The predictive effect of Kellgren-Lawrence grade and joint space height on pain and functional outcome

Kellgren-Lawrence分级和关节间隙高度对疼痛和功能结果的预测作用

阅读:1

Abstract

BACKGROUND: Plain radiographs play a key role in the diagnosis of knee osteoarthritis (OA), with the Kellgren-Lawrence (KL) grading system being widely used to assess radiographic severity of the disease. Previous studies have suggested that radiographically less severe knee OA may be associated with inferior outcomes following total knee replacement (TKA). This study aimed to evaluate whether preoperative radiological findings are predictive of postoperative Oxford Knee Score (OKS) and residual knee pain after primary TKA. METHODS: We retrospectively included all patients who underwent TKA at our high-volume joint replacement center in 2018. The primary outcome was the OKS collected at one year postoperatively. The secondary outcome was patient-reported knee pain at one year. Preoperative plain radiographs were graded using the KL classification, and joint space height was measured. Additional covariates included age, gender, BMI, ASA score, and specific comorbidities. Multivariable analyses were performed, and model performance was assessed using R(2) and variable importance metrics. RESULTS: A total of 1,401 patients were included. Patients with less severe osteoarthritis had lower postoperative OKS compared to those with more advanced disease. Similarly, a greater joint space height was associated with smaller improvements in OKS following TKA. In multivariable models, the R(2) was 0.125 for postoperative OKS and 0.075 for residual pain. KL grade, joint space height, and mechanical axis were combined as an interaction term. CONCLUSION: In this large single-center cohort, comprehensive clinical and radiographic data were analyzed using advanced statistical methods. Our findings support previous evidence suggesting that comparatively less severe radiographic OA is associated with less favorable outcomes after TKA. However, the limited predictive capacity of the models highlights the multifactorial nature of postoperative outcomes and the challenges faced in forecasting patient-reported results following TKA.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。