Daniel Schrednitzki1, Christoph Eckhard Horn2, Ute Anne Lampe2, Andreas M Halder2. 1. Department of Orthopaedic Surgery, Sana Kliniken Sommerfeld, Waldhausstr. 44, 16766, Kremmen, Germany. d.schrednitzki@sana-hu.de. 2. Department of Orthopaedic Surgery, Sana Kliniken Sommerfeld, Waldhausstr. 44, 16766, Kremmen, Germany.
Abstract
PURPOSE: Conventional instruments for total knee arthroplasty (TKA) have limited accuracy. The occurrence of outliers can negatively influence the clinical outcome and long-term survival of the implant. Orthopaedic robotic systems were developed to increase the accuracy of implant positioning and bone resections. Several systems requiring preoperative imaging have shown a higher degree of precision compared to conventional instrumentation. An imageless system needs less preoperative time and preparation and is more cost effective. Aim of this study was to find out whether this system is as precise, reproduces accurately the surgeon's planning and reduces the occurrence of outliers. METHODS: This retrospective study included the first 71 robotic-assisted TKA and 308 conventional TKA in 374 patients. Intraoperatively planned and actual bone resections were compared. Postoperative alignment, measured on full leg weight bearing radiographs, was related to the respective planning and statistically compared between the groups. RESULTS: Baseline characteristics (age, BMI, ASA, preoperative Knee Society Score and deformity) between both groups were comparable. According to the planned alignment, the postoperative mean difference was - 1.01° in the robotic versus 2.05° in the conventional group. The maximum deviation was - 2/+ 2.5° in the robotic and - 6.6/ + 6.8° in the conventional group. According to the plan, there were no outliers above ± 3° in the robotic versus 24% in the conventional group. The mean difference between planned and measured bone resection was 0.21 mm with a maximum of 2 mm. The 95% confidence interval was at each position 1 mm or below. CONCLUSIONS: The described imageless robotic system is accurate in terms of coronal alignment and bone resections. In precision, it is superior to conventional instrumentation and could therefore be used to evaluate new alignment concepts.
PURPOSE: Conventional instruments for total knee arthroplasty (TKA) have limited accuracy. The occurrence of outliers can negatively influence the clinical outcome and long-term survival of the implant. Orthopaedic robotic systems were developed to increase the accuracy of implant positioning and bone resections. Several systems requiring preoperative imaging have shown a higher degree of precision compared to conventional instrumentation. An imageless system needs less preoperative time and preparation and is more cost effective. Aim of this study was to find out whether this system is as precise, reproduces accurately the surgeon's planning and reduces the occurrence of outliers. METHODS: This retrospective study included the first 71 robotic-assisted TKA and 308 conventional TKA in 374 patients. Intraoperatively planned and actual bone resections were compared. Postoperative alignment, measured on full leg weight bearing radiographs, was related to the respective planning and statistically compared between the groups. RESULTS: Baseline characteristics (age, BMI, ASA, preoperative Knee Society Score and deformity) between both groups were comparable. According to the planned alignment, the postoperative mean difference was - 1.01° in the robotic versus 2.05° in the conventional group. The maximum deviation was - 2/+ 2.5° in the robotic and - 6.6/ + 6.8° in the conventional group. According to the plan, there were no outliers above ± 3° in the robotic versus 24% in the conventional group. The mean difference between planned and measured bone resection was 0.21 mm with a maximum of 2 mm. The 95% confidence interval was at each position 1 mm or below. CONCLUSIONS: The described imageless robotic system is accurate in terms of coronal alignment and bone resections. In precision, it is superior to conventional instrumentation and could therefore be used to evaluate new alignment concepts.
Authors: Muzaffar Ali; Anthony Kamson; Charlie Yoo; Inderpreet Singh; Christopher Ferguson; Raymond Dahl Journal: J Knee Surg Date: 2022-02-18 Impact factor: 2.757
Authors: David G Deckey; Jens T Verhey; Christian S Rosenow; Matthew K Doan; Kade S McQuivey; Anna M Joseph; Adam J Schwartz; Henry D Clarke; Joshua S Bingham Journal: J Arthroplasty Date: 2022-02-17 Impact factor: 4.757
Authors: Michele Ulivi; Valentina Meroni; Marco Viganò; Alessandra Colombini; Michele D M Lombardo; Nicolò Rossi; Luca Orlandini; Carmelo Messina; Luca M Sconfienza; Giuseppe M Peretti; Laura Mangiavini; Laura de Girolamo Journal: Knee Surg Sports Traumatol Arthrosc Date: 2022-08-30 Impact factor: 4.114