Demographic characteristics of the patients.

Background and aims 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. Methods 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. Result 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%. Conclusion 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.研究背景与目的 膝骨关节炎（Knee Osteoarthritis, OA）是老年人群中常见的慢性疾病，会降低患者的生活质量。本研究旨在探讨老年女性膝骨关节炎患者的影像学严重程度与健康相关生活质量（Health-related Quality of Life, HRQoL）之间的关联。 研究方法 本研究共纳入80例老年女性膝骨关节炎患者。采用Kellgren-Lawrence（K/L）分级量表评估影像学严重程度，并依据K/L分期将受试者分为早期（1~2级）与晚期（3~4级）两组。采用医学结局研究简表36（Medical Outcomes Study Short-Form 36, SF-36）开展健康相关生活质量评估。采用logistic回归分析评估健康相关生活质量与膝骨关节炎严重程度的关联。应用随机森林（Random Forest）模型评估与膝骨关节炎发生相关变量的重要性及预测精度。随后采用最小绝对收缩和选择算子（Least Absolute Shrinkage and Selection Operator, LASSO）回归分析筛选与膝骨关节炎相关的关键危险因素，并以此构建风险预测列线图模型。此外，绘制受试者工作特征（Receiver Operating Characteristic, ROC）曲线以评估该模型对膝骨关节炎的区分能力。 研究结果 患者的平均年龄为64.7±6.74岁，平均病程为5.01±2.12年。晚期组的健康相关生活质量评分（SF-36躯体健康总评PCS与精神健康总评MCS）显著差于早期组（p<0.05）。K/L分期与SF-36 PCS（r=-0.598）及MCS（r=-0.625）呈负相关，且相关性较强。Logistic回归分析显示，K/L分期与SF-36精神健康总评（MCS，OR=0.86，p=0.041）、躯体健康总评（PCS，OR=0.85，p=0.025）及计时起身行走试验（Timed Up and Go, TUG）均存在显著关联。基于LASSO回归筛选的膝骨关节炎关键危险因素构建的列线图模型对膝骨关节炎具有良好的预测价值，曲线下面积（Area Under the Curve, AUC）为72.2%。 研究结论 膝骨关节炎的影像学严重程度与健康相关生活质量存在相关性。健康相关生活质量是评估膝骨关节炎严重程度的重要预测指标，可为膝骨关节炎患者的临床管理与治疗提供有益参考。