A literature review of robotic systems showed that these systems can , similarly to computer navigation , reliably improve lower leg alignment , component positioning and soft tissues balancing .
Findings in this study suggest that computer navigation or robotic assistance may help managing these multiple variables and could improve outcomes .
Recently , there is a growing interest in surgical variables that are intraoperatively controlled by orthopaedic surgeons , including lower leg alignment , component positioning and soft tissues balancing .
Since more tight control over these factors is associated with improved outcomes of unicompartmental knee arthroplasty and total knee arthroplasty ( TKA ) , several computer navigation and robotic-assisted systems have been developed .
Although mechanical axis accuracy and component positioning have been shown to improve with computer navigation , no superiority in functional outcomes has yet been shown .
This could be explained by the fact that many differences exist between the number and type of surgical variables these systems control .
Most systems control lower leg alignment and component positioning , while some in addition control soft tissue balancing .
Finally , robotic-assisted systems have the additional advantage of improving surgical precision .
Manually controlling all these surgical variables can be difficult for the orthopaedic surgeon .
Clinical outcome using a ligament referencing technique in CAS versus conventional technique
Purpose Computer-assisted surgery ( CAS ) for total knee arthroplasty ( TKA ) has become increasingly common over the last decade . There are several reports including meta-analyses that show improved alignment , but the clinical results do not differ . Most of these studies have used a bone referencing technique to size and position the prosthesis . The question arises whether CAS has a more pronounced effect on strict ligamentous referencing TKAs . Methods We performed a prospect i ve cohort study comparing clinical outcome of navigated TKA ( 43 patients ) with that of conventional TKA ( 122 patients ) . Patients were assessed preoperatively , and 2 and 12 months postoperatively by an independent study nurse using vali date d patient-reported outcome tools as well as clinical examination . Results At 2 months , there was no difference between the two groups . However , after 12 months , CAS was associated with significantly less pain and stiffness , both at rest and during activities of daily living , as well as greater overall patient satisfaction . Conclusion The present study demonstrated that computer-navigated TKA significantly improves patient outcome scores such as WOMAC score ( P = 0.002 ) and Knee Society score ( P = 0.040 ) 1 year after surgery in using a ligament referencing technique . Furthermore , 91 % were extremely or very satisfied in the CAS TKA group versus 70 % after conventional TKA ( P = 0.007 )
A literature review of robotic systems showed that these systems can , similarly to computer navigation , reliably improve lower leg alignment , component positioning and soft tissues balancing .
Findings in this study suggest that computer navigation or robotic assistance may help managing these multiple variables and could improve outcomes .
Recently , there is a growing interest in surgical variables that are intraoperatively controlled by orthopaedic surgeons , including lower leg alignment , component positioning and soft tissues balancing .
Since more tight control over these factors is associated with improved outcomes of unicompartmental knee arthroplasty and total knee arthroplasty ( TKA ) , several computer navigation and robotic-assisted systems have been developed .
Although mechanical axis accuracy and component positioning have been shown to improve with computer navigation , no superiority in functional outcomes has yet been shown .
This could be explained by the fact that many differences exist between the number and type of surgical variables these systems control .
Most systems control lower leg alignment and component positioning , while some in addition control soft tissue balancing .
Finally , robotic-assisted systems have the additional advantage of improving surgical precision .
Manually controlling all these surgical variables can be difficult for the orthopaedic surgeon .