Evaluation of unicompartmental knee arthroplasy using a finite element method

Chien Wei Liu, Ching Sung Wang, Chien Tsu Chen, Chia Chi Lo

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The advanced development of unicompartmental knee arthroplasty (UKA) has provided patients with single compartment knee disease a treatment option besides high tibial osteotomy (HTO) and total knee arthroplasty (TKA). Previous clinical studies of UKA suggested osteolysis and aseptic loosening caused by the wear of polyethylene (PE) tibial components remained a problem. Further study and discussion should be conducted on the reduction and avoidance of the polyethylene tibial components damage. This study employed the finite element analysis. The results indicate that excessive activity and body weight and undercorrection of varus and tibial plateau malresection had contributed to the wear of polyethylene tibial components in unicompartmental knee prostheses (UKP). Of these, excessive activity and excessive body weight had more significant impact. The changes in thickness and angle of posterior slope had no significant impact on the wear of polyethylene tibial components. The results obtained from cross-tabulation analysis of multivariate showed that the achievement of the excellent long-term results and the reduction in the incidence of second replacement surgery relied on the evaluation of patients' body weight and daily activities in addition to the improvement in the accuracy of alignment between components and surgical precision. This study recommends that arthritis patients weighing more than 56 kg or the loading of unicompartment exceeding 800 N should not consider UKA as a treatment option at this stage.

Original languageEnglish
Pages (from-to)508-511
Number of pages4
JournalAdvanced Science Letters
Volume4
Issue number2
DOIs
Publication statusPublished - Feb 2011

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Keywords

  • Fea
  • Tibial component
  • Unicompartmental knee
  • Varus knee

ASJC Scopus subject areas

  • Education
  • Health(social science)
  • Mathematics(all)
  • Energy(all)
  • Computer Science(all)
  • Environmental Science(all)
  • Engineering(all)

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