Finding the Optimal Aim of Correction in Opening Wedge High Tibial Osteotomy

Overview

The purpose of this RCT is to investigate whether high tibial osteotomy using 3D printed patient specific guides aiming at 55% correction is non-inferior to aiming at 62%.

HTO should play a major role in modern treatment algorithms for knee overload and osteoarthritis. By transferring load from the failing/osteoarthritic compartment of the knee to a healthier compartment, HTO can delay or stop the progression of osteoarthritis at an early stage. This can remove pain and increase knee function, making return to work, activities and sport possible. HTO may delay or avoid the need for total knee replacement for \>10 years for at least 80% of patients. The optimal target for the postoperative mechanical axis of the leg is not yet clarified. Both under- and overcorrection can lead to unfavourable results. The classical Fusjisawa´s point of 62%, or approximately 3 deg. of valgus, is still often used as the optimal target, and studies show good clinical results and longevity. With an often accepted accuracy of +/- 3 deg. with conventional methods, the accepted postoperative range of valgus will be from 0 deg. to 6 deg. But the optimal range is possibly much narrower. Recent studies suggest a narrower range and less overcorrection. 3D-printed patient specific instrumentation (PSI) is based on CT of the individual patient´s knee, data simulation of the planned correction and subsequent 3D printed guides for each patient. The PSI design varies, but involves a positioning guide fitting only in position one the proximal tibia, a cutting guidance and a wedge opening guide. PSI seem to improve accuracy to the level of approximately +/- 1 deg. from the preplanned correction and leads to fewer unacceptable outliers compared to the conventional methods available. Improved accuracy has not shown to yield better clinical results. In the future the target axis should possibly be individualized, based on the pathology treated, gait analyses and data simulations. Modern gait analysis using wearable accelerator sensors, often referred to as inertial measurement units (IMUs) is rapidly evolving. By coupling individualized and accurate osteotomy with gait analysis using wearable sensors, one could better predict and understand how to normalise each individual patients´ gait pattern and possibly improve patient satisfaction and function after surgery. By coupling the highly accurate PSI method, an angular stable implant and a composite of outcomes based on radiology, validated patient reported outcome measures and gait analysis, our RCT can investigate if a correction target of 55% is non-inferior to the common 62%. The study will be designed as a continuous outcome non-inferiority trial where KOOS QoL subscale is used as the primary outcome and the basis for sample size calculation. The Minimal Clinical Important Difference (MCID) for KOOS QoL regarding HTO is 16.5 points. A presumed standard deviation (SD) of 23 points is obtained from a previous study on a similar population. A one-sided t-test power analysis with 2.5% significance level and 80% power level indicates that 31 patients would be needed in each group. In total 70 patients is planned to be included, which takes into account up to 10% dropout rate and some uncertainty regarding the predicted score values. Statistics: The primary outcome will be analyzed with a linear mixed model, where the measurements from all time points will be included. The main effect measure will be the between-group difference in change from baseline to two years, which will be estimated with a 95% confidence interval and a P-value for non-inferiority where the null hypothesis is that osteotomy correction to the 55% target is inferior to the correction to the 62% target and the alternative states that it is not. Inferiority is determined by KOOS QOL difference of at least MCID. Paired samples t-tests will be used to analyze differences between pre- and postoperative measurements on X-rays within each group. Independent samples t-tests will be used to analyze differences between groups. A p-value \< 0.05 is considered statistically significant.

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Interventions

Eligibility

Outcomes

Central Contacts