J Orthop Traumatol. 2025 Dec 2;26(1):74. doi: 10.1186/s10195-025-00896-1.
ABSTRACT
BACKGROUND: Robotic-assisted unicompartmental knee arthroplasty (UKA) has gained popularity for its potential to improve implant precision and reduce surgical errors. However, comparative evidence on short-term outcomes versus conventional UKA is lacking. Thus, the purpose of this study was to compare the short-term outcomes of robotic-assisted versus conventional UKA using a nationally representative database.
METHODS: The Nationwide Readmissions Database 2016-2020 was retrospectively examined to identify adult patients who received an elective UKA. After applying exclusion criteria and 1:2 propensity score matching (PSM), 8310 patients were included in the analysis. Outcomes included in-hospital complications, implant malposition or failure, perioperative fracture, length of hospital stay (LOS), hospital costs, and 30- and 90-day readmission rates. Multivariable regression analyses were performed to adjust for residual confounding factors.
RESULTS: Robotic-assisted UKA was associated with significantly lower complication rates compared with conventional UKA (3.7% versus 13.2%, p < 0.001). Specifically, robotic-assisted procedures had reduced risks of implant malposition or failure (odds ratio [OR] = 0.08; 95% confidence interval [CI]: 0.05-0.13; p < 0.001) and perioperative fracture (OR = 0.18; 95% CI 0.04-0.76; p = 0.020). No significant differences were observed in LOS, total hospital costs, or readmission rates at 30 and 90 days.
CONCLUSIONS: Robotic-assisted UKA is associated with improved short-term surgical safety, including fewer complications, particularly, reduced implant malposition and perioperative fractures. However, broader hospital metrics such as LOS, cost, and readmissions were comparable between the two approaches. Further prospective studies are needed to validate these findings and assess long-term outcomes and cost-effectiveness.
LEVEL OF EVIDENCE: Level III.
CLINICAL TRIAL REGISTRATION NUMBER: Not applicable.
PMID:41329432 | DOI:10.1186/s10195-025-00896-1
