Samuel J MacDessi1, Monther A Gharaibeh1, Ian A Harris2. 1. Sydney Knee Specialists, St George Private Hospital, Kogarah, New South Wales, Australia. 2. South Western Sydney Clinical School, University of New South Wales, Liverpool, New South Wales, Australia.
Abstract
BACKGROUND: Soft tissue balance is believed to be a major determinant of improved outcomes in total knee arthroplasty (TKA). We conducted this study to assess the accuracy of surgeon-defined assessment (SDA) of knee balance compared to pressure sensor data. We also assessed for any association between experience (learning curve) and accuracy of SDA. METHODS: A total of 308 patients undergoing 322 mechanically aligned TKA were prospectively analyzed. Femoral and tibial trial implants were inserted before performing knee balancing. We compared the surgeon determination on knee balance at 10°, 45°, and 90° of flexion to sensor data at the same flexion angles. RESULTS: Accuracy of SDA was 63%, 57.5%, and 63.8% at 10°, 45°, and 90°, respectively, when compared to sensor data. SDA had an overall sensitivity of 81% and specificity of 37.7%. Capacity to determine an unbalanced knee worsened at higher knee flexion angles with SDA test specificity of 53.5%, 34.8%, and 24.8% at 10°, 45°, and 90°, respectively (P = .0004 at 10° vs 45°, P < .0001 at 10° vs 90°). Cohen's kappa coefficient was 0.29 at 10° indicating fair agreement, and 0.14 and 0.12 at 45° and 90°, respectively, indicating poor agreement. The use of sensor had no time-based learning effect on capacity to determine knee balance. CONCLUSION: SDA is a poor predictor of the true soft tissue balance when compared to sensor data, particularly in assessing whether a knee is unbalanced. In addition, increased use of sensors did not improve surgeon capacity to determine knee balance.
BACKGROUND: Soft tissue balance is believed to be a major determinant of improved outcomes in total knee arthroplasty (TKA). We conducted this study to assess the accuracy of surgeon-defined assessment (SDA) of knee balance compared to pressure sensor data. We also assessed for any association between experience (learning curve) and accuracy of SDA. METHODS: A total of 308 patients undergoing 322 mechanically aligned TKA were prospectively analyzed. Femoral and tibial trial implants were inserted before performing knee balancing. We compared the surgeon determination on knee balance at 10°, 45°, and 90° of flexion to sensor data at the same flexion angles. RESULTS: Accuracy of SDA was 63%, 57.5%, and 63.8% at 10°, 45°, and 90°, respectively, when compared to sensor data. SDA had an overall sensitivity of 81% and specificity of 37.7%. Capacity to determine an unbalanced knee worsened at higher knee flexion angles with SDA test specificity of 53.5%, 34.8%, and 24.8% at 10°, 45°, and 90°, respectively (P = .0004 at 10° vs 45°, P < .0001 at 10° vs 90°). Cohen's kappa coefficient was 0.29 at 10° indicating fair agreement, and 0.14 and 0.12 at 45° and 90°, respectively, indicating poor agreement. The use of sensor had no time-based learning effect on capacity to determine knee balance. CONCLUSION:SDA is a poor predictor of the true soft tissue balance when compared to sensor data, particularly in assessing whether a knee is unbalanced. In addition, increased use of sensors did not improve surgeon capacity to determine knee balance.
Authors: Simon W Young; Nina Zeng; Mei Lin Tay; David Fulker; Christina Esposito; Matthew Carter; Ali Bayan; Bill Farrington; Rupert Van Rooyen; Matthew Walker Journal: Trials Date: 2022-07-20 Impact factor: 2.728
Authors: Samuel J MacDessi; Aziz Bhimani; Alexander W R Burns; Darren B Chen; Anthony K L Leong; Robert B Molnar; Jonathan S Mulford; Richard M Walker; Ian A Harris; Ashish Diwan; Jil A Wood Journal: BMJ Open Date: 2019-05-10 Impact factor: 2.692
Authors: Samuel J MacDessi; William Griffiths-Jones; Darren B Chen; Sam Griffiths-Jones; Jil A Wood; Ashish D Diwan; Ian A Harris Journal: Bone Joint J Date: 2020-01 Impact factor: 5.082