Neither a surgeon’s intraoperative impression nor the parameters of computer navigation have been shown to be predictive of the outcomes following total knee arthroplasty (TKA). The aim of this study was to determine whether a surgeon, with robotic assistance, can predict the outcome as assessed using the Knee Injury and Osteoarthritis Outcome Score (KOOS) for pain (KPS), one year postoperatively, and establish what factors correlate with poor KOOS scores in a well-aligned and balanced TKA. A total of 134 consecutive patients who underwent TKA using a dynamic ligament tensioning robotic system with a tibia first resection technique and a cruciate sacrificing ultracongruent TKA system were enrolled into a prospective study. Each TKA was graded based on the final mediolateral ligament balance at 10° and 90° of flexion: 1) < 1 mm difference in the thickness of the tibial insert and that which was planned (n = 75); 2) < 1 mm difference (n = 26); 3) between 1 mm to 2 mm difference (n = 26); and 4) > 2 mm difference (n = 7). The mean one-year KPS score for each grade of TKA was compared and the likelihood of achieving an KPS score of > 90 was calculated. Finally, the factors associated with lower KPS despite achieving a high-grade TKA (grade A and B) were analyzed.Aims
Methods
Achieving a balanced joint with neutral alignment is not always possible in total knee arthroplasty (TKA). Intra-operative compromises such as accepting some joint imbalance, non-neutral alignment or soft-tissue release may result in worse patient outcomes, however, it is unclear which compromise will most impact outcome. In this study we investigate the impact of post-operative soft tissue balance and component alignment on postoperative pain. 135 patients were prospectively enrolled in robot assisted TKA with a digital joint tensioning tool (OMNIBotics with BalanceBot, Corin USA) (57% female; 67.0 ± 8.1 y/o; BMI: 31.9 ± 4.8 kg/m2). All surgeries were performed with a PCL sacrificing tibia or femur first techniques technique, using CR femoral components and a deep dish tibial insert (APEX, Corin USA). Gap measurements were acquired under load (average 80 N) throughout the range of motion during trialing with the tensioning tool inserted in place of the tibial trial. Component alignment parameters and post-operative joint gaps throughout flexion were recorded. Patients completed 1-year KOOS pain questionnaires. Spearman correlations and Mann-Whitney-U tests were used to investigate continuous and categorical data respectively. All analysis performed in R 3.5.3.Introduction
Methods
Neither a surgeon's intraoperative impression or computer navigation parameters have been shown to be predictive of postoperative outcomes following TKA. The purpose of this study is to determine 1) whether a surgeon and a robot can predict the 1-year KOOS pain score (KPS) and 2) determine what factors correlate with poor KOOS scores in well aligned and balanced TKA. The data of 131 consecutive patients enrolled in a prospective trial was reviewed. All TKAs were performed using a dynamic ligament tensioning robotic system with a tibial first resection technique and a cruciate sacrificing ultracongruent knee implant. Each TKA was graded based on the final recorded mediolateral ligament balance at 10° and 90°: A) <1mm with an implanted insert thickness equal to planned (n=74); B) <1mm (n=25); C) <2mm (n=26); D) >2mm (n=6) (Table-1). The 1-year KPS for each knee grade were compared and the likelihood of achieving an KPS > 90 was calculated. Finally, the factors associated with lower KPS despite achieving a high grade TKA (A/B) was performed. The Mann-Whitney U test and Chi-squared analysis was performed.Introduction
Methods
Soft-tissue balancing methods in TKA have evolved from surgeon feel to digital load-sensing tools. Such techniques allow surgeons to assess the soft-tissue envelope after bone cuts, however, these approaches are ‘after-the-fact’ and require soft-tissue release or bony re-cuts to achieve final balance. Recently, a robotic ligament tensioning device has been deployed which characterizes the soft tissue envelope through a continuous range-of-motion after just the initial tibial cut, allowing for virtual femoral resection planning to achieve a targeted gap profile throughout the range of flexion (figure-1). This study reports the first early clinical results and patient reported outcomes (PROMs) associated with this new technique and compares the outcomes with registry data. Since November 2017, 314 patients were prospectively enrolled and underwent robotic-assisted TKA using this surgical technique (mean age: 66.2 ±8.1; females: 173; BMI: 31.4±5.3). KOOS/WOMAC, UCLA, and HSS-Patient Satisfaction scores were collected pre- and post-operatively. Three, six, and twelve-month assessments were completed by 202, 141, and 63 patients, respectively, and compared to registry data from the Shared Ortech Aggregated Repository (SOAR). SOAR is a TJA PROM repository run by Ortech, an independent clinical data collection entity, and it includes data from thousands of TKAs from a diverse cross-section of participating hospitals, teaching institutions and clinics across the United States and Canada who collect outcomes data. PROMs were compared using a two-tailed t-test for non-equal variance.Introduction
Methods
Soft tissue releases are often required to correct deformity and achieve gap balance in total knee arthroplasty (TKA). However, the process of releasing soft tissues can be subjective and highly variable and is often perceived as an ‘art’ in TKA surgery. Releasing soft tissues also increases the risk of iatrogenic injury and may be detrimental to the mechanically sensitive afferent nerve fibers which participate in the regulation of knee joint stability. Measured resection TKA approaches typically rely on making bone cuts based off of generic alignment strategies and then releasing soft tissue afterwards to balance gaps. Conversely, gap-balancing techniques allow for pre-emptive adjustment of bone resections to achieve knee balance thereby potentially reducing the amount of ligament releases required. No study to our knowledge has compared the rates of soft tissue release in these two techniques, however. The objective of this study was, therefore, to compare the rates of soft tissue releases required to achieve a balanced knee in tibial-first gap-balancing versus femur-first measured-resection techniques in robotic assisted TKA, and to compare with release rates reported in the literature for conventional, measured resection TKA [1]. The number and type of soft tissue releases were documented and reviewed in 615 robotic-assisted gap-balancing and 76 robotic-assisted measured-resection TKAs as part of a multicenter study. In the robotic-assisted gap balancing group, a robotic tensioner was inserted into the knee after the tibial resection and the soft tissue envelope was characterized throughout flexion under computer-controlled tension (fig-1). Femoral bone resections were then planned using predictive ligament balance gap profiles throughout the range of motion (fig-2), and executed with a miniature robotic cutting-guide. Soft tissue releases were stratified as a function of the coronal deformity relative to the mechanical axis (varus knees: >1° varus; valgus knees: >1°). Rates of releases were compared between the two groups and to the literature data using the Fischer's exact test.Introduction
Methods
Achieving good ligament balance in total knee arthroplasty (TKA) is essential to prevent early failure and revision surgery. Poor balance and instability are well-defined, however, an ideal ligament balance target across all patients is not well-understood. In this study we investigate the achieved ligament balance using an imageless, intra-operative dynamic balancing tool and its relation to patient reported outcomes. A prospective, multi-surgeon, multi-center study investigated the use of a dynamic ligament-balancing tool in combination with a robotic-assisted navigation platform using the APEX knee (OMNI-Corin, Raynham MA). After all resections, the femoral trial and a computer-controlled tensioning device in place of the tibial tray was inserted into the knee joint. The difference in medial and lateral (ML) gaps when balancing the knee under constant load at extension (10°), mid-flexion (30°) and flexion (90°) was captured. Patients completed the KOOS questionnaire at 3 months ± 2 weeks post-surgery and considered the past 7 days as a timeframe for responses. Pearson's correlation was used to determine linear correlations between factors and ANOVA tests were used to determine differences in categorical data.Background
Methods
Achieving a well-balanced midflexion and flexion soft tissue envelope is a major goal in Total Knee Arthroplasty (TKA). The definition of soft tissue balance that results in optimal outcomes, however, is not well understood. Studies have investigated the native soft tissue envelope in cadaveric specimen and have shown loosening of the knee in flexion, particularly on the lateral side. These methods however do not reflect the post TKA environment, are invasive, and not appropriate for intra-operative use. This study utilizes a digital gap measuring tool to investigate the impact of soft tissue balance in midflexion and flexion on post-operative pain. A prospective multicenter multi-surgeon study was performed in which patients underwent TKA with a dynamic ligament-balancing tool in combination with a robotic-assisted navigation platform. All surgeries were performed with APEX implants (Corin Ltd., USA) using a variety of tibia and femur first techniques. Gap measurements were acquired under load (average 80 N) throughout the range of motion during trialing with the balancing tool inserted in place of the tibial trial. Patients completed KOOS pain questionnaires at 3months±2weeks post-op. Linear correlations were investigated between KOOS pain and coronal gap measurements in midflexion (30°–60°) and flexion (>70°). T-tests were used to compare outcomes between categorical data.Introduction
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