The Strongest Oxford Knee Score Predictors of Subsequent Revision are Overall Pain, Limping When Walking, and Knee Giving Way

Background: The Oxford Knee Score (OKS) is used to measure knee arthroplasty outcomes; however, it is unclear which questions are more relevant. Our aims were to (1) identify which OKS question(s) were the strongest predictors of subsequent revision and (2) compare the predictive ability of the pain and function domains. Methods: All primary total knee arthroplasties (TKAs) and unicompartmental knee arthroplasties (UKAs) in the New Zealand Joint Registry between 1999 and 2019 with an OKS at 6 months (TKA n = 27,708; UKA n = 8,415), 5 years (TKA n = 11,519; UKA n = 3,365) or 10 years (TKA n = 6,311; UKA n = 1,744) were included. Prediction models were assessed using logistic regressions and receiver operating characteristic analyses. Results: A reduced model with 3 questions (overall pain, limping when walking, knee giving way) showed better diagnostic ability than full OKS for predicting UKA revision at 6 months (area under the curve [AUC]: 0.80 versus 0.78; P <.01) and 5 years (0.81 versus 0.77; P = .02), and comparable diagnostic ability for predicting TKA revision at all time points (6 months, 0.77 versus 0.76; 5 years, 0.78 versus 0.75; 10 years, 0.76 versus 0.73; all not significant), and UKA revision at 10 years (0.80 versus 0.77; not significant). The pain domain had better diagnostic ability for predicting subsequent revision for both procedures at 5 and 10 years. Conclusion: Questions on overall pain, limping when walking, and knee giving way were the strongest predictors of subsequent revision. Attention to low scores from these questions during follow-up may allow for prompt identification of patients most at risk of revision. (c) 2023 Elsevier Inc. All rights reserved.

Automated summary

This study analyzed data from the New Zealand Joint Registry and found that overall pain, limping when walking, and knee giving way were the strongest predictors of subsequent knee arthroplasty revision. Paying attention to these issues can help identify patients at highest risk of revision.