Aims. No predictive model has been published to forecast operating time for total knee arthroplasty (TKA). The aims of this study were to design and validate a predictive model to estimate operating time for
Introduction.
Introduction. There is increasing pressure on healthcare providers to demonstrate competitiveness in quality, patient outcomes and cost. Robotic and computer-assisted total knee arthroplasty (TKA) have been shown to be more accurate than conventional TKA, thereby potentially improving quality and outcomes, however these technologies are usually associated with longer procedural times and higher costs for hospitals. The aim of this study was to determine the surgical efficiency, learning curve and early patient satisfaction of
Aims. The aims of this study were: 1) to describe extended restricted kinematic alignment (E-rKA), a novel alignment strategy during
Aims.
Objectives. The use of the haptically bounded saw blades in
We sought to evaluate the early post-operative active range-of-motion (AROM) between
Introduction. Total knee arthroplasty (TKA) is a well established treatment option for patients with end stage osteoarthritis. Conventional TKA with manual instruments has been shown to be a cost effective and time efficient surgery. While robotic-assisted operative systems have been shown to have benefits in surgical accuracy, they have also been reported to have longer surgical times. The purpose of this work was to determine surgical time and learning curve for a novel
Introduction. Surgical outcome analysis has shifted from surgeon- to patient-reported outcome measures (PROM). High rates of dissatisfaction (13–20%) in PROM after TKA have persisted despite significant advances in pain-management, implant design and introduction of newer surgical techniques. The NAVIO
The use of robotics in total joint arthroplasty is the latest in a long list of expensive technologies that promise multiple positive outcomes, but come with an expensive price tag. In the last decade alone we've seen the same claims for navigation and patient specific instruments and implants. There are various current systems available including a robotic arm, robotic-guided cutting jigs and robotic milling systems. For robotics to be widely adopted it will need to address the following concerns, which as of 2017 it has not. 1). Cost - Very clearly the robotic units come with a significant price tag. Perhaps over time, like other technologies, they will reduce, but at present they are prohibitive for most institutions. 2). Outcomes - One could perhaps justify the increased costs if there was compelling evidence that either outcomes were improved or revision rates reduced. Neither of these has been proved in any type of randomised trial or registry captured data. As with any new technology one must be wary of the claims superseding the results. In 2017 the jury is still out on the cost vs. benefit of
Introduction/Aim. The NAVIO
Introduction. Robotic systems have been used in TKA to add precision, although few studies have evaluated clinical outcomes. We report on early clinical results evaluating patient reported outcomes (PROs) on a series of
Total knee arthroplasty is a successful procedure with good long-term results. Studies indicate that 15% – 25% of patients are dissatisfied with their total knee arthroplasty. In addition, return to sports activities is significantly lower than total hip arthroplasty with 34% – 42% of patients reporting decreased sports participation after their total knee arthroplasties. Poor outcomes and failures are often associated with technical errors. These include malalignment and poor ligament balancing. Malalignment has been reported in up to 25% of all revision knee arthroplasties, and instability is responsible for over 20% of failures. Most studies show that proper alignment within 3 degrees is obtained in only 70% – 80% of cases. Navigation has been shown in many studies to improve alignment. In 2015, Graves examined the Australian Joint Registry and found that computer navigated total knee arthroplasty was associated with a reduced revision rate in patients under 65 years of age. Navigation can improve alignment, but does not provide additional benefits of ligament balance. Robotic-assisted surgery can assist in many of the variables that influence outcomes of total knee arthroplasty including: implant positioning, soft tissue balance, lower limb alignment, proper sizing. The data on robotic-assisted unicompartmental arthroplasty is quite promising. Cytech showed that femoral and tibial alignment were both significantly more accurate than manual techniques with three times as many errors with the manually aligned patients. Pearle, et al. compared the cumulative revision rate at two years and showed this rate was significantly lower than data reported in most unicompartmental series, and lower revision rates than both Swedish and Australian registries. He also showed improved satisfaction scores at two years. Pagnano has noted that optimal alignment may require some deviation from mechanically neutral alignment and individualization may be preferred. This is also likely to be a requirement of more customised or bi-cruciate retaining implant designs. The precision of robotic surgery may be necessary to obtain this individualised component alignment. While robotic total knee arthroplasty requires further data to prove its value, more precise alignment and ligament balancing is likely to lead to improved outcomes, as Pearl, et al. and the Australian registry have shown. While it is difficult to predict the future at this time, I believe
Introduction/Aim. Mid-flexion instability is a well-documented, but often poorly understood cause of failure of
Arthrofibrosis remains a dominant post-operative complication and reason for returning to the OR following total knee arthroplasty. Trauma induced by ligament releases during TKA soft tissue balancing and soft tissue imbalance are thought to be contributing factors to arthrofibrosis, which is commonly treated by manipulation under anesthesia (MUA). We hypothesized that a robotic-assisted ligament balancing technique where the femoral component position is planned in 3D based on ligament gap data would result in lower MUA rates than a measured resection technique where the implants are planned based solely on boney alignment data and ligaments are released afterwards to achieve balance. We also aimed to determine the degree of mechanical axis deviation from neutral that resulted from the ligament balancing technique. Methods. We retrospectively reviewed 301 consecutive primary TKA cases performed by a single surgeon. The first 102 consecutive cases were performed with a femur-first measured resection technique using computer navigation. The femoral component was positioned in neutral mechanical alignment and at 3° of external rotation relative to the posterior condylar axis. The tibia was resected perpendicular to the mechanical axis and ligaments were released as required until the soft tissues were sufficiently balanced. The subsequent 199 consecutive cases were performed with a tibia-first ligament balancing technique using a
Aims. The aim of this study was to report patient and clinical outcomes following
We introduce a novel active tensioning system that can be used for dynamic gap-based implant planning as well as for assessment of final soft tissue balance during implant trialing. We report on the concept development and preliminary findings observed during early feasibility testing in cadavers with two prototype systems. System description. The active spacer (fig 1) consists of a motorized actuator unit with integrated force sensors, independently actuated medial and lateral upper arms, and a set of modular attachments for replicating the range of tibial baseplate and insert trial sizes. The spacer can be controlled in either force or position (gap) control and is integrated into the OMNIBotics. TM.
Aims. Patient dissatisfaction following primary total knee arthroplasty (TKA) with manual jig-based instruments has been reported to be as high as 30%.
Introduction. Component position and overall limb alignment following total knee arthroplasty (TKA) have been shown to influence prosthetic survivorship and clinical outcomes.
Valgus deformity in an end stage osteoarthritic knee can be difficult to correct with no clear consensus on case management. Dependent on if the joint can be reduced and the degree of medial laxity or distension, a surgeon must use their discretion on the correct method for adequate lateral releases. Robotic assisted (RA) technology has been shown to have three dimensional (3D) cut accuracy which could assist with addressing these complex cases. The purpose of this work was to determine the number of soft tissue releases and component orientation of valgus cases performed with RA total knee arthroplasty (TKA). This study was a retrospective chart review of 72 RATKA cases with valgus deformity pre-operatively performed by a single surgeon from July 2016 to December 2017. Initial and final 3D component alignment, knee balancing gaps, component size, and full or partial releases were collected intraoperatively. Post-operatively, radiographs, adverse events, WOMAC total and KOOS Jr scores were collected at 6 months, 1 year and 2 year post-operatively.Introduction
Methods