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Table 3 Factors affecting the amount of changes of joint-line convergence angle (JLCA)

From: Change of joint-line convergence angle should be considered for accurate alignment correction in high tibial osteotomy

Parameters Correlation coefficient with ΔJLCA (P value) Risk of JLCA decrease ≥ 2°: OR (95% CI, P value)
Univariable Multivariable
Demographic factors
 Age 0.175 (0.121) 0.960 (0.889–1.036, 0.294)  
 Sex (female) 0.136 (0.231)a 3.462 (0.416–28.819, 0.251)  
 Height − 0.012 (0.914) 1.004 (0.938–1.074, 0.912)  
 Weight − 0.136 (0.230) 1.022 (0.979–1.067, 0.324)  
 BMI − 0.192 (0.089) 1.107 (0.959–1.276, 0.164)  
Radiographic parameters
 Preoperative mFTA 0.497 (< 0.001) 0.651 (0.525–0.809, < 0.001)
 Preoperative mLDFA − 0.179 (0.113) 1.209 (0.913–1.600, 0.185)  
 Preoperative mMPTA 0.136 (0.228) 0.765 (0.571–1.024, 0.072)  
 Preoperative JLCA (standing) − 0.724 (< 0.001) 7.181 (2.711–19.021, < 0.001) 4.429 (1.350–14.534, 0.014)
 Preoperative JLCA (supine) − 0.227 (0.043) 1.718 (1.006–2.932, 0.047)
 Difference of JLCA standing and supine − 0.755 (< 0.001) 22.679 (4.415–116.490, < 0.001) 11.74 (1.770–77.886, 0.011)
 Preoperative TPS − 0.083 (0.465) 1.110 (0.926–1.332, 0.260)  
 Postoperative mFTA 0.018 (0.875) 0.896 (0.728–1.102, 0.299)  
 Postoperative mMPTA − 0.232 (0.039) 1.178 (0.973–1.426, 0.093)  
 Postoperative JLCA (standing) 0.097 (0.394) 1.340 (0.805–2.230, 0.260)  
 Postoperative JLCA (supine) − 0.053 (0.642) 1.178 (0.711–1.954, 0.525)  
 Postoperative TPS − 0.121 (0.286) 1.127 (0.946–1.343, 0.180)  
 Change of mFTA − 0.457 (< 0.001) 1.360 (1.135–1.629, 0.001)
 Change of mMPTA − 0.298 (0.007) 1.282 (1.062–1.547, 0.010)
 Change of TPS − 0.049 (0.669) 1.032 (0.860–1.240, 0.733)  
  1. JLCA joint-line convergence angle, ΔJLCA the amount of change of the JLCA after high tibial osteotomy, OR odds ratio, CI confidence interval, BMI body mass index, mFTA mechanical femorotibial angle, mLDFA mechanical lateral distal femoral angle, mPTA mechanical proximal tibial angle; TPS tibial posterior slope
  2. aSpearman’s correlation analysis