ArticleAnnals of biomedical engineering2021
Enhanced In-Silico Polyethylene Wear Simulation of Total Knee Replacements During Daily Activities.
Article in Annals of biomedical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 18 citations in OpenAlex.
- Gait-to-Contact (G2C): A Novel Deep Learning Framework to Predict Total Knee Replacement Wear from Gait Patterns.Annals of biomedical engineering · 2026Article
- Experimental and computational evaluation of knee implant wear and creep under in vivo and ISO boundary conditions.Biomedical engineering online · 2024Article
- [Effect of prosthetic joint line installation height errors on insert wear in unicompartmental knee arthroplasty].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023Article
- Comparison of Kinematics and Contact Mechanics in Normal Knee and Total Knee Replacements: A Computational Investigation.Annals of biomedical engineering · 2021Article
- Using Musculoskeletal Models to EstimateFrontiers in bioengineering and biotechnology · 2021Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
A computational wear simulator is an efficient tool for evaluating the wear of artificial knee joints. The classical Archard's wear law-based simulator has questionable accuracy and is focused on walking. In this study, an in silico polyethylene wear simulation of total knee replacements was developed considering the various highly demanding daily activities. A good predicted accuracy (error = 8.1%) was found through comparison of the experimental results. A relatively larger averaged wear loss was found under the loading condition (1.53 mg/mc) of daily activities compared with the walking condition (1.32 mg/mc). The squatting movement (2.57 mg/mc) produces the highest overall wear rate. In addition, a relatively larger amount of wear was found on the medial side knee prosthesis than that on the lateral side. The enhanced in silico polyethylene wear simulator provides an accurate and comprehensive tool for wear prediction in preclinical wear testing.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.