Johanna Elliott1, Jobe Shatrov2, Brett Fritsch2, David Parker2. 1. Sydney Orthopaedic Research Institute, 445 Victoria Avenue, Chatswood, NSW, 2067, Australia. jellyott@gmail.com. 2. Sydney Orthopaedic Research Institute, 445 Victoria Avenue, Chatswood, NSW, 2067, Australia.
Abstract
INTRODUCTION: A review of the data supporting robotic systems currently available is presented focussing on precision and reproducibility, radiological outcomes, clinical outcomes, and survivorship. MATERIALS AND METHODS: Scientific literature published on robotic systems for knee arthroplasty was reviewed using the reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Inclusion criteria were any study involving robotic-assisted UKA or TKA that reported precision of implant positioning or functional outcomes or range of motion or survivorship, including cadaveric or dry bone studies with a minimum of 6-month follow-up. RESULTS: Thirty-nine studies were identified for robotic-assisted unicompartmental knee arthroplasty, and 24 studies for robotic-assisted total knee arthroplasty. Those that reported on radiological outcomes or cadaver studies consistently demonstrated improved precision with the use of robotic systems irrespective of the system. PROMS and survival data demonstrated equivalent short-term results. However, many studies reported outcomes inconsistently and few had long-term clinical follow-up or survivorship data. CONCLUSIONS: This review adds to the body of evidence supporting improved precision and reproducibility with robotic assistance in knee arthroplasty. Despite intensive funding of research into robotic knee systems, there remains considerable heterogeneity in exposure and outcome analysis and few quality long-term studies demonstrating translation to better clinical outcomes and implant survivorship.
INTRODUCTION: A review of the data supporting robotic systems currently available is presented focussing on precision and reproducibility, radiological outcomes, clinical outcomes, and survivorship. MATERIALS AND METHODS: Scientific literature published on robotic systems for knee arthroplasty was reviewed using the reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Inclusion criteria were any study involving robotic-assisted UKA or TKA that reported precision of implant positioning or functional outcomes or range of motion or survivorship, including cadaveric or dry bone studies with a minimum of 6-month follow-up. RESULTS: Thirty-nine studies were identified for robotic-assisted unicompartmental knee arthroplasty, and 24 studies for robotic-assisted total knee arthroplasty. Those that reported on radiological outcomes or cadaver studies consistently demonstrated improved precision with the use of robotic systems irrespective of the system. PROMS and survival data demonstrated equivalent short-term results. However, many studies reported outcomes inconsistently and few had long-term clinical follow-up or survivorship data. CONCLUSIONS: This review adds to the body of evidence supporting improved precision and reproducibility with robotic assistance in knee arthroplasty. Despite intensive funding of research into robotic knee systems, there remains considerable heterogeneity in exposure and outcome analysis and few quality long-term studies demonstrating translation to better clinical outcomes and implant survivorship.
Authors: Stuart W Bell; Iain Anthony; Bryn Jones; Angus MacLean; Philip Rowe; Mark Blyth Journal: J Bone Joint Surg Am Date: 2016-04-20 Impact factor: 5.284
Authors: Marco Adriani; Michael-Alexander Malahias; Alex Gu; Cynthia A Kahlenberg; Michael P Ast; Peter K Sculco Journal: J Arthroplasty Date: 2019-11-05 Impact factor: 4.757
Authors: Joost A Burger; Laura J Kleeblad; Inger N Sierevelt; Wieger G Horstmann; Rutger C I van Geenen; Liza N van Steenbergen; Peter A Nolte Journal: J Arthroplasty Date: 2020-02-18 Impact factor: 4.757
Authors: Stephen G Zak; David Cieremans; Alex Tang; Ran Schwarzkopf; Joshua C Rozell Journal: Arch Orthop Trauma Surg Date: 2022-05-12 Impact factor: 3.067