髌股疼痛综合征X线特征与三种评分系统的多元线性回归分析

Multiple linear regression analysis of the X-ray measurement and WOMAC,KUJALA,MELBOURNE scores of patellofemoral pain syndrome

目的采用X线测量发生髌股疼痛综合征(PFPS)膝关节的相关影像学参数,并分别与WOMAC、KUJALA和MELBOURNE评分系统进行多元线性回归分析。方法筛选出49例(51膝)膝关节选取和PFPS相关的10项参数进行测量:股骨远端外翻角(DFVA,X1)、胫骨近端内翻角(PTVA,X2)、股骨角(FA,X3)、胫骨角(TA,X4)、胫股角(TFA,X5)、Insall-Salvati指数(ISR,X6)、沟角(SA,X7)、外侧髌骨角(LPA,X8)、适合角(CA,X9)、髌股指数(PI,X10),并进行WOMAC、KUJALA和MELBOURNE评分,应用多元线性回归方程分析影像学参数与评分之间的相关性。结果 3组多元线性回归方程均有统计学意义(P<0.05),WOMAC评分多元回归方程:Y=-213.742+2.011X5,F=3.960,R2=0.494;KUJALA评分多元回归方程:Y=125.835-24.475X6-0.341X7-0.992X8,F=32.732,R2=0.891;MELBOURNE评分多元回归方程:Y=51.66-16.329X6-5.47X10,F=22.178,R2=0.856。结论①膝关节X线测量数据在一定程度上反映3项评分及膝关节功能的情况;②KUJALA评分能较全面地评估PFPS,轴位X线片上Insall-Salvati指数、沟角、外侧髌股角较为重要,可用于临床评估PFPS患者在治疗前后的功能恢复情况;③由于KUJALA和MELBOURNE评分的决定系数较大,回归系数标准误较小,从而在临床上通过统计控制确定评分值来评估影像学参数。

Objective To perform multiple linear regression analysis of X ray measurement and WOMAC, KUJALA and MELBOURNE scores of patellofemoral pain syndrome （PFPS） knee joints. Methods A total of 49 patients （51 knees） were reviewed according to inclusion and exclusion criteria. 10 parameters were chosen including distal femoral valgus angle （DF- VA ,Xl）, proximal tibial varus angle （PTVA ,X,.）, femoral angle （FA,X3）, tibia angle （TA ,X4）, tibiofemoral angle（TFA,Xs）, Insall-Salvati ratio （ISR,X6）, sulcus angle （SA,XT）, lateral patellofemoral angle （LPA,Xs）, congruence angle （CA,Xg） and patellofemoral index（PI ,X10） which all were related to patellofemoral pain syndrome. These data were obtained from PACS 3.0 imaging software. The WOMAC, KUJALA, MELBOURNE scores were collected. Then multiple regression equations were applied for the linear regression analysis of correlation between the X ray measurement and WOMAC, KUJALA, MELBOURNE scores. Results There were statistical significance in these three multiple regression equations （P 〈0.05）. WOMAC score multiple regression equation was Y=-213.742 ＋2.011X5, F =3.960, R2 =0.494. It was Y=125.835-24.475X6-0.341XT-0.992Xs, F =32.732, R2 =0.891 for KUJALA. MULBOURNE＇s equation was Y =51.66-16.329Xt-5.47Xx0, F =22.178, R2- =0.856. Conclusion （1）X ray measurement of knee joint can reflect these three scores to a certain extent. （2）KUJALA score is better than WOMAC and MULBOURNE scores for its more comprehensive evaluation to PFPS. Axial slices ISR,SA,LPA should be addressed and applied to compare the recovery of PFPS patients before and after treatment. （3）Due to their bigger determination coefficient and smaller standard errors of the regression coefficients, KUJALA and MULBORNE scores can be used to determine the scores by statistical control to evaluate the imaging parametels.