Literature DB >> 30096469

Factors associated with proximal femur fracture determined in a large cadaveric cohort.

Dan Dragomir-Daescu1, Timothy L Rossman2, Asghar Rezaei3, Kent D Carlson3, David F Kallmes4, John A Skinner4, Sundeep Khosla5, Shreyasee Amin6.   

Abstract

Many researchers have used cadaveric fracture tests to determine the relationship between proximal femur (hip) fracture strength and a multitude of possible explanatory variables, typically considered one or two at a time. These variables include subject-specific proximal femur variables such as femoral neck areal bone mineral density (aBMD), sex, age, and geometry, as well as physiological hip fracture event variables such as fall speed and angle of impact. However, to our knowledge, no study has included all of these variables simultaneously in the same experimental dataset. To address this gap, the present study simultaneously included all of these subject-specific and fracture event variables in multivariate models to understand their contributions to femoral strength and fracture type. The primary aim of this study was to determine not only whether each of these variables contributed to the prediction of femoral strength, but also to determine the relative importance of each variable in strength prediction. A secondary aim was to similarly characterize the importance of these variables for the prediction of fracture type. To accomplish these aims, we characterized 197 proximal femurs (covering a wide range of subject-specific variables) with DXA and CT scans, and then tested the femurs to fracture in a sideways fall on the hip configuration. Each femur was tested using one of three fall speed conditions and one of four angles of impact (bone orientations). During each test, we acquired measurements of relevant force and displacement data. We then reduced the test data to determine femoral strength, and we used post-fracture CT scans to classify the fracture type (e.g., trochanteric, cervical). Using these results, the explanatory variables were analyzed with mixed statistical models to explain variations in hip fracture strength and fracture type, respectively. Five explanatory variables were statistically significant in explaining the variability in femoral strength: aBMD, sex, age, fall speed, and neck-shaft angle (P ≤ 0.0135). These five variables, including significant interactions, explained 80% of the variability in hip fracture strength. Additionally, when only aBMD, sex, and age (P < 0.0001) were considered in the model, again including significant interactions, these three variables alone explained 79% of the variability in hip fracture strength. So while fall speed (P = 0.0135) and neck-shaft angle (P = 0.0041) were statistically significant, the inclusion of these variables did not appreciably improve the prediction of hip fracture strength compared to the model that considered only aBMD, sex and age. For the variables we included in this study, in the ranges we considered, our findings indicate that the clinically-available information of patient age, sex and aBMD are sufficient for femoral strength assessment. These findings also suggest that there is little value in the extra effort required to characterize the effect of femoral geometry on strength, or to account for the probabilistic nature of fall-related factors such as fall speed and angle of impact. For fracture type, the only explanatory variable found to be significant was aBMD (P ≤ 0.0099). We found that the odds of having intertrochanteric fractures increased by 47% when aBMD decreased by one standard deviation (0.2 g/cm2).
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Bone biomechanics; Bone testing speed; Femoral orientation; Fracture type; Hip fracture; Proximal femur strength

Mesh:

Year:  2018        PMID: 30096469      PMCID: PMC6342454          DOI: 10.1016/j.bone.2018.08.005

Source DB:  PubMed          Journal:  Bone        ISSN: 1873-2763            Impact factor:   4.398


  26 in total

1.  Prediction of fracture location in the proximal femur using finite element models.

Authors:  J H Keyak; S A Rossi; K A Jones; C M Les; H B Skinner
Journal:  Med Eng Phys       Date:  2001-11       Impact factor: 2.242

2.  Impact direction from a fall influences the failure load of the proximal femur as much as age-related bone loss.

Authors:  T P Pinilla; K C Boardman; M L Bouxsein; E R Myers; W C Hayes
Journal:  Calcif Tissue Int       Date:  1996-04       Impact factor: 4.333

3.  Proximal Cadaveric Femur Preparation for Fracture Strength Testing and Quantitative CT-based Finite Element Analysis.

Authors:  Dan Dragomir-Daescu; Asghar Rezaei; Susheil Uthamaraj; Timothy Rossman; James T Bronk; Mark Bolander; Vincent Lambert; Sean McEligot; Rachel Entwistle; Hugo Giambini; Iwona Jasiuk; Michael J Yaszemski; Lichun Lu
Journal:  J Vis Exp       Date:  2017-03-11       Impact factor: 1.355

4.  Method and Instrumented Fixture for Femoral Fracture Testing in a Sideways Fall-on-the-Hip Position.

Authors:  Dan Dragomir-Daescu; Asghar Rezaei; Timothy Rossman; Susheil Uthamaraj; Rachel Entwistle; Sean McEligot; Vincent Lambert; Hugo Giambini; Iwona Jasiuk; Michael J Yaszemski; Lichun Lu
Journal:  J Vis Exp       Date:  2017-08-17       Impact factor: 1.355

5.  Proximal femur elastic behaviour is the same in impact and constant displacement rate fall simulation.

Authors:  S Gilchrist; K K Nishiyama; P de Bakker; P Guy; S K Boyd; T Oxland; P A Cripton
Journal:  J Biomech       Date:  2014-07-07       Impact factor: 2.712

6.  Age-related reductions in the strength of the femur tested in a fall-loading configuration.

Authors:  A C Courtney; E F Wachtel; E R Myers; W C Hayes
Journal:  J Bone Joint Surg Am       Date:  1995-03       Impact factor: 5.284

7.  DXA predictions of human femoral mechanical properties depend on the load configuration.

Authors:  E Dall'Ara; B Luisier; R Schmidt; M Pretterklieber; F Kainberger; P Zysset; D Pahr
Journal:  Med Eng Phys       Date:  2013-05-16       Impact factor: 2.242

8.  Reducing hip fracture risk during sideways falls: evidence in young adults of the protective effects of impact to the hands and stepping.

Authors:  Fabio Feldman; Stephen N Robinovitch
Journal:  J Biomech       Date:  2007-03-28       Impact factor: 2.712

9.  Comparison of hip fracture risk prediction by femoral aBMD to experimentally measured factor of risk.

Authors:  Benjamin J Roberts; Erica Thrall; John A Muller; Mary L Bouxsein
Journal:  Bone       Date:  2009-10-22       Impact factor: 4.398

10.  Femoral neck BMD is a strong predictor of hip fracture susceptibility in elderly men and women because it detects cortical bone instability: the Rotterdam Study.

Authors:  Fernando Rivadeneira; M Carola Zillikens; Chris Edh De Laet; Albert Hofman; André G Uitterlinden; Thomas J Beck; Huibert Ap Pols
Journal:  J Bone Miner Res       Date:  2007-11       Impact factor: 6.741

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  6 in total

1.  Optimizing Accuracy of Proximal Femur Elastic Modulus Equations.

Authors:  Asghar Rezaei; Kent D Carlson; Hugo Giambini; Samad Javid; Dan Dragomir-Daescu
Journal:  Ann Biomed Eng       Date:  2019-03-12       Impact factor: 3.934

2.  Single-level subject-specific finite element model can predict fracture outcomes in three-level spine segments under different loading rates.

Authors:  Asghar Rezaei; Maryam Tilton; Yong Li; Michael J Yaszemski; Lichun Lu
Journal:  Comput Biol Med       Date:  2021-09-09       Impact factor: 6.698

3.  Comparison of HU histogram analysis and BMD for proximal femoral fragility fracture assessment: a retrospective single-center case-control study.

Authors:  Sun-Young Park; Hong Il Ha; Injae Lee; Hyun Kyung Lim
Journal:  Eur Radiol       Date:  2021-10-13       Impact factor: 7.034

Review 4.  Pathophysiology of Demineralization, Part I: Attrition, Erosion, Abfraction, and Noncarious Cervical Lesions.

Authors:  W Eugene Roberts; Jonathan E Mangum; Paul M Schneider
Journal:  Curr Osteoporos Rep       Date:  2022-02-07       Impact factor: 5.096

5.  Effect of Age on the Patterns of Traumatic Femoral Fractures: Seven Years of Experience at a Regional Tertiary Hospital.

Authors:  Hong Yuan; Hailong Yu; Yunpeng Zhu; Liangbi Xiang; Hongwei Wang
Journal:  Orthop Surg       Date:  2022-08-05       Impact factor: 2.279

Review 6.  The Role of Fall Biomechanics in the Cause and Prevention of Bone Fractures in Older Adults.

Authors:  Vicki Komisar; Stephen Neil Robinovitch
Journal:  Curr Osteoporos Rep       Date:  2021-06-09       Impact factor: 5.096

  6 in total

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