[1]陈敏,余泽芸,宋丹,等.老年膝骨关节炎合并肌少症的影响因素分析及风险预测模型构建[J].中医正骨,2025,37(03):23-28,38.
　CHEN Min,YU Zeyun,SONG Dan,et al.Influencing factors and a risk forecasting model for knee osteoarthritis complicated with sarcopenia in the aged[J].The Journal of Traditional Chinese Orthopedics and Traumatology,2025,37(03):23-28,38.
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老年膝骨关节炎合并肌少症的影响因素分析及风险预测模型构建()

《中医正骨》[ISSN:1001-6015/CN:41-1162/R]

卷:
第37卷
期数:
2025年03期
页码:
23-28,38
栏目:
临床研究
出版日期:
2025-03-20

文章信息/Info

Title:
Influencing factors and a risk forecasting model for knee osteoarthritis complicated with sarcopenia in the aged
作者:
陈敏; 余泽芸; 宋丹; 周礼; 熊小琴
宜宾市第一人民医院,四川 宜宾 644000
Author(s):
CHEN Min; YU Zeyun; SONG Dan; ZHOU Li; XIONG Xiaoqin
The First People's Hospital of Yibin,Yibin 644000,Sichuan,China
关键词:
骨关节炎; 膝;  肌肉衰减征;  老年人;  Logistic模型;  因素分析; 统计学;  列线图表;  风险;  预测
Keywords:
osteoarthritis; knee;  sarcopenia;  aged;  logistic models;  factor analysis; statistical;  nomograms;  risk;  forecasting
摘要:
目的:探讨老年膝骨关节炎(knee osteoarthritis,KOA)合并肌少症的影响因素,并构建老年KOA合并肌少症的风险预测模型。方法:选取2020年6月至2024年12月在宜宾市第一人民医院住院治疗的KOA患者为研究对象。将2020年6月至2024年6月纳入的患者归入模型组(用于模型建立),将2024年7—12月纳入的患者归入为验证组(用于模型验证)。采用亚洲肌少症工作组制定的肌少症诊断方法诊断肌少症,收集患者性别、年龄、体质量指数、KOA病程、Kellgren-Lawrence分级、蛋白质摄入量、膝关节疼痛视觉模拟量表(visual analogue scale,VAS)评分、西安大略和麦克马斯特大学骨关节炎指数(Western Ontario and McMaster Universities osteoarthritis index,WOMAC)分级、吸烟、酗酒、规范治疗、规律运动、合并基础疾病、钙剂补充、维生素D补充等信息。将模型组患者根据是否合并肌少症,分为合并肌少症组和不合并肌少症组。先对合并肌少症组和不合并肌少症组患者的相关信息进行单因素对比分析,对其中组间差异有统计学意义的因素进行Lasso回归分析,将Lasso回归分析筛选出来的因素用于多因素Logistic回归分析。采用R语言和rms程序包构建老年KOA合并肌少症的列线图预测模型。分别基于模型组和验证组数据,采用受试者操作特征(receiver operating characteristic,ROC)曲线和Hosmer-Lemeshow拟合优度检验分别评价老年KOA合并肌少症列线图预测模型的区分度和校准度。结果:共纳入模型组患者675例,其中合并肌少症组196例,不合并肌少症组479例; 纳入验证组患者77例。合并肌少症组和不合并肌少症组患者年龄、KOA病程、Kellgren-Lawrence分级、蛋白质摄入量、膝关节疼痛VAS评分、WOMAC分级、酗酒、规范治疗、规律运动、合并基础疾病、维生素D补充情况比较,组间差异均有统计学意义[(73.8±5.2)岁,(68.3±4.6)岁,t=12.921,P=0.000;(26.5±3.9)个月,(19.6±4.6)个月,t=19.768,P=0.000; χ2=16.171,P=0.000;(59.3±6.5)g·d-1,(63.9±6.3)g·d-1,t=8.475,P=0.000;(5.6±1.7)分,(4.7±1.3)分,t=7.109,P=0.000; χ2=8.627,P=0.013; χ2=8.082,P=0.004; χ2=4.076,P=0.043; χ2=10.096,P=0.001; χ2=10.822,P=0.004; χ2=7.644,P=0.006]。Lasso回归分析筛选出年龄、KOA病程、Kellgren-Lawrence分级、蛋白质摄入量、膝关节疼痛VAS评分、规律运动和 WOMAC 分级为老年KOA合并肌少症的预测变量。Logistic回归分析结果显示,年龄、KOA病程和膝关节疼痛VAS评分是老年KOA合并肌少症的危险因素,蛋白质摄入量是老年KOA合并肌少症的保护因素。采用模型组数据进行老年KOA合并肌少症列线图预测模型验证,ROC曲线下面积为0.865[P=0.000,95%CI(0.837,0.892)],采用验证组数据进行老年KOA合并肌少症列线图预测模型验证,ROC曲线下面积为0.762[P=0.000,95%CI(0.709,0.811)]; Hosmer-Lemeshow拟合优度检验结果显示,模型组最大、最小偏移量分别为0.037、0.011(P=0.885),验证组最大、最小偏移量分别为0.058、0.031(P=0.773)。结论:年龄、KOA病程和膝关节疼痛VAS评分是老年KOA合并肌少症的危险因素,蛋白质摄入量是老年KOA合并肌少症的保护因素,基于上述因素构建的老年KOA合并肌少症列线图预测模型具有较高的应用价值。
Abstract:
Objective:To explore the influencing factors of knee osteoarthritis complicated with sarcopenia in the aged,and to construct a risk prediction model for KOA complicated with sarcopenia in the aged.Methods:The KOA patients hospitalized at The First People's Hospital of Yibin from June 2020 to December 2024 were selected as the subjects.The ones admitted from June 2020 to June 2024 were assigned into the model group(for model building),while those from July 2024 to December 2024 into the validation group(for model validation).The information of the patients,including gender,age,body mass index(BMI),KOA duration,Kellgren-Lawrence(K-L)grade,protein intake,knee pain visual analogue scale(VAS)score,Western Ontario and McMaster Universities osteoarthritis index(WOMAC)grade,smoking,alcohol abuse,standardized treatment,regular exercise,combined with underlying diseases,calcium supplementation,and vitamin D supplementation,was collected,and the sarcopenia was diagnosed among the included KOA patients using the diagnostic methods developed by the Asian Working Group for Sarcopenia(AWGS).According to the results,the KOA patients with and without sarcopenia in model group were subgrouped into a sarcopenia group and a non-sarcopenia group.After that,a single-factor analysis was conducted on the extracted information of patients in the 2 subgroups,followed by a Lasso regression analysis on the factors with statistically significant differences between the 2 subgroups,based on which a multi-factor logistic regression analysis on the factors screened by Lasso regression analysis was performed.According to the findings,a nomogram prediction model for KOA complicated with sarcopenia in the aged was constructed using the R language and rms package,and the discrimination and calibration performance of the nomogram prediction model were analyzed and evaluated by using the receiver operating characteristic(ROC)curve and Hosmer-Lemeshow goodness-of-fit(GOF)test based on the data of model group and validation group,respectively.Results:Seventy-seven patients were enrolled in the validation group,and 675 ones in model group,among which 196 ones in sarcopenia group,and 479 ones in non-sarcopenia group.The single-factor analysis showed significant differences between sarcopenia group and non-sarcopenia group in the age,KOA duration,K-L grade,protein intake,knee pain VAS score,WOMAC grade,alcohol abuse,standardized treatment,regular exercise,combined with underlying diseases,and vitamin D supplementation(73.8±5.2 vs 68.3±4.6 years,t=12.921,P=0.000; 26.5±3.9 vs 19.6±4.6 months,t=19.768,P=0.000; χ2=16.171,P=0.000; 59.3±6.5 vs 63.9±6.3 g/day,t=8.475,P=0.000; 5.6±1.7 vs 4.7±1.3 points,t=7.109,P=0.000; χ2=8.627,P=0.013; χ2=8.082,P=0.004; χ2=4.076,P=0.043; χ2=10.096,P=0.001; χ2=10.822,P=0.004; χ2=7.644,P=0.006).After Lasso regression analysis,age,KOA duration,K-L grade,protein intake,knee pain VAS score,regular exercise,and WOMAC grade were identified as the variables for predicting sarcopenia in the aged KOA patients.The multi-factor logistic regression analysis showed that the age,KOA duration,and knee pain VAS score were the risk factors,while the protein intake was a protective factor for KOA complicated with sarcopenia in the aged.The area under the ROC curve of the nomogram prediction model for KOA complicated with sarcopenia in the aged validated based on the data of model group and validation group was 0.865(P=0.000,95%CI(0.837,0.892))and 0.762(P=0.000,95%CI(0.709,0.811)),respectively.The Hosmer-Lemeshow GOF test showed that the maximum and minimum offsets was 0.037 and 0.011(P=0.885),respectively,in model group,and 0.058 and 0.031(P=0.773),respectively,in validation group.Conclusion:Age,KOA duration,and knee pain VAS score are the risk factors for KOA complicated with sarcopenia,while the protein intake is a protective factor against sarcopenia in the aged KOA patients.The nomogram prediction model constructed based on the above factors has a high clinical applied value in predicting the risk for sarcopenia in the aged KOA patients.

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备注/Memo

备注/Memo:
基金项目:四川省卫生和健康委员会科研课题(21PJ011)
通讯作者:陈敏 E-mail:huaxi19796@126.com
更新日期/Last Update: 1900-01-01