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    Multiple Regression Analysis of Hip Fracture Risk Assessment Via Finite Element Analysis

    Source: Journal of Engineering and Science in Medical Diagnostics and Therapy:;2021:;volume( 004 ):;issue: 001::page 011006-1
    Author:
    Awal, Rabina
    ,
    Faisal, Tanvir R.
    DOI: 10.1115/1.4049233
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: An accurate assessment of hip fracture risk requires a proper consideration of parameters affecting the fracture. In general, hip fracture is assessed based on bone mineral density (BMD) and load amount, but hip fracture is an outcome of the interaction of the parameters such as loading directions, bone density, which are often disregarded. Assessing the effect of the parameters individually may not correctly reflect the root cause of the hip fracture. Hence, this research aims at analyzing the significance of parameters and their interaction in assessing the fracture risk. A multiple regression analysis has been conducted considering bone density (ρash), different loading directions during sideways fall, represented by load angle (α) about femoral shaft on the coronal plane and angle (β) about femoral neck (FN) axis on the transverse plane as independent parameters and fracture risk index (FRI) as a dependent parameter. The statistical results showing the significant value of 0.7321 for α, and 0.0001 for β and ρash indicate that the effect of loading direction (α) does not have impact on fracture risk in comparison with the loading direction (β) and ρash. Furthermore, the analysis of the interaction of parameters shows that the impact of β on fracture risk may depends more on bone density.
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      Multiple Regression Analysis of Hip Fracture Risk Assessment Via Finite Element Analysis

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4277962
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    • Journal of Engineering and Science in Medical Diagnostics and Therapy

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    contributor authorAwal, Rabina
    contributor authorFaisal, Tanvir R.
    date accessioned2022-02-05T22:40:46Z
    date available2022-02-05T22:40:46Z
    date copyright1/13/2021 12:00:00 AM
    date issued2021
    identifier issn2572-7958
    identifier otherjesmdt_004_01_011006.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4277962
    description abstractAn accurate assessment of hip fracture risk requires a proper consideration of parameters affecting the fracture. In general, hip fracture is assessed based on bone mineral density (BMD) and load amount, but hip fracture is an outcome of the interaction of the parameters such as loading directions, bone density, which are often disregarded. Assessing the effect of the parameters individually may not correctly reflect the root cause of the hip fracture. Hence, this research aims at analyzing the significance of parameters and their interaction in assessing the fracture risk. A multiple regression analysis has been conducted considering bone density (ρash), different loading directions during sideways fall, represented by load angle (α) about femoral shaft on the coronal plane and angle (β) about femoral neck (FN) axis on the transverse plane as independent parameters and fracture risk index (FRI) as a dependent parameter. The statistical results showing the significant value of 0.7321 for α, and 0.0001 for β and ρash indicate that the effect of loading direction (α) does not have impact on fracture risk in comparison with the loading direction (β) and ρash. Furthermore, the analysis of the interaction of parameters shows that the impact of β on fracture risk may depends more on bone density.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleMultiple Regression Analysis of Hip Fracture Risk Assessment Via Finite Element Analysis
    typeJournal Paper
    journal volume4
    journal issue1
    journal titleJournal of Engineering and Science in Medical Diagnostics and Therapy
    identifier doi10.1115/1.4049233
    journal fristpage011006-1
    journal lastpage011006-7
    page7
    treeJournal of Engineering and Science in Medical Diagnostics and Therapy:;2021:;volume( 004 ):;issue: 001
    contenttypeFulltext
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