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作 者:王霞[1] 张子云 娄雪娇 张利娟 张黎[1] 毛慧慧 闫翠萍[3] 张蓉[4] 王莉[5] 黄琼 常彩云[7] 胡聂[8] 杨佳明 Wang Xia;Zhang Ziyun;Lou Xuejiao;Zhang Lijuan;Zhang Li;Mao Huihui;Yan Cuiping;Zhang Rong;Wang Li;Huang Qiong;Chang Caiyun;Hu Nie;Yang Jiaming(Department of Rheumatology and Immunology,Tongji Hospital Affiliated to Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China)
机构地区:[1]华中科技大学同济医学院附属同济医院风湿免疫内科,湖北武汉430030 [2]恩施州中心医院 [3]宜昌市第一人民医院 [4]荆州市中心医院 [5]荆州市第一人民医院 [6]湖北民族学院附属民大医院 [7]宜昌市中心人民医院 [8]武汉大学中南医院 [9]天门市第一人民医院
出 处:《护理学杂志》2022年第20期28-33,共6页Journal of Nursing Science
摘 要:目的探讨类风湿关节炎患者躯体功能受限的危险因素,构建类风湿关节炎患者躯体功能受限风险预测列线图模型。方法采取便利抽样选取湖北省9所三级甲等医院风湿免疫科的628例类风湿关节炎住院患者作为建模组,采用一般资料问卷、健康评估问卷-残疾指数(HAQ-DI)和医院焦虑抑郁量表(HADS)进行横断面调查。应用logistic回归模型分析类风湿关节炎患者躯体功能受限的危险因素,应用R软件构建预测类风湿关节炎患者躯体功能受限风险的列线图模型,并在88例患者中进行验证。结果共508例类风湿关节炎患者存在躯体功能受限。logistic回归分析结果显示,民族、饮酒、疾病活动度评分、年龄、住院次数和焦虑评分是患者功能受限的风险因素。对列线图模型进行内部验证,ROC曲线下面积为0.811;校准曲线接近理想曲线;外部验证结果显示ROC曲线下面积为0.862。结论构建的类风湿关节炎患者躯体功能受限风险预测模型具有较好的区分度和校准度,可个体化预测临床类风湿关节炎患者躯体功能受限风险,以便采取针对性干预措施。Objective To explore the risk factors of impaired physical function(IPF)in patients with rheumatoid arthritis(RA),and to construct a nomogram model for predicting the risk of IPF in RA patients.Methods A total of 628 hospitalized RA patients from 93A hospitals in Hubei province were selected by convenience sampling.The general information questionnaire,the Health Assessment Questionnaire Disability Index(HAQ-DI)and the Hospital Anxiety and Depression Scale(HADS)were used for cross-sectional survey.Logistic regression model was used to analyze the risk factors of IPF in the RA patients.R software was used to construct a nomogram model,which was later validated in another sample of 88 RA patients.Results A total of 508 RA patients had IPF.Multivariate logistic regression analysis showed that ethnicity,alcohol drinking,disease activity score,age,hospitalization times and anxiety score were risk factors of IPF.The area under the ROC curve of the nomogram model was 0.811;the calibration curve was close to the ideal curve.External validation results showed that the area under ROC curve was 0.862.Conclusion The risk prediction model of IPF of RA patients constructed has good discrimination and calibration,which can provide reference for clinical individualized prediction of IPF risk of RA patients,and is helpful for intervention of RA patients.
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