摘要
目的评估类风湿关节炎(RA)患者发生骨折的危险因素,建立回归方程,预测RA患者骨折的风险。方法设计专门的登记表,随机现场调查全国多中心9省市18个医院门诊及住院RA患者681例,收集的资料包括年龄、性别、病程、关节受累表现、治疗情况、骨折的发生情况等,采用Logistic回归分析进行统计学处理。结果类风湿关节炎患者骨折的危险因素为:性别(X1)、RA家族史(X2)、病程(X3)、畸形关节数(X4)、SF-36评分(X5);RA患者骨折的回归方程建立:logit(P)=-0.838X1+0.789X2+0.219X3+0.041X4+0.017X5-4.217;RA患者骨折的危险因素比较:用标准化回归系数作比较,性别为0.185,RA家族史为0.139,病程为0.197,畸形关节数为0.162,可见病程对骨折发生的影响最大。结论 RA患者骨折的发生是由诸多因素造成的,男性、病程长、畸形关节数多及RA家族史阳性是骨折的危险因素,通过回归方程能够预测RA患者发生骨折的危险性。
Objective To evaluate the risk factors and to predict the risk of fractures in patients with rheumatoid arthritis (RA) by establishing a regression equation. Methods 681 RA patients were randomly selected from wards or clinics of 18 hospitals in 9 provinces/cities across China. By using a pre-designed information card, we col- lected data from these patients including age, gender, disease duration, involvement of joints, treatment, and fractures, which were then processed with Logistic regression analysis. Results The risk factors of fractures in RA patients were gender (Xl), a family history of RA (X2), disease duration (X3), the number of deformed joints (X4) and SF-36 score (Xs). Establishment of the regression equation of fracture in RA patients : logit (P) =-0.838Xj +0.789X2 +0.219X3 +0.041X4+ 0.017X5-4.217. Contribution to the risk of fracture in RA patients in standardized regression coefficients were 0.185 by gender, 0.139 by family history of RA, 0.197 by disease duration and 0.162 by number of deformed joints. Obviously, disease duration had the greatest impact on the occurrence of fracture. Conclusion The occurrence of fractures in patients with RA is caused by various factors. Male, long disease duration, more deformed joints and positive family history of RA are risk factors. Risk of fractures can be predicted with regression equation.
出处
《中国药物与临床》
CAS
2011年第11期1241-1243,共3页
Chinese Remedies & Clinics
基金
国家"十一五"科技支撑计划项目(2008Bai59B01)
山西省教育厅科技项目(20111107)
山西省科技厅攻关项目(20110313013-1)
太原市科技局项目(11016212)
关键词
关节炎
类风湿
骨质疏松
骨折
回归分析
Arthritis,rheumatoid
Osteoporosis
Fractures
Regression analysis