Abstract / Summary
Abstract Objective To evaluate the early comparative effectiveness of robotic versus conventional total knee replacement (TKR) and unicompartmental knee replacement (UKR) in the UK. Design Target trial emulation study. Setting Public and private hospitals using data from the National Joint Registry of England, Wales, Northern Ireland, the Isle of Man, Guernsey, and Jersey. Participants 697 145 knee replacement surgeries between 2018 and 2024: 675 034 were conventional (TKRs and UKRs) and 22 111 were robotic. Main outcome measures The main outcome was five year knee replacement survival (mean 2.5 years follow-up); all cause revision risk; cause specific revision risk; intraoperative complications; and revision complexity of robotic versus conventional (TKR and UKR) knee replacement. Kaplan-Meier and Cox regression analyses were used to compare implant survival and indications for revision surgery. Propensity score matching using target trial emulation framework was used to estimate the average treatment effect in the treated population. Results The five year implant survival of the matched conventional and robotic TKR groups was 98.5% (95% confidence interval (CI) 98.3% to 98.7%) and 98.6% (98.2% to 99.0%), respectively, with no between group difference in revision risk (hazard ratio 1.03, 95% CI 0.86 to 1.26; P=0.71). The five year implant survival of the matched conventional and robotic UKR groups was 97.8% (95% CI 97.2% to 98.3%) and 96.4% (92.4% to 98.3%), respectively, with no between group difference in revision risk (hazard ratio 1.03, 95% CI 0.75 to 1.42; P=0.86). Cause specific revision risk and intraoperative complication risks did not differ between groups for either TKR or UKR. Conclusions No statistically significant differences were detected in revision risk, cause specific risk, or intraoperative complication risk between the robotic and conventional groups. This was consistent for both TKR and UKR. The possibility of unmeasured and residual confounding cannot be ruled out, however, owing to the observational design of the study. These results highlight the importance of careful evaluation of robotic technology in publicly funded healthcare systems, given the substantially higher capital and procedural costs involved.