Aims. The aims of this systematic review were to assess the learning curve of semi-active robotic arm-assisted total hip arthroplasty (rTHA), and to compare the accuracy, patient-reported functional outcomes, complications, and survivorship between rTHA and manual total hip arthroplasty (mTHA). Methods. Searches of PubMed, Medline, and Google Scholar were performed in April 2020 in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Search terms included “robotic”, “hip”, and “arthroplasty”. The criteria for inclusion were published clinical research articles reporting the learning curve for rTHA (robotic arm-assisted only) and those comparing the implantation accuracy, functional outcomes, survivorship, or complications with mTHA. Results. There were 501 articles initially identified from databases and references. Following full text screening, 17 articles that satisfied the inclusion criteria were included. Four studies reported the learning curve of rTHA, 13 studies reported on implant positioning, five on functional outcomes, ten on complications, and four on survivorship. The meta-analysis showed a significantly greater number of cases of acetabular component placement in the safe zone compared with the mTHA group (95% confidence interval (CI) 4.10 to 7.94; p < 0.001) and that rTHA resulted in a significantly better Harris Hip Score compared to mTHA in the short- to mid-term follow-up (95% CI 0.46 to 5.64; p = 0.020). However, there was no difference in infection rates, dislocation rates, overall complication rates, and survival rates at short-term follow-up. Conclusion. The learning curve of rTHA was between 12 and 35 cases, which was dependent on the assessment goal, such as operating time, accuracy, and team working. Robotic arm-assisted total hip arthroplasty was associated with improved accuracy of component positioning and functional outcome, however no difference in complication rates or survival were observed at short- to mid-term follow-up. Overall, there remains an absence of high-quality level I evidence and cost analysis comparing rTHA and mTHA. Cite this article: Bone Joint J 2021;103-B(6):1009–1020

Aims

This systematic review aims to compare the precision of component positioning, patient-reported outcome measures (PROMs), complications, survivorship, cost-effectiveness, and learning curves of MAKO robotic arm-assisted unicompartmental knee arthroplasty (RAUKA) with manual medial unicompartmental knee arthroplasty (mUKA).

The application of robotics in the operating theatre for knee arthroplasty remains controversial. As with all new technology, the introduction of new systems might be associated with a learning curve. However, guidelines on how to assess the introduction of robotics in the operating theatre are lacking. This systematic review aims to evaluate the current evidence on the learning curve of robot-assisted knee arthroplasty. An extensive literature search of PubMed, Medline, Embase, Web of Science, and Cochrane Library was conducted. Randomized controlled trials, comparative studies, and cohort studies were included. Outcomes assessed included: time required for surgery, stress levels of the surgical team, complications in regard to surgical experience level or time needed for surgery, size prediction of preoperative templating, and alignment according to the number of knee arthroplasties performed. A total of 11 studies met the inclusion criteria. Most were of medium to low quality. The operating time of robot-assisted total knee arthroplasty (TKA) and unicompartmental knee arthroplasty (UKA) is associated with a learning curve of between six to 20 cases and six to 36 cases respectively. Surgical team stress levels show a learning curve of seven cases in TKA and six cases for UKA. Experience with the robotic systems did not influence implant positioning, preoperative planning, and postoperative complications. Robot-assisted TKA and UKA is associated with a learning curve regarding operating time and surgical team stress levels. Future evaluation of robotics in the operating theatre should include detailed measurement of the various aspects of the total operating time, including total robotic time and time needed for preoperative planning. The prior experience of the surgical team should also be evaluated and reported.

Cite this article: Bone Joint J 2020;102-B(4):407–413.