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Bone Bulletin

Abstract

Introduction

Total knee arthroplasty (TKA) is one of the most common orthopedic surgeries worldwide and is the mainstay for treating severe knee arthritis. In the United States, surgeons perform over 700,000 TKAs each year, and that number is expected to climb as osteoarthritis becomes more common in an aging population.1,2 Roughly, two TKAs are completed for every one total hip arthroplasty (THA) and yet patient satisfaction after TKA has always lagged behind the THA.3 Hip replacements routinely see satisfaction rates above 90 percent.2,3 For knees, however, satisfaction rates historically have fallen between 80 and 89 percent.4 There are a few reasons for this gap, including persistent pain, stiffness, and/or instability after surgery.5 The knee is a complex joint relative to the hip, with both translational and rotational properties, making restoration of normal mechanics particularly challenging.6,7,19 These challenges have led to increased interest in technologies designed to account for these variables.8

Robotic-assisted TKA promises a more precise placement of the new joint, more accurate bone cuts relative to preoperative plans, and improved balancing of the soft tissues around the knee.9,12 Even though hospitals have been quick to adopt these systems and companies have invested heavily, it remains unclear if the benefits are as significant as expected.6 Early studies suggest that robots can help with accuracy and may speed up recovery in the short term, but we do not yet know if they lead to superior function, longer-lasting implants, or are cost effective in the long run.10,11 This article will examine various robotic-assisted TKA models, their theoretical and demonstrated benefits, and the challenges associated with evaluating outcomes long-term.

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