the best multivariate injury risk model. Force-only risk models were also determined for comparison. Cumulative distribution functions were developed from the parameters of a Weibull analysis and the forces and risk scores (i.e., values calculated from the injury risk models) from 10% to 90% probability were calculated. According to the adjusted R(2), variance inflation factor and p-values, the model that best predicted the crack event included medial/lateral impulse, F(z) load rate, impact velocity and the natural logarithm of F(z) (Adj. R(2)=0.698), while the best predictive model of the fracture event included medial/lateral impulse, impact velocity and peak F(z) (Adj. R(2)=0.845). The multivariate models predicted injury risk better than both the F(z)-only crack (Adj. R(2)=0.551) and fracture (Adj. R(2)=0.293) models. Risk scores of 0.5 and 0.6 corresponded to 10% failure probability for the crack and fracture events, respectively. The inclusion of medial/lateral impulse and impact velocity in both crack and fracture models, and F(z) load rate in the crack model, underscores the dynamic nature of these events. This study presents a method capable of developing a set of distal radius fracture prediction models that can be used in the assessment and development of distal radius injury prevention interventions.

Language: en