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      Predicting the Outcome of Total Knee Arthroplasty Using the WOMAC Score: A Review of the Literature

      1 , 1 , 1
      The Journal of Knee Surgery
      Georg Thieme Verlag KG

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          Abstract

          It is estimated that up to a third of recipients of total knee arthroplasty (TKA) experience chronic pain postoperatively. However, there are no clear indications within the literature that predict which patients are at higher risk of being dissatisfied with their TKA. The Western Ontario and McMaster University Osteoarthritis Index (WOMAC) is one of the most commonly used, patient-reported outcome measures in patients with lower limb osteoarthritis. This review discusses the available evidence surrounding the predictability of the outcome of TKA using the WOMAC score as well as considering further patient factors that have been implicated in the level of improvement post TKA. It may be concluded from the available literature that a combination of knee scores and patient factors would be the most accurate way of predicting those patients most likely to have a good outcome from their TKA. There is some disparity within the literature about which patient factors and reported outcome measure scores lead to a positive postoperative outcome. Patient expectations following the procedure also need to be evaluated, as objective measures on a scoring system do not necessarily equate with the subjective patient experience.

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          Author and article information

          Journal
          The Journal of Knee Surgery
          J Knee Surg
          Georg Thieme Verlag KG
          1538-8506
          1938-2480
          August 02 2019
          August 2019
          July 10 2018
          August 2019
          : 32
          : 08
          : 736-741
          Affiliations
          [1 ]Department of Orthopaedics, Newcastle upon Tyne Hospitals Foundation Trust, Freeman Hospital, Newcastle upon Tyne, United Kingdom
          Article
          10.1055/s-0038-1666866
          29991079
          442c829f-6777-427f-b701-e85c6801b853
          © 2019
          History

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