Li Ying, Guo Yabin, Zhao Peipei, Zeng Biyun, Zhou Yang
School of Nursing, Sun Yat-Sen University, Guangzhou, China.
Teaching and Research Section of Clinical Nursing, Xiangya Hospital of Central South University, 87 Xiangya Road, Kaifu District, Changsha, Hunan Province, China.
J Orthop Surg Res. 2024 Dec 23;19(1):866. doi: 10.1186/s13018-024-05349-9.
This study aims to identify predictors of knee osteoarthritis (KOA) risk in middle-aged population, construct and validate a nomogram for KOA in this demographic.
From June to December 2020, we conducted a cross-sectional survey on 5,527 middle-aged individuals from Changsha and Zhangjiajie cities in Hunan Province, selected using a stratified multi-stage random sampling method. Data collection involved a structured questionnaire encompassing general demographic, physical condition, and lifestyle behaviors dimensions. The dataset was randomly split into a training set (n = 3868) and a validation set (n = 1659) at a 7:3 ratio via computerized randomization. We analyzed the prevalence of self-reported KOA and identified its influencing factors using logistic regression. A nomogram was constructed based on these "three-dimensional" factors. Subsequent validation was conducted, and the nomogram's performance was further evaluated through ROC curves, C-index, Hosmer-Lemeshow test, and calibration curves.
The self-reported prevalence of KOA in the middle-aged population was 11.4% (632/5527). The risk factor with the greatest impact is: diagnosed with osteoporosis(95% CI 2.269-3.568, OR = 2.845), followed by age between 51 to 60 years (95% CI 2.176-3.151, OR = 2.619), diagnosed with hypertension(95% CI 1.633-2.499, OR = 2.02), diagnosed with diabetes (OR = 1.689), ethnic Han Chinese (OR = 1.673), exercise according to physical condition (OR = 1.643), pay attention to keeping the knee joint warm (OR = 1.535), eating habits are mainly light vegetables (OR = 1.374), male gender (OR = 1.343), drink occasionally in small amounts (OR = 1.286); a higher level of education (OR = 0.477) and frequently or always apply an external or plaster to relieve symptoms after knee discomfort (OR = 0.377; OR = 0.385) are protective factors. The C-index of the training set model was 0.8107 (95% CI: 0.8102-0.8111), with a statistically significant area under the ROC curve (AUC = 0.818), and the calibration curve showed a good fit. The C-index for the validation set was 0.8124 (95% CI: 0.8109-0.8140), with an AUC of 0.812. The Hosmer-Lemeshow test resulted in a P-value of 0.46 (P ≥ 0.05)indicating good calibration of the model.
The three dimensions nomogram generated in this study was a valid and easy-to-use tool for assessing the risk of KOA in middle-aged population, and helped healthcare professionals to screen the high-risk population.
本研究旨在确定中年人群膝骨关节炎(KOA)风险的预测因素,构建并验证该人群KOA的列线图。
2020年6月至12月,我们采用分层多阶段随机抽样方法,对湖南省长沙市和张家界市的5527名中年个体进行了横断面调查。数据收集涉及一份结构化问卷,涵盖一般人口统计学、身体状况和生活方式行为等方面。通过计算机随机化,将数据集以7:3的比例随机分为训练集(n = 3868)和验证集(n = 1659)。我们分析了自我报告的KOA患病率,并使用逻辑回归确定其影响因素。基于这些“三维”因素构建了列线图。随后进行了验证,并通过ROC曲线、C指数、Hosmer-Lemeshow检验和校准曲线进一步评估列线图的性能。
中年人群自我报告的KOA患病率为11.4%(632/5527)。影响最大的风险因素为:诊断为骨质疏松(95%CI 2.269 - 3.568,OR = 2.845),其次是年龄在51至60岁之间(95%CI 2.176 - 3.151,OR = 2.619),诊断为高血压(95%CI 1.633 - 2.499,OR = 2.02),诊断为糖尿病(OR = 1.689),汉族(OR = 1.673),根据身体状况进行锻炼(OR = 1.643),注意保持膝关节温暖(OR = 1.535),饮食习惯以清淡蔬菜为主(OR = 1.374),男性(OR = 1.343),偶尔少量饮酒(OR = 1.286);较高的教育水平(OR = 0.477)以及在膝关节不适后经常或总是使用外用药物或膏药缓解症状(OR = 0.377;OR = 0.385)是保护因素。训练集模型的C指数为0.8107(95%CI:0.8102 - 0.8111),ROC曲线下面积具有统计学意义(AUC = 0.818),校准曲线显示拟合良好。验证集的C指数为0.8124(95%CI:0.8109 - 0.8140),AUC为0.812。Hosmer-Lemeshow检验的P值为0.46(P≥0.05),表明模型校准良好。
本研究生成的三维列线图是评估中年人群KOA风险的有效且易于使用的工具,有助于医疗保健专业人员筛查高危人群。