The potential of dividing the oxford knee score into subscales for predicting clinically meaningful improvements in pain and function of patients undergoing total knee arthroplasty

Abstract

BackgroundSubdividing the Oxford Knee Score (OKS) into a pain component scale (OKS-PCS) and a function component scale (OKS-FCS) for predicting clinically meaningful improvements may provide a basis for identifying patients in need of enhanced support from health care professionals to manage pain and functional challenges following total knee arthroplasty. AimTo assess the potential of dividing the OKS into subscales for predicting clinically meaningful improvements in pre- and postoperative pain and function by comparing two different versions of extracting pain and function derived from the OKS. MethodsThis retrospective observational cohort study included 201 patients undergoing total knee arthroplasty. Multiple logistic regression analysis was applied for binary classification of whether patients achieved clinically meaningful improvements in pain and function. ResultsThe best overall version for predicting clinically meaningful improvements had an area under the receiver operating characteristic curve of 0.79 for both pain and function, whereas Nagelkerke's R2 was 0.322 and 0.334, respectively. ConclusionThe findings indicate that it is reasonable to subdivide the OKS into subscales for predicting clinically meaningful improvements in pain and function. However, more studies are needed to compare various types of classification algorithms in larger patient populations.