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首页> 外文期刊>Gait & posture >A multivariate statistical ranking of clinical and gait measures before and after total knee replacement.
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A multivariate statistical ranking of clinical and gait measures before and after total knee replacement.

机译：全膝关节置换前后临床和步态测量的多变量统计排名。

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The purpose of this study was to assess the use of a multivariate statistical method to rank clinical and gait variables, thus describing a ranking of patient dysfunction prior to and following total knee replacement (TKR) surgery. Twenty end-stage knee osteoarthritis (KOA) subjects scheduled for TKR and 20 healthy controls performed level walking and stair ascent twice: pre- (P1) and 6 months post-surgery (P2). Clinical and gait measures were entered into a principle component analysis (PCA) to determine orthogonal principle components (PCs). The PCs were entered into a discriminant function analysis to determine the best predictors of group membership. The PCA extracted three PCs for both the P1 and P2 data sets. Three orthogonal dimensions were formed: "knee dysfunction", "gait dysfunction", and "stair ascent dysfunction". For P1 the "knee dysfunction" dimension composed of both subjective and objective measures, best discriminated between end-stage knee osteoarthritis patients and controls. For P2, the "stair ascent dysfunction" dimension best discriminated between 6 months post-TKR patients and controls. The results of this study suggest that a multivariate statistical method provides a clinically relevant ranking of patient dysfunction prior to and following TKR. This ranking of dysfunction could serve to identify rehabilitation priorities.
机译：这项研究的目的是评估使用多元统计方法对临床和步态变量进行排名，从而描述在全膝关节置换术（TKR）手术前后患者功能障碍的等级。计划进行TKR的20名末期膝关节骨关节炎（KOA）受试者和20名健康对照者两次进行水平步行和爬楼梯：手术前（P1）和手术后6个月（P2）。将临床和步态测量方法纳入主成分分析（PCA），以确定正交主成分（PC）。将PC进行判别功能分析，以确定组成员身份的最佳预测指标。 PCA为P1和P2数据集提取了三台PC。形成了三个正交的维度：“膝关节功能障碍”，“步态功能障碍”和“楼梯上升功能障碍”。对于P1，“膝关节功能障碍”维度包括主观和客观指标，可以最好地区分终末期膝骨关节炎患者和对照组。对于P2，最好在TKR后6个月的患者和对照组之间区分“阶梯上升功能障碍”。这项研究的结果表明，多元统计方法可为TKR之前和之后的患者功能障碍提供临床相关的排名。这种功能障碍的分级可以用来确定康复的重点。

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