MétaCan
Menu
Back to cohort
Record W2905245042

AN APPROACH TO EXAMINE THE EFFECT OF TAPER ANGLE AND THREADING ON PERIPROSTHETIC BONE REMODELING FROM BONE-ANCHORED AMPUTATION PROSTHESES

2014· article· en· W2905245042 on OpenAlexvenueno aff
Anita Fung, W. Brent Edwards

Bibliographic record

VenueJournal of undergraduate research in Alberta · 2014
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
Fundersnot available
KeywordsPeriprostheticImplantMaterials scienceOsseointegrationFemurBiomedical engineeringStress shieldingBone remodelingProsthesisOrthodonticsDentistryArthroplastyMedicineSurgery
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION The most common problems experienced by transfemoral amputees using socket prostheses are soft tissue pain and a limited range of motion around the hip joint [1].  Recently, intraosseous transcutaneous amputation prostheses (ITAP) have been developed as an alternative to the standard socket prostheses for amputees.  A current shortcoming of ITAP is the change in the local mechanical loading at the bone-implant interface leading to bone resorption.  The clinical consequences of this bone loss are increased risks of bone fracture and implant loosening [2].  The purpose of this study was to develop a finite element modeling approach to examine the effect of ITAP fixture threading and taper angle on femoral bone remodeling. METHODS An intact femoral geometry was generated using Mimics software (Materialise, Leuven, Belgium) from CT scans obtained from the VAHKUM database [3]. Twelve ITAP (six threaded and six unthreaded) implants of varying taper angles were designed using SolidWorks (Waltham, MA). Implants were registered and aligned within the femoral diaphysis, and the implant-femur assembly was meshed with quadratic tetrahedral elements; elements at the bone-implant interface shared identical nodes to represent full osseointegration.  Bone elements were assigned inhomogeneous linear-elastic material properties based on CT Hounsfield units. Implant material was modeled as titanium alloy Ti6Al4V ( E =114 GPa, ν =0.3), which is commonly used for prostheses due to its superior strength and biocompatibility. Boundary conditions and loads applied to the finite element models were taken from Tomaszewski et al. [4], which were linearly scaled to correspond to an individual with a mass of 70.1 kg and a height of 170 cm.  All models were solved using ABAQUS Standard v6.1 (Providence, RI). Strain energy density was calculated for each implanted femur and compared to those of an intact femur. RESULTS Considerable energy was transferred to the ITAP (Figure 1). Consequently, the periprosthetic cortical bone in the implanted femur had a significantly lower strain energy density than that of the intact femur (Figure 1). DISCUSSION AND CONCLUSIONS It is critical that implant geometry is optimized to decrease periprosthetic bone resorption and reduce the incidence of bone fracture and implant loosening.  Changes in strain energy density following prosthetic implantation is a driving stimulus for bone remodeling, and our future work will incorporate adaptive bone remodeling algorithms into our simulations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.338
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of undergraduate research in AlbertaSame topicOrthopaedic implants and arthroplastyFrench-language works237,207