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Impact of Modeling Assumptions on Stability Predictions in Reverse Total Shoulder Arthroplasty

Overview of attention for article published in Frontiers in Physiology, August 2018
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Title
Impact of Modeling Assumptions on Stability Predictions in Reverse Total Shoulder Arthroplasty
Published in
Frontiers in Physiology, August 2018
DOI 10.3389/fphys.2018.01116
Pubmed ID
Authors

Mehul A. Dharia, Jeffrey E. Bischoff, David Schneider

Abstract

Reverse total shoulder arthroplasty (rTSA) is commonly used in the shoulder replacement surgeries for the relief of pain and to restore function, in patients with grossly deficient rotator cuff. Primary instability due to glenoid loosening is one of the critical complications of rTSA; the implants are designed and implanted such that the motion between the glenoid baseplate and underlying bone is minimized to facilitate adequate primary fixation. Finite element analysis (FEA) is commonly used to simulate the test setup per ASTM F2028-14 for comparing micromotion between designs or configurations to study the pre-clinical indications for stability. The FEA results can be influenced by the underlying modeling assumptions. It is a common practice to simplify the screw shafts by modeling them as cylinders and modeling the screw-bone interface using bonded contact, to evaluate micromotion in rTSA components. The goal of this study was to evaluate the effect of three different assumptions for modeling the screw-bone interface on micromotion predictions. The credibility of these modeling assumptions was examined by comparing the micromotion rank order predicted among three different modular configurations with similar information from the literature. Eight configurations were modeled using different number of screws, glenosphere offset, and baseplate sizes. An axial compression and shear load was applied through the glenosphere and micromotion at the baseplate-bone interface was measured. Three modeling assumptions pertaining to modeling of the screw-bone interface were used and micromotion results were compared to study the effect of number of peripheral screws, eccentricities, and baseplate diameter. The relative comparison of micromotion between configurations using two versus four peripheral screws remained unchanged irrespective of the three modeling assumptions. However, the relative comparison between two inferior offsets and baseplate sizes changed depending on the modeling assumptions used for the screw-bone interface. The finding from this study challenges the generally believed hypothesis that FEA models can be used to make relative comparison of micromotion in rTSA designs as long as the same modeling assumptions are used across all models. The comparisons with previously published work matched the finding from this study in some cases, whereas the comparison was contradicting in other cases. It is essential to validate the computer modeling approach with an experiment using similar designs and methods to increase the confidence in the predictions to make design decisions.

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Mendeley readers

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The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 15%
Other 6 11%
Student > Master 5 9%
Researcher 4 7%
Student > Postgraduate 3 6%
Other 9 17%
Unknown 19 35%
Readers by discipline Count As %
Engineering 13 24%
Medicine and Dentistry 10 19%
Nursing and Health Professions 2 4%
Computer Science 1 2%
Arts and Humanities 1 2%
Other 2 4%
Unknown 25 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 September 2018.
All research outputs
#21,737,162
of 24,260,998 outputs
Outputs from Frontiers in Physiology
#10,112
of 14,867 outputs
Outputs of similar age
#294,500
of 337,101 outputs
Outputs of similar age from Frontiers in Physiology
#377
of 483 outputs
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