Unicompartmental knee arthroplasty (UKA) has a higher risk of revision than total knee arthroplasty, particularly for low volume surgeons. The recent introduction of robotic-arm assisted systems has allowed for increased accuracy, however new systems typically have learning curves. The objective of this study was to determine the learning curve of a robotic-arm assisted system for UKA.

Methods A total of 152 consecutive robotic-arm assisted primary medial UKA were performed by five surgeons between 2017 and 2021. Operative times, implant positioning, reoperations and patient-reported outcome measures (PROMS; Oxford Knee Score, EuroQol-5D, and Forgotten Joint Score) were recorded.

There was a learning curve of 11 cases with the system that was associated with increased operative time (13 minutes, p<0.01) and improved insert sizing over time (p=0.03). There was no difference in implant survival (98.2%) between learning and proficiency phases (p = 0.15), and no difference in survivorship between ‘high’ and ‘low’ usage surgeons (p = 0.23) at 36 months. There were no differences in PROMS related to the learning curve. This suggested that the learning curve did not lead to early adverse effects in this patient cohort.

The introduction of a robotic-arm assisted UKA system led to learning curves for operative time and implant sizing, but there was no effect on patient outcomes at early follow- up. The short learning curve was independent of UKA usage and indicated that robotic-arm assisted UKA may be particularly useful for low-usage surgeons.

Source of the study: University of Auckland, Auckland, New Zealand

Unicompartmental knee arthroplasty (UKA) has benefits for patients with appropriate indications. However, UKA has a higher risk of revision, particularly for low-usage surgeons. The introduction of robotic-arm assisted systems may allow for improved outcomes but is also associated with a learning curve. We aimed to characterise the learning curve of a robotic-arm assisted system (MAKO) for UKA in terms of operative time, limb alignment, component sizing, and patient outcomes.

Operative times, pre- and post-surgical limb alignments, and component sizing were prospectively recorded for consecutive cases of primary medial UKA between 2017 and 2021 (n=152, 5 surgeons). Patient outcomes were captured with the Oxford Knee Score (OKS), EuroQol-5D (EQ-5D), Forgotten Joint Score (FJS-12) and re-operation events up to two years post-UKA. A Cumulative Summation (CUSUM) method was used to estimate learning curves and to distinguish between learning and proficiency phases.

Introduction of the system had a learning curve of 11 cases. There was increased operative time of 13 minutes between learning and proficiency phases (learning 98 mins vs. proficiency 85 mins; p<0.001), associated with navigation registration and bone preparation/cutting. A learning curve was also found with polyethylene insert sizing (p=0.03). No difference in patient outcomes between the two phases were detected for patient-reported outcome measures, implant survival (both phases 98%; NS) or re-operation (learning 100% vs. proficiency: 96%; NS). Implant survival and re-operation rates did not differ between low and high usage surgeons (cut-off of 12 UKAs per year).

Introduction of the robotic-arm assisted system for UKA led to increased operative times for navigation registration and bone preparation, but no differences were detected in terms of component placement or patient outcomes regardless of usage. The short learning curve regardless of UKA usage indicated that robotic-arm assisted UKA may be particularly useful for low-usage surgeons.