Song Jiulong, Ye Ziqi, Li Wen, Chen Zihao, Wang Xinwei, Chen Wei
College of Physical Education, Yangzhou University, Yangzhou, Jiangsu, China.
Department of Rehabilitation Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China.
PLoS One. 2025 May 8;20(5):e0319482. doi: 10.1371/journal.pone.0319482. eCollection 2025.
Knee osteoarthritis (OA) is a common chronic condition among the elderly, leading to a decline in OA patients' quality of life. This study aimed to investigate the relationship between radiographic severity and health-related quality of life (HRQoL) in elderly women with knee OA.
A total of 80 elderly women with knee OA were enrolled in this study. Radiographic severity was assessed with the Kellgren-Lawrence (K/L) scale, we divided the subjects into early (1-2) and late (3-4) according to the K/L stage. HRQoL assessment was conducted using the MOS item Short-Form 36 (SF-36). The association of HRQoL with knee OA severity was estimated using logistic regression. Applied a random forest model to assess the importance and accuracy of relevant variables in the occurrence of OA. The LASSO (Least Absolute Shrinkage and Selection Operator) regression was then used to identify key factors associated with OA, which were incorporated into the development of a risk prediction nomogram model. Furthermore, a receiver operating characteristic (ROC) curve was constructed to evaluate the model's discriminative ability for OA.
The mean age of the patients was 64.7 ± 6.74 years, and the mean course of disease was 5.01 ± 2.12 years. HRQoL score (SF-36 PCS and MCS) was significantly worse in the late-stage group compared to the early group (p < 0.05). The late group K/L scale has a negative correlation with SF-36 PCS (r = -0.598) and MCS (r = -0.625) and a strong positive correlation. In logistic regression analysis, the K/L scale were significantly associated with SF-36MCS (OR = 0.86, p = 0.041), SF-36 PCS (OR = 0.85, p = 0.025) and TUG (OR = 1.80, p = 0.001). The nomogram model based on key OA risk factors identified by LASSO regression demonstrated substantial predictive value for OA, with an area under the curve (AUC) of 72.2%.
The radiographic severity of knee OA was correlated with health-related quality of life. The HRQoL is an important predictive indicator of the severity of knee OA severity, which might provide beneficial management and treatment for patients with knee OA.
膝关节骨关节炎(OA)是老年人常见的慢性疾病,会导致OA患者生活质量下降。本研究旨在调查老年女性膝关节OA的影像学严重程度与健康相关生活质量(HRQoL)之间的关系。
本研究共纳入80名老年女性膝关节OA患者。采用Kellgren-Lawrence(K/L)量表评估影像学严重程度,根据K/L分期将受试者分为早期(1-2期)和晚期(3-4期)。使用MOS条目简明健康调查36项量表(SF-36)进行HRQoL评估。采用逻辑回归估计HRQoL与膝关节OA严重程度的关联。应用随机森林模型评估相关变量在OA发生中的重要性和准确性。然后使用LASSO(最小绝对收缩和选择算子)回归识别与OA相关的关键因素,并将其纳入风险预测列线图模型的构建中。此外,构建受试者工作特征(ROC)曲线以评估该模型对OA的判别能力。
患者的平均年龄为64.7±6.74岁,平均病程为5.01±2.12年。与早期组相比,晚期组的HRQoL评分(SF-36生理健康综合评分和心理健康综合评分)明显更差(p<0.05)。晚期组的K/L量表与SF-36生理健康综合评分(r=-0.598)和心理健康综合评分(r=-0.625)呈负相关且相关性较强。在逻辑回归分析中,K/L量表与SF-36心理健康综合评分(OR=0.86,p=0.041)、SF-36生理健康综合评分(OR=0.85,p=0.025)和定时起立行走测试(OR=1.80,p=0.001)显著相关。基于LASSO回归确定的关键OA风险因素构建的列线图模型对OA具有显著的预测价值,曲线下面积(AUC)为72.2%。
膝关节OA的影像学严重程度与健康相关生活质量相关。HRQoL是膝关节OA严重程度的重要预测指标,可为膝关节OA患者提供有益的管理和治疗。