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Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_9 | Pages 89 - 89
1 May 2016
Megahed R Stocks O Ismaily S Stocks G Noble P
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Introduction

The success of knee replacement surgery depends, in part, on restoration of the correct alignment of the leg with respect to the load-bearing vector passing from the hip to the ankle (the mechanical axis). Conventional thinking is that the correct angle of resection of the distal femur (Valgus Cut Angle, VCA) depends on femoral length or femoral offset, though femoral bowing, in addition to length and medial offset, may also have a significant influence on the VCA. We hypothesized that femoral bowing has a strong effect on the VCA necessary to restore physiologic alignment after arthroplasty or osteotomy.

Methods

A total of 102 long-leg radiographs were obtained from patients scheduled for primary total knee arthroplasty. The patients on average were 41% male 59% female, 67.9 ± 11.1 years, 67.0 ± 4.7 in, 192 ± 43 lbs, and had a BMI of 29.7 ± 4.8. All radiographs were prepared with the feet placed in identical rotation and the patellae pointing forward, and were excluded if there was evidence of malrotation, as defined by (i) a difference in the medial head offsets of the right and left femur of >3mm, (ii) a difference in the width of the tibiofibular syndesmoses, or (iii) a difference in the rotation of one foot compared to the other.

The following anatomic variables were measured on each radiograph: (i) the neck shaft angle (NSA) of the femur, (ii) the length of the femur, (iii) the length of the femoral shaft, (iv) the medial head offset, (v) the medial-lateral bow of the distal femur, (vi) the hip- knee axis angle, (vii) the mechanical axis deviation of the extremity at the knee, (viii) the medio-lateral bow of the tibia, and (ix) the valgus cut angle required to restore the mechanical axis to the center of the knee during surgery (VCA). Bivariate plots were constructed using the measurements thought to influence the VCA: femoral bowing, femoral offset, and length of femur. Multivariate regression was then used to find the variable that had the strongest effect on the VCA.