Buus Amanda A Ø, Laugesen Britt, El-Galaly Anders, Laursen Mogens, Hejlesen Ole K
Department of Orthopaedic Surgery, Aalborg University Hospital, Aalborg, Denmark.
Nursing Research Unit, Aalborg University Hospital & Center for Clinical Guidelines, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark; Center for Clinical Guidelines, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.
Int J Orthop Trauma Nurs. 2022 May;45:100919. doi: 10.1016/j.ijotn.2021.100919. Epub 2021 Dec 22.
Subdividing 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.
To 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.
This 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.
The 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 R was 0.322 and 0.334, respectively.
The 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.
将牛津膝关节评分（OKS）细分为疼痛分量表（OKS - PCS）和功能分量表（OKS - FCS）以预测具有临床意义的改善情况，可为识别那些在全膝关节置换术后需要医疗保健专业人员加强支持以应对疼痛和功能挑战的患者提供依据。
通过比较从OKS中提取疼痛和功能的两种不同版本，评估将OKS细分为子量表以预测术前和术后疼痛及功能具有临床意义的改善情况的潜力。
这项回顾性观察性队列研究纳入了201例行全膝关节置换术的患者。采用多元逻辑回归分析对患者在疼痛和功能方面是否实现具有临床意义的改善进行二元分类。
预测具有临床意义改善的最佳总体版本，其疼痛和功能的受试者工作特征曲线下面积均为0.79，而纳格尔克R分别为0.322和0.334。
研究结果表明，将OKS细分为子量表以预测疼痛和功能具有临床意义的改善是合理的。然而，需要更多研究在更大的患者群体中比较各种类型的分类算法。
