Robot-assisted total knee arthroplasty is associated with a learning curve for surgical time but not for component alignment, limb alignment and gap balancing

Abstract

Purpose: The application of robotics in the operating theatre for total knee arthroplasty (TKA) remains controversial. As with all new technology, the introduction of new systems is associated with a learning curve and potentially associated with extra complications. Therefore, the aim of this study is to identify and predict the learning curve of robot-assisted (RA) TKA.

Methods: A RA TKA system (MAKO) was introduced in April 2018 in our service. A retrospective analysis was performed of all patients receiving a TKA with this system by six surgeons. Operative times, implant and limb alignment, intraoperative joint balance and robot-related complications were evaluated. Cumulative summation (CUSUM) analyses were used to assess learning curves for operative time, implant alignment and joint balance in RA TKA. Linear regression was performed to predict the learning curve of each surgeon.

Results: RA TKA was associated with a learning curve of 11-43 cases for operative time (p < 0.001). This learning curve was significantly affected by the surgical profile (high vs. medium vs. low volume). A complete normalisation of operative times was seen in four out of five surgeons. The precision of implant positioning and gap balancing showed no learning curve. An average deviation of 0.2° (SD 1.4), 0.7° (SD 1.1), 1.2 (SD 2.1), 0.2° (SD 2.9) and 0.3 (SD 2.4) for the mLDFA, MPTA, HKA, PDFA and PPTA from the preoperative plan was observed. Limb alignment showed a mean deviation of 1.2° (SD 2.1) towards valgus postoperatively compared to the intraoperative plan. One tibial stress fracture was seen as a complication due to suboptimal positioning of the registration pins.

Conclusion: RA TKA is associated with a learning curve for surgical time, which might be longer than reported in current literature and dependent on the profile of the surgeon. There is no learning curve for component alignment, limb alignment and gap balancing.

Level of evidence: IV.