Literature DB >> 28730547

Sideways fall-induced impact force and its effect on hip fracture risk: a review.

M Nasiri Sarvi1,2, Y Luo3,4.   

Abstract

Osteoporotic hip fracture, mostly induced in falls among the elderly, is a major health burden over the world. The impact force applied to the hip is an important factor in determining the risk of hip fracture. However, biomechanical researches have yielded conflicting conclusions about whether the fall-induced impact force can be accurately predicted by the available models. It also has been debated whether or not the effect of impact force has been considered appropriately in hip fracture risk assessment tools. This study aimed to provide a state-of-the-art review of the available methods for predicting the impact force, investigate their strengths/limitations, and suggest further improvements in modeling of human body falling.
METHODS: We divided the effective parameters on impact force to two categories: (1) the parameters that can be determined subject-specifically and (2) the parameters that may significantly vary from fall to fall for an individual and cannot be considered subject-specifically.
RESULTS: The parameters in the first category can be investigated in human body fall experiments. Video capture of real-life falls was reported as a valuable method to investigate the parameters in the second category that significantly affect the impact force and cannot be determined in human body fall experiments.
CONCLUSIONS: The analysis of the gathered data revealed that there is a need to develop modified biomechanical models for more accurate prediction of the impact force and appropriately adopt them in hip fracture risk assessment tools in order to achieve a better precision in identifying high-risk patients. Graphical abstract Impact force to the hip induced in sideways falls is affected by many parameters and may remarkably vary from subject to subject.

Entities:  

Keywords:  Fall; Fracture risk; Hip; Hip fracture; Impact force; Sideways

Mesh:

Year:  2017        PMID: 28730547     DOI: 10.1007/s00198-017-4138-5

Source DB:  PubMed          Journal:  Osteoporos Int        ISSN: 0937-941X            Impact factor:   4.507


  112 in total

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  8 in total

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Authors:  S K Gratza; P O Chocano-Bedoya; E J Orav; M Fischbacher; G Freystätter; R Theiler; A Egli; R W Kressig; J A Kanis; H A Bischoff-Ferrari
Journal:  Osteoporos Int       Date:  2019-08-03       Impact factor: 4.507

2.  Influence of bone lesion location on femoral bone strength assessed by MRI-based finite-element modeling.

Authors:  Chamith S Rajapakse; Nishtha Gupta; Marissa Evans; Hamza Alizai; Malika Shukurova; Abigail L Hong; Nicholas J Cruickshank; Nirmal Tejwani; Kenneth Egol; Stephen Honig; Gregory Chang
Journal:  Bone       Date:  2019-03-07       Impact factor: 4.398

3.  On the internal reaction forces, energy absorption, and fracture in the hip during simulated sideways fall impact.

Authors:  Ingmar Fleps; William S Enns-Bray; Pierre Guy; Stephen J Ferguson; Peter A Cripton; Benedikt Helgason
Journal:  PLoS One       Date:  2018-08-16       Impact factor: 3.240

4.  Physical and Psychological Factors Affecting Falls in Older Patients with Arthritis.

Authors:  Mikyong Byun; Jiyeon Kim; Moonho Kim
Journal:  Int J Environ Res Public Health       Date:  2020-02-09       Impact factor: 3.390

5.  The Influence of Fall Direction and Hip Protector on Fracture Risk: FE Model Predictions Driven by Experimental Data.

Authors:  Ellie S Galliker; Andrew C Laing; Stephen J Ferguson; Benedikt Helgason; Ingmar Fleps
Journal:  Ann Biomed Eng       Date:  2022-02-07       Impact factor: 3.934

6.  Characteristics of step responses following varying magnitudes of unexpected lateral perturbations during standing among older people - a cross-sectional laboratory-based study.

Authors:  Shani Batcir; Guy Shani; Amir Shapiro; Itshak Melzer
Journal:  BMC Geriatr       Date:  2022-05-06       Impact factor: 4.070

7.  Advanced 2D image processing technique to predict hip fracture risk in an older population based on single DXA scans.

Authors:  F Jazinizadeh; J D Adachi; C E Quenneville
Journal:  Osteoporos Int       Date:  2020-05-15       Impact factor: 4.507

8.  Acceleration Magnitude at Impact Following Loss of Balance Can Be Estimated Using Deep Learning Model.

Authors:  Tae Hyong Kim; Ahnryul Choi; Hyun Mu Heo; Hyunggun Kim; Joung Hwan Mun
Journal:  Sensors (Basel)       Date:  2020-10-28       Impact factor: 3.576

  8 in total

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