Abstract
Aims
Robotic arm-assisted unicompartmental knee arthroplasty (R-UKA) has been shown to improve alignment and accuracy of component placement compared with conventional unicompartmental knee arthroplasty (C-UKA). Despite this, there is conflicting evidence for whether this has an impact on revision rates.
Methods
We performed a retrospective analysis of a prospective database, comparing patients who underwent R-UKA using the Stryker Restoris MCK implant with those who underwent C-UKA using the cemented Oxford Partial Knee implant, between January 2002 and December 2024 at The Prince Charles Hospital (Brisbane, Australia), with a minimum six-month follow-up. Patient selection for UKA mirrored the recommendations by Kozinn and Scott. The primary outcome of interest was to compare the all-cause revision rate between these two groups. Secondary outcomes of interest were to compare hospital length of stay (HLOS), surgical duration, the odds of superficial surgical site infection, and the odds of periprosthetic joint infection (PJI) between the same groups. The analysis of individual outcomes were adjusted for age, sex, BMI, American Society of Anesthesiologists grade, Charlson Comorbidity Index, and primary surgeon grade.
Results
The hazard of all-cause revision significantly decreased by 78% in the R-UKA group as compared with the C-UKA group (p = 0.046). HLOS was also significantly shorter by 2.2 days (95% CI 1.0 to 3.3) in the R-UKA group (p < 0.001). There was no significant difference in the surgical duration (p = 0.733), odds of superficial surgical site infection (p = 0.845), nor in the odds of PJI (p = 0.415) between the two groups.
Conclusion
The substantial improvement in revision outcomes suggests that R-UKA is the option of choice for managing symptomatic unicompartmental knee arthritis in carefully selected patients with isolated medial compartmental osteoarthritis, especially in the hands of low-volume surgeons. Decreased HLOS should be interpreted with caution, given the non-contemporaneous nature of the two cohorts.
Cite this article: Bone Jt Open 2026;7(10):1304–1311.
Keywords: Unicompartmental Knee, Robotic, Mako, Conventional, Survivorship, Instrumented, robotic arm, Unicompartmental knee arthroplasty (UKA), surgical site infection, Anesthesiologists, osteoarthritis, primary surgeon, BMI, Charlson Comorbidity Index, unicompartmental knee, medial unicompartmental knee arthroplasty
Introduction
Unicompartmental knee arthroplasty (UKA) is an established surgical method to address symptomatic isolated unicompartmental knee arthritis in select patients.1 As compared with a total knee arthroplasty, UKA preserves normal joint kinematics, thus leading to a faster recovery and improved patient-reported outcomes.2-5 Despite these benefits, UKA may be underutilized due to the high technical demands of the surgery.6 Conventional instrumented UKA (C-UKA) has a steep learning curve of between 25 and 50 cases,7-9 with further studies showing inferior outcomes when performed by low-volume surgeons.10-12
Although the most common indication for revision following UKA is for progression of arthritis, early failures have been attributed to technical errors in achieving adequate implant positioning.13,14 Malalignment has been shown to cause accelerated polyethylene wear, early aseptic loosening, stress fractures of the adjacent compartment, worse functional outcomes, and ultimately expedite the progression of osteoarthritis.15-20 In order to mitigate this risk, robotic arm-assisted UKA (R-UKA) systems with haptic feedback technology have been developed to improve the accuracy of bony resections and enhance implant positioning.21,22 Of concern, a previous study utilizing data from the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) has reported a fivefold increase in the revision rate for periprosthetic joint infection (PJI) in patients undergoing the Mako-assisted Restoris joint arthroplasty (Stryker, USA), compared with other non-robotically assisted UKA in the first three months.23 This finding has now not been shown in the 2025 report.24
Several studies comparing R-UKA with C-UKA have shown improved functional outcomes and shorter length of stay in hospital. Of interest, these studies had reported conflicting results on the effect of R-UKA on complication rates.25-27 Thus, the primary aim of this study was to compare the all-cause revision rate between patients undergoing R-UKA versus those undergoing C-UKA at our institution. Secondary outcomes of interest were to compare hospital length of stay (HLOS), surgical duration, the odds of superficial surgical site infection, and the odds of PJI between these two groups.
Methods
This retrospective cohort study was conducted at The Prince Charles Hospital, a tertiary-level university teaching hospital located in Brisbane, Australia. No AI was used in the research or manuscript development,28 and reporting of this study adhered to the recommendations by STROBE.29 We used prospectively collected data from our institution’s internal audit database to conduct this study, thereby minimizing the risk of recall bias. In selected patients, UKA has been the standard of care for symptomatic unicompartmental knee arthritis at our institution. Patient eligibility criteria for UKA at our institution closely mirrored those of Kozinn and Scott:30 unicompartmental knee arthritis, non-manual occupation, range of motion ≥ 90°, flexion contracture ≤ 5°, correctable valgus/varus deformity of < 15°, as well as the absence of inflammatory arthritis. Prior to 2019, only C-UKAs were performed at our institution, utilizing a variety of implants. Since then, there has been a departmental shift in practice towards the use of R-UKA.
Consecutive patients who underwent an elective UKA at The Prince Charles Hospital between January 2002 and December 2024, with a minimum follow-up period of six months, were identified for potential inclusion. All patients who underwent R-UKA received a Restoris MCK Partial Knee (Stryker, USA). This is a cemented fixed-bearing prosthesis implanted with the assistance of the Mako robotic system (Stryker), an image-guided semiactive robotic arm technology with haptic feedback. As the majority of patients who underwent a C-UKA received the cemented Oxford Partial Knee (Zimmer Biomet, USA), we used this as our comparator group to minimize the risk of anomalous outcomes from implant heterogeneity. This is a cemented mobile bearing prosthesis, which has been implanted using the instrumented technique as described by the manufacturer. We excluded patients who underwent lateral compartment joint arthroplasty, those who received a bilateral simultaneous UKA, and those who underwent C-UKA utilizing implants apart from the Oxford Partial Knee System. All UKAs were performed by or under the supervision of a fellowship-trained consultant orthopaedic surgeon (AMS).
Using our predefined inclusion and exclusion criteria, we identified 177 patients for analysis: 65 patients in the C-UKA group and 112 patients in the R-UKA group. The median follow-up was 11.8 years (IQR 7.7 to 20.0) in the C-UKA group and 4.6 years (IQR 2.6 to 5.5) in the R-UKA group. There was no significant difference in age at the time of surgery (p = 0.211, Mann-Whitney U test), sex (p = 0.158, Fisher’s exact test), BMI (p = 0.209, Mann-Whitney U test), American Society of Anesthesiologists (ASA)31 grade (p = 0.322, Fisher’s exact test), smoking status (p = 0.535, Fisher’s exact test), Charlson Comorbidity Index (CCI)32 (p = 0.893, Mann-Whitney U test), or primary surgeon grade (p = 0.618, Fisher’s exact test) between the two groups. In terms of comorbidities, there were a significantly greater number of patients with chronic obstructive pulmonary disease (p = 0.035, Fisher’s exact test) and depression/anxiety (p = 0.011, Fisher’s exact test) in the R-UKA group compared with the C-UKA group. Significantly fewer patients in the R-UKA group had a previous meniscectomy (p = 0.048, Fisher’s exact test) compared with the C-UKA group. There was no difference in the proportion of patients with a history of cardiac arrhythmia (p = 0.539, Fisher’s exact test), coronary artery disease (p > 0.999, Fisher’s exact test), cardiac failure (p = 0.134, Fisher’s exact test), cerebrovascular disease (p > 0.999, Fisher’s exact test), chronic kidney disease (p = 0.501, Fisher’s exact test), diabetes (p = 0.194, Fisher’s exact test), hypertension (p = 0.210, Fisher’s exact test), chronic liver disease (p > 0.999, Fisher’s exact test), and peripheral vascular disease (p = 0.533, Fisher’s exact test) between the two groups. In both groups, the consultant surgeon was the primary operator in most cases. A detailed analysis of these covariates is displayed in Table I.
Table I.
Demographic details, comorbidities, and surgical factors.
| Variable | C-UKA | R-UKA | p-value |
|---|---|---|---|
| Patients, n | 65 | 112 | |
| Median age at surgery, yrs (IQR) | 64.0 (56.0 to 73.0) | 66.0 (59.0 to 72.5) | 0.211* |
| Sex, n (%) | 0.158† | ||
| Male | 31 (47.7) | 67 (59.8) | |
| Female | 34 (52.3) | 45 (40.2) | |
| Median BMI, kg/m² (IQR) | 29.6 (26.8 to 38) | 28.4 (26.1 to 32.1) | 0.209* |
| ASA grade, n (%) | 0.322† | ||
| I | 10 (15.4) | 11 (9.8) | |
| II | 35 (53.9) | 53 (47.3) | |
| III | 20 (30.8) | 46 (41.1) | |
| IV | 0 (0) | 2 (1.8) | |
| Comorbidities, n (%) | |||
| Cardiac arrhythmia | 3 (4.6) | 9 (8.0) | 0.539† |
| Coronary artery disease | 6 (9.2) | 10 (8.9) | > 0.999† |
| Cardiac failure | 2 (3.1) | 0 (0) | 0.134† |
| Chronic obstructive pulmonary disease | 3 (4.6) | 16 (14.3) | 0.035† |
| Cerebrovascular disease | 2 (3.1) | 3 (2.7) | > 0.999† |
| Chronic kidney disease | 5 (7.7) | 5 (4.5) | 0.501† |
| Depression/anxiety | 3 (4.6) | 21 (18.8) | 0.011† |
| Diabetes | 12 (18.5) | 14 (12.5) | 0.194† |
| Hypertension | 25 (38.5) | 55 (49.1) | 0.210† |
| Chronic liver disease | 1 (1.5) | 1 (0.9) | > 0.999† |
| Peripheral vascular disease | 0 (0) | 2 (1.8) | 0.533† |
| Previous meniscectomy | 3 (4.6) | 0 (0) | 0.048† |
| Active smoker | 5 (7.7) | 6 (5.4) | 0.535† |
| Charlson Comorbidity Index score | 2.0 (1.0 to 4.0) | 2.0 (2.0–4.0) | 0.893† |
| Primary surgeon grade, n (%) | 0.699† | ||
| Consultant | 38 (58.5) | 72 (64.3) | |
| Fellow | 13 (20.0) | 18 (16.1) | |
| Resident | 14 (21.5) | 22 (19.6) | |
Mann–Whitney U test
Fisher’s exact test
ASA, American Society of Anesthesiologists; C-UKA, conventional unicompartmental knee arthroplasty; R-UKA, robotic arm-assisted unicompartmental knee arthroplasty.
Outcome measurement
The primary outcome of this study was to compare the all-cause revision rate between the R-UKA and C-UKA groups. To account for variation in revision rates due to the differences in follow-up period, we employed survivor analysis, and examined revision incidence within three years following UKA. Survival time was defined as the interval from the date of UKA to the date of revision surgery. Patients were censored at death or in the case of survival, on 1 June 2025. Kaplan-Meier analysis was used to illustrate the differences between the two arms. This was quantified using hazard ratios (HRs) derived from a Cox-regression analysis. Furthermore, the difference in revision incidence within five years of UKA was quantified using odds ratios (ORs).
The secondary outcomes were to compare the median HLOS and surgical time, as well as the odds of superficial surgical site infection and PJI between the two groups. To further account for difference in patient factors and surgeon experience, each outcome was adjusted for age, sex, BMI, ASA grade, CCI score and primary surgeon grade using the appropriate regression analyses.
Statistical analysis
Continuous variables were expressed as median (IQR) and compared using Mann-Whitney U test, whereas discrete variables were expressed as count (percentage) and compared using Fisher’s exact test. All statistical analyses were performed using Stata v. 18.0 (StataCorp, USA). The threshold for statistical significance was set at p < 0.05.
Results
A total of 15 revisions were identified within the follow-up period: 12 (18.5%) in the C-UKA group and three (2.7%) in the R-UKA group. In the C-UKA group, four patients underwent revision due to progression of osteoarthritis, another four patients were revised for aseptic loosening, and one patient each revised for bearing dislocation, postoperative periprosthetic fracture, malalignment, and PJI. Of the three patients that were revised in the R-UKA group, two were for aseptic loosening and one for progression of arthritis. Median time to revision was 3.3 years (IQR 0.8 to 14.1) in the C-UKA group and 1.9 years (IQR 0.9 to 3.1) in the R-UKA group. The Kaplan-Meier survival curve is illustrated in Figure 1. After adjusting for age, sex, BMI, ASA grade, CCI score, and primary surgeon grade, the all-cause revision rate was significantly lower in the R-UKA group (HR 0.22, 95% CI 0.05 to 0.98; p = 0.046, Wald test). Seven patients were revised within three years of their index operation: five (7.7%) in the C-UKA group and two (1.8%) in the R-UKA group. After adjusting for age, sex, BMI, ASA grade, CCI score, and primary surgeon grade, the revision hazard was 99% lower in the R-UKA group (p = 0.023; Wald test). A detailed breakdown of the timeline for each revision complication is discussed in Supplementary Table i.
Fig. 1.

Kaplan-Meier survival analysis truncated at seven years. C-UKA, conventional unicompartmental knee arthroplasty; R-UKA, robotic arm-assisted unicompartmental knee arthroplasty.
Median HLOS was five days (IQR 3.0 to 6.0) in the C-UKA group and three days (IQR 2.0 to 3.5) in the R-UKA group. When adjusted for age, sex, BMI, ASA grade, CCI score, and primary surgeon grade, the HLOS was significantly lower by 2.2 days (95% CI 1.0 to 3.3) in the R-UKA group (p < 0.001, Wald test) when compared with the C-UKA group. Similarly, median surgical time was 105.0 minutes (IQR 103.0 to 126.0) and 98.0 minutes (IQR 98.0 to 123.0), respectively. Adjusted difference in surgical time was three minutes shorter (95% CI -15.35 to 21.41) in the R-UKA group. This was not statistically significant (p = 0.733; Wald test). Two infections were recorded: one superficial surgical site infection in the R-UKA group and one PJI in the C-UKA group. The adjusted odds of superficial surgical site infection was 0.73 (95% CI 0.03 to 16.96; p = 0.845, Wald test), and the adjusted odds of PJI was 0.30 (95% CI 0.01 to 12.76; p = 0.415, Wald test) in the R-UKA group, compared with the C-UKA group. The outcomes of our analysis are summarized in Table II.
Table II.
Summary of primary and secondary outcomes.
| Variable | C-UKA | R-UKA | Adjusted analysis (95% CI) | p-value |
|---|---|---|---|---|
| Patients, n | 65 | 112 | ||
| All-cause revision, n (%) | 12 (18.5) | 3 (2.7) | HR 0.22 (0.05 to 0.98) | 0.046* |
| Aseptic loosening | 4 | 2 | ||
| Bearing dislocation | 1 | 0 | ||
| Periprosthetic fracture | 1 | 0 | ||
| Malalignment | 1 | 0 | ||
| Periprosthetic joint infection | 1 | 0 | ||
| Progression of arthritis | 4 | 1 | ||
| Three-year revision, n (%) | 5 (7.7) | 2 (1.8) | HR 0.01 (0.00 to 0.54) | 0.023* |
| Aseptic loosening | 1 | 2 | ||
| Periprosthetic fracture | 1 | 0 | ||
| Malalignment | 1 | 0 | ||
| Periprosthetic joint infection | 1 | 0 | ||
| Progression of arthritis | 1 | 0 | ||
| Median hospital length of stay, days (IQR) | 5.0 (3.0 to 6.0) | 3.0 (3.0 to 3.5) | β -2.2 (-3.3 to -1.0) | < 0.001† |
| Median surgical duration, minutes (IQR) | 105.0 (103.0 to 126.0) | 98.0 (86.0 to 123.0) | β -3.0 (-21.4 to 15.3) | 0.733† |
| Superficial surgical site infection, n (%) | 0 (0) | 1 (0.89) | OR 0.73 (0.03 to 17.0) | 0.845* |
| Periprosthetic joint infection, n (%) | 1 (1.5) | 0 (0) | OR 0.30 (0.02 to 5.5) | 0.415* |
Fisher’s exact test
Mann–Whitney U test
C-UKA, conventional unicompartmental knee arthroplasty; HR, hazard ratio; OR, odds ratio; R-UKA, robotic arm assisted unicompartmental knee arthroplasty; β, regression coefficient.
Discussion
The most pertinent finding of this study is that patients undergoing R-UKA at our institution had a significantly lower rate of all-cause revision compared with those undergoing C-UKA. Our results echo the most recent AOANJRR report, which has found a 36% reduction in revision hazard in R-UKA compared with C-UKA after 3.5 years.24 As the assumption of proportionality was upheld in our analysis, we did not show a divergent pattern of survivorship as reported in the AOANJRR. Unique to the present study is that we demonstrated a significant reduction in revision rate following medial R-UKA. Several previous studies have only shown a reduction in complication rate, with no effect on revision rate itself.25-27,33,34 We postulate that this finding may be due to optimization of component positioning. Our hypothesis is supported by several high-quality randomized controlled trials that have proven that R-UKA significantly improves the accuracy of component placement,22,35 with additional studies showing that this benefit was sustained even in inexperienced surgeons.36,37 The results of our primary outcome analysis thus support the adoption of robotic technology in UKA to improve patient outcome.
A previous AOANJRR study by St Mart et al23 reported an increase in the revision rate for PJI in patients undergoing the Mako-assisted Restoris joint arthroplasty in the first three months. This difference was hypothesized to result from the additional wounds caused by the introduction of guide pins. Fortunately, we did not observe any increase in infection rate within our patient population. Only one patient in the C-UKA group was revised due to infection. This patient received a washout and debridement with exchange of the polyethylene liner, followed by a period of antibiotic treatment. Additionally, one patient in the R-UKA group also had a superficial surgical site infection unrelated to the pin sites. This patient was treated with a short course of antibiotics. Both of these patients were closely followed up in an outpatient setting, with no evidence of recurrence of infection. We also demonstrated a significantly lower median HLOS in the R-UKA group by two days. This finding has also been reported by several other studies, and is likely secondary to improved pain scores from less traumatic soft-tissue handling.21,25,38-40 In contrary to the findings by Goh et al,41 there was no statistically significant difference in surgical duration between the two groups. Therefore, despite a higher consumable cost associated with R-UKA, the decrease in revision rate and shorter HLOS have been shown to provide overall savings for the health system.42
Our study is the first to report a substantial reduction in all-cause revision for patients undergoing medial R-UKA compared with those undergoing medial C-UKA. A major strength of this study is the use of a prospectively maintained database, thus minimizing the risk of recall bias. We also accounted for differences in patient factors and surgeon experience by adjusting each outcome for age, sex, BMI, ASA grade, CCI score, and primary surgeon grade. Although no a priori power analysis was performed given the retrospective nature of this study, post-hoc power analysis showed that our study is adequately powered to detect the primary outcome. There are several weaknesses of this study that need to be addressed. First, the follow-up period was unequal between the two arms, with C-UKA having a longer follow-up period. We mitigated this difference by the use of survival analysis, which takes into consideration follow-up duration, as well as a truncated survivorship model.43 In our institution, no patient received a C-UKA after 2019, making contemporaneous cohort examination unfeasible. Second, the implant used in the R-TKA arm was a fixed bearing prosthesis, whereas the implant used in the C-UKA was a mobile bearing implant. Several registry studies have failed to demonstrate a difference in long-term outcome attributed to implant design.44,45 Third, patient-reported outcome measures (PROMs) were not collected in our cohort, limiting the inferences that could be derived out of this study. Nonetheless, several studies have consistently demonstrated improved short-term functional outcomes following R-UKA,27,34,46 further reinforcing the benefits of this technological advancement. Fourth, it is important to note that there was a difference in times between R-UKA and C-UKA groups. Evolution of enhanced recovery protocols, as well as changing perceptions on early hospital discharge over time makes HLOS data less reliable. Lastly, we did not assess whether the poorer outcomes associated with C-UKA at our institution were attributable to the associated learning curve, and thus not generalizable to high-volume surgeons or centres. Approximately 40% of cases were performed by a fellow or resident physician in both groups. It is entirely possible that the outcomes may be equivalent if the operating surgeon had overcome the steep learning curve associated with C-UKA. Previous studies have found that the Mako-assisted UKA had a learning curve of between six and 11 cases, compared with the Oxford mobile bearing UKA, which has a learning curve of 140 cases.47-50
In conclusion, our results demonstrate that patients undergoing R-UKA have a significantly lower all-cause revision rate and HLOS compared with those undergoing C-UKA. We found no difference in surgical duration, the odds of superficial surgical site infection, and PJI between the two groups. Our results suggest that R-UKA is the option of choice for managing symptomatic unicompartmental knee arthritis in carefully selected patients with isolated medial compartmental osteoarthritis, and particularly in the hands of lower-volume surgeons. Although we found that the HLOS in the R-UKA group was shorter, this should be interpreted with caution, given the non-contemporaneous nature of the two cohorts. The reduced revision risk justifies the continued use and development of R-UKA.
Take home message
- Robotic arm-assisted unicompartmental knee arthroplasty demonstrated a significantly lower risk of revision and a shorter hospital length of stay than conventional unicompartmental knee arthroplasty.
- Further research is warranted to determine the long-term clinical and economic implications of these findings.
Author contributions
T. Cheok: Conceptualization, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft
K. Law: Conceptualization, Investigation, Methodology, Project administration, Validation
J. F. Vermeir: Conceptualization, Data curation, Investigation, Methodology, Project administration, Writing – original draft
R. L. Jaarsma: Conceptualization, Supervision, Writing – review & editing
J. N. Doornberg: Conceptualization, Supervision, Writing – review & editing
A. M. Silva: Conceptualization, Project administration, Supervision, Writing – review & editing
Funding statement
The authors received no financial or material support for the research, authorship, and/or publication of this article.
ICMJE COI statement
J. F. Vermeir reports other financial or non-financial interests from Stryker, unrelated to this study. A. M. Silva reports consulting fees from Stryker and Johnson & Johnson, and support for attending meetings and/or travel from Stryker, Johnson & Johnson and Zimmer Biomet, all of which are unrelated to this study.
Data sharing
The datasets generated and analyzed in the current study are not publicly available due to data protection regulations. Access to data is limited to the researchers who have obtained permission for data processing. Further inquiries can be made to the corresponding author.
Acknowledgements
The authors would like to thank the orthopaedic surgeons involved in the care of patients included in this study. The authors also thank Louise Tuppin, Data Manager of the Orthopaedic Research and Data Management Unit at The Prince Charles Hospital, for her assistance with reports that supported this project. No AI was used in the research or manuscript development.
Ethical review statement
Ethical approval was sought and obtained before the commencement of this study (Approval No.: HREC/2025/MNH/122223).
Open access funding
The open access fee for this article was self-funded by the Department of Orthopaedic Surgery at The Prince Charles Hospital.
Supplementary material
Supplementary table showing the timeline for each revision complication.
© 2026 Cheok et al. This article is distributed under the terms of the Creative Commons Attributions (CC BY 4.0) licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original author and source are credited.
Data Availability
The datasets generated and analyzed in the current study are not publicly available due to data protection regulations. Access to data is limited to the researchers who have obtained permission for data processing. Further inquiries can be made to the corresponding author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and analyzed in the current study are not publicly available due to data protection regulations. Access to data is limited to the researchers who have obtained permission for data processing. Further inquiries can be made to the corresponding author.
