Do Differences in Patient-Reported Outcome Measures for Robot-Assisted and Navigated Unicompartmental Knee Replacement Achieve Minimal Clinically Important Differences?

Introduction: Technology is increasingly incorporated into unicompartmental knee arthroplasty (UKA) through computer-assisted navigation (N-UKA) and robot-assisted surgery (R-UKA) to improve alignment, implant positioning, and gap balancing. Whether intraoperative technology helps achieve the minimal clinically important difference (MCID) in patient-reported outcomes (PROMs) compared to conventional UKA (C-UKA) remains unclear. This systematic review aimed to assess whether differences in PROMs between C-UKA and technology-assisted UKA reached MCID values. Materials and Methods: PubMed/MEDLINE/Cochrane Library were reviewed for studies comparing PROMs between primary C-UKA (control group) and N-UKA or R-UKA. Delta improvements were compared to established MCID values. Additional radiographic and clinical differences were assessed. The review yielded four (N=328) N-UKA and seven (N=526) R-UKA studies with C-UKA cohorts as controls. Results: Differences in preoperative and postoperative PROMs were reported as statistically significant in three of four studies (75%) comparing N-UKA and C-UKA; however, none of the studies reported values that reached the MCID. Differences in preoperative and postoperative PROMs were reported as statistically significant in four of seven studies (57.1%) comparing R-UKA and C-UKA; however, only three of the studies (42.9%) reported values that reached the MCID. Improved radiographic outcomes for N-UKA and R-UKA were reported in 75% and 57.1% of studies, respectively. Only one study reported improved revision rates with R-UKA compared to C-UKA. Conclusion: Though studies may report better improvements in PROMs in N-UKA and R-UKA compared to C-UKA, these often may not achieve clinical significance. Future studies should present outcome differences in the context of validated MCID as well as other metrics such as revision rates and radiographic outliers as the impetus for technology-assisted UKA.