Abstract
Aims
Robotic-assisted unicompartmental knee arthroplasty (R-UKA) has been proposed as an approach to improve the results of the conventional manual UKA (C-UKA). The aim of this meta-analysis was to analyze the studies comparing R-UKA and C-UKA in terms of clinical outcomes, radiological results, operating time, complications, and revisions.
Methods
The literature search was conducted on three databases (PubMed, Cochrane, and Web of Science) on 20 February 2024 according to the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Inclusion criteria were comparative studies, written in the English language, with no time limitations, on the comparison of R-UKA and C-UKA. The quality of each article was assessed using the Downs and Black Checklist for Measuring Quality.
Results
Among the 3,669 articles retrieved, 21 studies on 19 series of patients were included. A total of 3,074 patients (59.5% female and 40.5% male; mean age 65.2 years (SD 3.9); mean BMI 27.4 kg/m2 (SD 2.2)) were analyzed. R-UKA obtained a superior Knee Society Score improvement compared to C-UKA (mean difference (MD) 4.9; p < 0.001) and better Forgotten Joint Score postoperative values (MD 5.5; p = 0.032). The analysis of radiological outcomes did not find a statistically significant difference between the two approaches. R-UKA showed longer operating time (MD 15.6; p < 0.001), but reduced complication and revision rates compared to C-UKA (5.2% vs 10.1% and 4.1% vs 7.2%, respectively).
Conclusion
This meta-analysis showed that the robotic approach for UKA provided a significant improvement in functional outcomes compared to the conventional manual technique. R-UKA showed similar radiological results and longer operating time, but reduced complication and revision rates compared to C-UKA. Overall, R-UKA seems to provide relevant benefits over C-UKA in the management of patients undergoing UKA.
Cite this article: Bone Jt Open 2024;5(5):374–384.
Take home message
This meta-analysis showed that robotic-assisted unicompartmental knee arthroplasty (R-UKA) provided a significant improvement in functional outcomes compared to the conventional manual technique (C-UKA).
R-UKA showed similar radiological results and longer operating time, but reduced complication and revision rates compared to C-UKA.
Overall, R-UKA seems to provide relevant benefits over C-UKA in the management of patients undergoing UKA.
Introduction
Unicompartmental knee arthroplasty (UKA) is an established and effective treatment for patients affected by unicompartmental osteoarthritis of the knee joint.1 The popularity of UKA has risen over the past two decades. Currently, UKA covers 10% of all knee arthroplasties worldwide.2 The potential advantages of UKA include the lower complication rate, reduced operating time, decreased intraoperative blood loss, reduced periarticular soft-tissue trauma, improved preservation of bone stock, better restoration of native kinematics, quicker recovery time, lower perioperative costs, improved functional outcomes, and increased patient satisfaction compared to the whole joint replacement.1,3,4 However, long-term survival has been the most pressing issue concerning the viability of conventional UKA (C-UKA).3 In fact, UKA presents concerns with regard to implant survival and revision rates.5
Accuracy of component positioning and limb alignment are important prognostic variables affecting implant survival and time to revision surgery following UKA.6-8 Techniques that improve the accuracy of implant positioning and limb alignment in UKA may help to improve long-term survival and reduce the burden of revisions.1 Given the sensitivity of UKA survival and functional outcomes to small changes in component position, robotic-assisted UKA (R-UKA) has become an attractive method for ensuring accurate execution of the surgical plan.3 Robotic technologies have been advanced to increase surgical precision, reduce the amount of soft-tissue and inflammatory response, and improve component alignment and soft-tissue balance, with the expectation that revision rates from technical errors may be mitigated.4,9 Thus, robotic assistance could enable surgeons to perform UKA with accuracy superior to conventional methods.10 Despite the potential of R-UKA, the available literature does not provide clear evidence for whether the proposed advantages of this technique translate into better clinical outcomes, and reduce revision rates, compared to C-UKA.
The present systematic review and meta-analysis aims at comparing R-UKA and C-UKA in terms of functional outcomes, radiological results, operating time, complications, and revisions.
Methods
Literature search
A literature search was conducted on the PubMed, Cochrane, and Web of Science databases on 20 February 2024 using the following criteria: (robot*) AND ((unicompartmental knee arthroplasty) OR (unicompartmental knee replacement) OR (UKA) OR (knee arthroplasty) OR (knee replacement) OR (knee prosthe*)). The trial was registered on PROSPERO (ID CRD42022373129). The guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) were used (Figure 1).11
Fig. 1
Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) flow diagram.
Studies selection and data extraction
The screening process and analysis were conducted by two independent observers (AB, AS), with disagreement resolved by consensus with a third author (AI). First, the articles were screened by title and abstract. The following inclusion criteria were used: comparative studies, written in English, with no time limitations, on the comparison of R-UKA and C-UKA. Exclusion criteria were: non-comparative studies, articles written in other languages, reviews, preclinical studies, case series, case reports, studies not comparing R-UKA and C-UKA, and studies not reporting clinical or radiological outcomes, operating time, revisions, or complications. In the second step, the full texts of the selected articles were screened, with further exclusions according to the previously described criteria. Relevant data (title, author, year of publication, journal, patients’ characteristics, follow-up time, clinical outcomes, radiological outcomes, operating time, complications, and revisions) were extracted and collected in a database, to be analyzed for the purposes of the present study.
Radiological outcomes included limb alignment and tibial component alignment parameters. The hip-knee-ankle angle (HKA) is a measure of lower limb alignment, defined as the angle between the mechanical axes of the femur and the tibia. The tibial component alignment was evaluated through two different angles measured on anteroposterior and lateral radiographs of the studied knees. The tibial slope (TS) is the angle formed between the vertical line of the tibial anatomical axis and the tibial plateau tangent, and reflects the tilt of the tibial plateau. The tibial coronal angle (TCA) represents the alignment of the tibial component on the coronal plane. The alignment angles were expressed as the difference from their optimal values to directly reflect the accuracy of the implant position (Figure 2).
Fig. 2
Illustration of radiological outcomes: hip-knee-ankle angle (HKA; left), tibial slope (TS; centre), and tibial coronal alignment angle (TCA; right).
Assessment of risk of bias and quality of evidence
The quality of each article was assessed independently by two authors (AB, AS) using the Downs and Black Checklist for Measuring Quality.12 This is a reliable tool containing 27 ‘yes’ or ‘no’ questions across five sections, providing a numerical score out of a maximum of 32 points. The five sections include questions about the overall quality of the study (ten items), the ability to generalize the study’s findings (three items), the study bias (seven items), the confounding and selection bias (six items), and the power of the study (one item).
Statistical analysis
Statistical analysis and forest plotting were performed according to Neyeloff et al,13 using the Meta XL tool for Excel (Microsoft, USA). The analysis was performed using random effects (DerSimonian & Laird) for the weighted mean difference (MD) of continuous variables, and the Peto method for odds ratios (ORs) of dichotomous variables. The I2 statistic for heterogeneity was included, as well as the Q statistic. In the case of continuous outcome, the weighted MD (δ) was used to calculate the Z-test statistic. The 95% confidence intervals (CIs) for the δ were derived and if the 95% CI excludes zero, the meta-analysis has shown a significant treatment effect at 0.05 level of significance. The derived results were used to define the test statistic z = δ/SE which is N(0, 1), and its corresponding p-value can be used to confirm or negate the result of the same meta-analysis. For dichotomous variables, the OR was used to calculate the test statistic. The 95% CIs for OR were derived; if the 95% CI excludes zero, the meta-analysis has shown a significant treatment effect at 0.05 level of significance. Fisher's exact test was used to check if the OR was statistically different from 1.
Results
Systematic review
A total of 3,669 articles were retrieved; after the removal of duplicates, and screening of the titles, abstracts, and full-texts, 21 studies were included according to the eligibility criteria (Table I). Among the 21 papers included, two were follow-ups of previous papers and therefore referring to the same original patient series: 19 studies were thus identified, and the most updated data extrapolated from the relative papers were included in the qualitative and quantitative data syntheses, as reported in Figure 3. A total of 3,074 patients (59.5% female and 40.5% male; mean age 65.2 years (standard deviation (SD) 3.9); mean BMI 27.4 kg/m2 (SD 2.2)) was analyzed: 1,352 patients in the R-UKA group and 1,695 in the C-UKA group. Among the studies reporting the knee compartment treated with UKA, 17 studies (15 series of patients) concerned the treatment of the medial compartment and one study the treatment of the lateral compartment, while two studies included both patients treated with medial UKA and patients treated with lateral UKA. Overall, 20 studies on 18 series of patients described the use of three different robotic systems: Mako (11 studies, nine series of patients), Navio (seven studies), and Acrobot (two studies). Only one study did not report the brand of the robotic system employed.
Table I.
| Author | Year | Journal | Study type | Treatment group | Pts, n | M, n | F, n | Mean age, yrs (SD) | Mean BMI, kg/m2 (SD) | Medial | Lateral | Robot |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Banger et al16 | 2021 | Bone Joint J | RCT | R-UKA | 55 | NR | NR | NR | NR | 55 | 0 | Mako |
| C-UKA | 49 | NR | NR | NR | NR | 49 | 0 | |||||
| Batailler et al14 | 2023 | Knee Surg Sports Traumatol Arthrosc | RCT | R-UKA | 33 | 21 | 12 | 65.6 (7.9) | 26.4 (3.5) | 33 | 0 | Navio |
| C-UKA | 33 | 12 | 21 | 67.1 (8.1) | 28.3 (5.6) | 33 | 0 | |||||
| Batailler et al17 | 2019 | Knee Surg Sports Traumatol Arthrosc | Retrospective case-control study | R-UKA | 80 | 53 | 27 | 69 (9.6) | 26.1 (4.1) | 57 | 23 | Navio |
| C-UKA | 80 | 53 | 27 | 68 (10) | 25.5 (3.9) | 57 | 23 | |||||
| Blyth et al18 | 2017 | Bone Joint Res | RCT | R-UKA | 64 | 29 | 35 | 68 (7.97) | 26.9 (3.26) | 64 | 0 | Mako |
| C-UKA | 62 | 27 | 35 | 69 (6) | 27.4 (3.38) | 62 | 0 | |||||
| Canetti et al19 | 2018 | Arch Orthop Trauma Surg | Retrospective comparative study | R-UKA | 11 | 2 | 9 | 66.5 (6.8) | 24.2 (4.3) | 0 | 11 | Navio |
| C-UKA | 17 | 5 | 12 | 59.5 (9.9) | 26.3 (3.8) | 0 | 17 | |||||
| Cobb et al20 | 2006 | J Bone Joint Surg Br | RCT | R-UKA | 13 | 8 | 5 | NR | NR | 13 | 0 | Acrobot |
| C-UKA | 14 | NR | NR | NR | NR | 14 | 0 | |||||
| Cool et al21 | 2019 | J Arthroplasty | Retrospective longitudinal study | R-UKA | 246 | 114 | 132 | NR | NR | NR | NR | NR |
| C-UKA | 492 | 210 | 282 | NR | NR | NR | NR | |||||
| Crizer et al22 | 2021 | Adv Orthop | Retrospective cohort study | R-UKA | 50 | 29 | 21 | 63 (11) | 28.1 (4.5) | 50 | 0 | Navio |
| C-UKA | 39 | 22 | 17 | 58 (13) | 28.3 (4.1) | 39 | 0 | |||||
| Foissey et al23 | 2022 | Int Orthop | Retrospective cohort study | R-UKA | 197 | 89 | 108 | 66.7 (7.7) | 27.5 (3.3) | 197 | 0 | Navio |
| C-UKA | 159 | 61 | 98 | 68.3 (8.1) | 27 (3.4) | 159 | 0 | |||||
| Gilmour et al24 | 2018 | J Arthroplasty | RCT | R-UKA | 58 | 32 | 26 | 61.8 (7.8) | NR | 58 | 0 | Mako |
| C-UKA | 54 | 28 | 26 | 62.6 (7.1) | NR | 54 | 0 | |||||
| Hansen et al25 | 2014 | J Arthroplasty | Retrospective comparative study | R-UKA | 30 | 16 | 14 | 57.1 (9.8) | 32.1 (5.5) | 30 | 0 | Mako |
| C-UKA | 32 | 11 | 21 | 60.7 (11.8) | 33.3 (5.7) | 32 | 0 | |||||
| Kayani et al26 | 2019 | Bone Joint J | Prospective cohort study | R-UKA | 73 | 32 | 41 | 65.3 (8.6) | NR | 73 | 0 | Mako |
| C-UKA | 73 | 34 | 39 | 66.1 (5.8) | NR | 73 | 0 | |||||
| Lonner et al27 | 2010 | Clin Orthop Relat Res | Retrospective cohort study | R-UKA | 31 | 15 | 16 | NR | 30 (5) | 31 | 0 | Mako |
| C-UKA | 27 | 17 | 10 | NR | 28 (4) | 27 | 0 | |||||
| MacCallum et al28 | 2016 | Eur J Orthop Surg Traumatol | Retrospective cohort study | R-UKA | 87 | NR | NR | NR | NR | 87 | 0 | Mako |
| C-UKA | 177 | NR | NR | NR | NR | 177 | 0 | |||||
| Maritan et al15 | 2023 | Knee Surg Sports Traumatol Arthrosc | Retrospective cohort study | R-UKA | 52 | 11 | 41 | 60.9 (8.4) | 26.2 (3.3) | 52 | 0 | Mako |
| C-UKA | 43 | 6 | 37 | 61.5 (8.5) | 27 (2.8) | 43 | 0 | |||||
| Mergenthaler et al29 | 2021 | Knee Surg Sports Traumatol Arthrosc | Retrospective case-control study | R-UKA | 200 | 78 | 122 | 66.7 (9.3) | 27 (4.2) | 159 | 41 | Navio |
| C-UKA | 191 | 58 | 133 | 67.1 (10.7) | 26.4 (4.2) | 135 | 59 | |||||
| Negrín et al30 | 2021 | Knee Surg Relat Res | Retrospective cohort study | R-UKA | 16 | 7 | 9 | NR | NR | 16 | 0 | Navio |
| C-UKA | 18 | 12 | 6 | NR | NR | 18 | 0 | |||||
| Park et al31 | 2019 | PLoS One | Retrospective comparative study | R-UKA | 55 | 11 | 44 | NR | 25.5 (2.5) | 55 | 0 | Mako |
| C-UKA | 57 | 7 | 50 | NR | 25.9 (3.7) | 57 | 0 | |||||
| Rodriguez et al32 | 2005 | Int J Med Robot | RCT | R-UKA | 13 | NR | NR | NR | NR | 13 | 0 | Acrobot |
| C-UKA | 15 | NR | NR | NR | NR | 15 | 0 | |||||
| Wong et al33 | 2019 | Knee Surg Sports Traumatol Arthrosc | Retrospective cohort study | R-UKA | 58 | 30 | 28 | 70.4 (9.7) | 28.2 (5.6) | 58 | 0 | Mako |
| C-UKA | 118 | 44 | 74 | 67.9 (9.5) | 28.7 (4.4) | 118 | 0 | |||||
| Wu et al34 | 2021 | J Clin Med | Retrospective cohort study | R-UKA | 52 | 11 | 41 | 68.5 (9.8) | NR | 52 | 0 | Mako |
| C-UKA | 61 | 9 | 52 | 69.4 (9.1) | NR | 61 | 0 |
-
C-UKA, conventional unicompartmental knee arthroplasty; NR, not reported; RCT, randomized controlled trial; R-UKA, robotic-assisted unicompartmental knee arthroplasty; SD, standard deviation.
Fig. 3
Correspondence between the 21 articles retrieved and the 19 series of patients analyzed.
Meta-analysis
Among the outcome measures extracted, a meta-analysis was performed on the following parameters: Knee Society Score (KSS),35 range of motion (ROM), visual analogue scale (VAS) for pain (0 = no pain, 10 = worst pain), Forgotten Joint Score (FJS),36 12-Item Short Form Survey (SF-12) questionnaire,37 HKA, TS, TCA, operating time, postoperative complications, and revisions. A sub-analysis was performed on the medial UKAs: available parameters that could be meta-analyzed included KSS, HKA, TS, TCA, operating time, postoperative complications, and revisions. Another sub-analysis was performed on the two most documented robotic systems: Mako and Navio. Available parameters that could be meta-analyzed include TS, TCA, operating time, and complications for Mako, KSS, TS, operating time, and revisions for Navio.
Clinical outcomes
KSS: The analysis of KSS improvement from preoperative to postoperative values (Figure 4) demonstrated a statistically significant difference in favour of the R-UKA group (p < 0.001; MD 4.9; standard error (SE) 1.3). All the studies included in the meta-analysis of KSS improvement used the Navio robotic system. Similarly, the analysis of KSS postoperative values in the medial UKA subgroup (Figure 4) found a statistically significant difference in favour of R-UKA (p < 0.001; MD 5.0; SE 1.0).
Fig. 4
a) Knee Society Score (KSS): forest plot of the individual studies and weighted mean difference (WMD) for KSS improvement, including a 95% confidence interval (CI). The size of the squares shows the weight of the study. Robotic-assisted unicompartmental knee arthroplasty (R-UKA) showed better KSS values compared to conventional UKA (C-UKA) (p < 0.001). b) KSS, medial UKA subgroup: forest plot of the individual studies and WMD for KSS improvement, including a 95% CI. The size of the squares shows the weight of the study. R-UKA showed better KSS values compared to C-UKA (p = 0.022). c) Forgotten Joint Score (FJS): forest plot of the individual studies and WMD for FJS values, including a 95% CI. The size of the squares shows the weight of the study. R-UKA showed better FJS values compared to C-UKA (p = 0.022).
FJS: The analysis of FJS postoperative values (Figure 4) demonstrated a statistically significant difference in favour of R-UKA (p = 0.032; MD 5.5; SE 2.5).
VAS: The analysis of VAS, ROM, and SF-12 improvements from preoperative to postoperative values did not find a statistically significant difference between R-UKA and C-UKA.
Radiological outcomes
HKA: The analysis of HKA improvement from preoperative to postoperative values did not find a statistically significant difference between R-UKA and C-UKA, nor did the sub-analysis of the medial UKA subgroup.
TS: The analysis of TS postoperative values did not find a statistically significant difference between R-UKA and C-UKA, nor did the sub-analyses of TS postoperative values in the medial UKA subgroup and Mako subgroup. A statistically significant difference was found in the Navio sub-analysis with lower values obtained with the robotic-assisted approach (p < 0.001; MD -2.0; SE 0.3).
TCA: The analysis of TCA postoperative values did not find a statistically significant difference between R-UKA and C-UKA, nor did the sub-analyses of the medial UKA subgroup and Mako subgroup.
Perioperative parameters
Operating time: The analysis of operating time (Figure 5) demonstrated a statistically significant difference in favour of the C-UKA group (p < 0.001; MD 15.6; SE 3.3). Similarly, the analysis of operating time in the medial UKA subgroup (Figure 5) found a statistically significant difference in favour of C-UKA (p < 0.001; MD 16.1; SE 3.5). No statistically significant differences were found in the sub-analyses of Mako and Navio subgroups.
Fig. 5
a) Operating time: forest plot of the individual studies and pooled weighted mean difference (WMD) for operating time, including a 95% confidence interval (CI). The size of the squares shows the weight of the study. Robotic-assisted unicompartmental knee arthroplasty (R-UKA) showed longer operating time compared to conventional UKA (C-UKA) (p < 0.001). b) Operating time, medial UKA subgroup: forest plot of the individual studies and pooled WMD for operating time, including a 95% CI. The size of the squares shows the weight of the study. R-UKA showed longer operating time compared to C-UKA (p < 0.001).
Complications: The analysis of postoperative complications showed a rate of 5.2% for R-UKA and of 10.1% for C-UKA. The sub-analysis of the medial UKA subgroup showed a rate of 6.5% for R-UKA and 9.2% for C-UKA. The sub-analysis of the MAKO subgroup showed a rate of 5.8% for R-UKA and 5.4% for C-UKA. These differences did not reach statistical significance. Details of complications are reported in Table II.
Table II.
Complications types and frequency in robotic-assisted versus conventional manual unicompartmental knee arthroplasty.
| Complication | R-UKA, n (%) | C-UKA, n (%) |
|---|---|---|
| Aseptic loosening | 4 (19) | 9 (23.1) |
| Postop knee pain with/without stiffness or swelling | 9 (42.9) | 3 (7.7) |
| Limb malalignment | 0 (0) | 10 (25.6) |
| Myocardial infarction | 0 (0) | 9 (23.1) |
| Implant failure | 4 (19) | 4 (10.3) |
| Deep haematoma | 1 (4.8) | 1 (2.6) |
| Infection | 1 (4.8) | 1 (2.6) |
| Postop cellulitis | 1 (4.8) | 1 (2.6) |
| Acute urinary retention | 1 (4.8) | 0 (0) |
| Perforated peptic ulcer | 0 (0) | 1 (2.6) |
| Total | 21 (100) | 39 (100) |
-
C-UKA, conventional manual unicompartmental knee arthroplasty; R-UKA, robotic-assisted unicompartmental knee arthroplasty.
Revisions: The analysis of revision rates showed a rate of 4.1% for R-UKA and 7.2% for C-UKA. The sub-analysis of the medial UKA subgroup showed a rate of 3.2% for R-UKA and 6.6% for C-UKA. The sub-analysis of the Navio subgroup showed a rate of 5.3% for R-UKA and 9.7% for C-UKA. These differences did not reach statistical significance.
Risk of bias
The Downs and Black Checklist for Measuring Quality for assessing the risk of bias assigns each study an ‘excellent’ ranking for scores ≥ 26, ‘good’ for scores from 20 to 25, ‘fair’ for scores between 15 and 19, and ‘poor’ for scores ≤ 14 points. According to these criteria, none of the included studies was classified as poor, 1 was fair, 16 were good, and 4 were excellent (Figure 6).
Fig. 6
Downs and Black’s tool for risk of bias assessment including the answers to the 27 ‘yes’ or ‘no’ questions for the each of the included studies.12 Green: yes. Red: no.
Discussion
The main finding of this meta-analysis is that the robotic approach for UKA provided a significant improvement in functional outcomes compared to the conventional manual technique.
Robotic-assisted surgery has become increasingly popular in UKA and is one of the most discussed topics in the current literature. R-UKA provides live intraoperative data on knee kinematics through the arc of flexion, which can be used to fine-tune implant positioning and optimize soft-tissue tensioning.1 In light of this, R-UKA offers a unique opportunity to achieve high levels of accuracy in implant positioning, which may help to improve implant survival and reduce the number of revisions.1 The accuracy superior to conventional methods can also translate to a better outcome,10 as demonstrated by this meta-analysis.
The functional result is key in the perspective of patients undergoing UKA surgery, since clinical outcomes and ultimately patient satisfaction remain the fundamental goals of this procedure.38 Previous meta-analyses on a smaller number of studies have tried to quantify benefits in terms of clinical outcomes. The meta-analysis conducted by Chin et al39 found significantly superior KSS improvement in R-UKA compared to C-UKA up to three years after surgery. On the other hand, the meta-analysis by Zhang et al40 failed to find a decisive superiority in functional outcomes when comparing R-UKA with C-UKA, describing similar clinical results for the two approaches. The current meta-analysis, including an up-to-date research of the literature with a higher number of comparative studies, shed new light on this controversial issue, quantifying the clinical benefit. The present meta-analysis found a statistically significant difference in terms of KSS improvement and FJS between R-UKA and C-UKA. Specifically, a mean difference of 4.9 points was found in the analysis of KSS improvement in favour of R-UKA. Although this difference did not reach the minimal clinically important difference (MCID) of 5.4 points reported in the literature for KSS,41 it is very close to this value and could hardly be interpreted as clinically irrelevant. The results of the FJS analysis showed a MD of 5.5 points in favour of R-UKA. Similarly in this case, while not reaching the MCID of this score (8.8 points),42 it still represents a considerable functional difference between the two approaches. This is of particular interest in terms of clinical relevance, as well as in terms of clinical indication for using robotic-assisted technology. In fact, robotic assistance showed different results when used for TKA. In a recent systematic review and meta-analysis, Bensa et al43 investigated the results of 14 randomized controlled trial (RCTs) for a total of 2,255 patients and found that R-TKA did not provide overall superior results compared to C-TKA in terms of clinical and radiological outcomes, while showing longer operating time, thus questioning the benefits of robotic-assisted surgery to improve TKA outcome in the routine clinical practice. An opposite scenario was found instead for UKA, where significant functional advantages of the robotic approach were found.
Another relevant aspect of the comparison between R-UKA and C-UKA is represented by the analysis of the radiological outcomes. This aspect plays a crucial role in the outcome of UKA, especially concerning the long-term survival of the implant.44 In fact, it is generally believed that UKA survival is mainly related to the original leg alignment,45 with some authors encouraging only mild under-correction of varus deformities in order to obtain the best results and the longest survival.46 Overall, there is currently no general agreement on the superiority of the robotic technique in achieving better UKA positioning, with the available studies reporting contrasting results. Hernigou and Deschamps47 documented that the best clinical and radiological results in UKA were achieved when HKA was between 170° and 180°. The authors underlined that the alignment affects the progression of osteoarthritis in the opposite compartment of the knee and wear in the tibial component, especially when there has been an over-correction of constitutional varus. With regard to posterior tibial slope, Chen et al48 observed that the best mid-term results for medial UKA were obtained with values ranging from 4° to 7°. This study did not find a statistically significant difference of limb alignment and implant positioning between R-UKA and C-UKA, especially in terms of HKA, tibial slope, and TCA. This result is partially in contrast with previous reviews, which found R-UKA to be more precise than C-UKA in these aspects.39,49 However, the lack of difference found in the present study may be explained by the fact that, differently from UKA, the aim of UKA is not to correct the limb alignment, but rather to restore the pre-disease anatomy of the knee compartment treated, which increases the complexity of the obtained data interpretation.50,51
Perioperative parameters are also important when comparing R-UKA and C-UKA. This meta-analysis found a statistically significant difference between the two approaches in terms of operating time, favouring C-UKA over R-UKA by 15 minutes. This result is confirmed by several studies in the current literature showing similar findings, mainly due to surgical preparation, milling, and registration stages of the R-UKA surgical procedure.39,40,49 The learning curve of the robotic-assisted procedure may be a relevant aspect affecting the operating time, although R-UKA has a rather flat learning curve, meaning that surgeons with limited experience require a relatively limited number of surgeries before achieving routine efficiency with this approach.52 Furthermore, R-UKA seems to enable younger or inexperienced surgeons to achieve better accuracy when performing this intervention, suggesting that the use of robotic-assisted technique can also improve the learning curve of performing C-UKA.10
Complications and revisions are another important aspect when performing any prosthetic implant. Previous literature analyses showed controversial findings. A meta-analysis conducted by Zhang et al40 reported a significantly reduced complication rate in R-UKA, and another meta-analysis published by Sun et al53 showed significantly inferior complication and revision rates in R-UKA, while Chin et al39 and Fu et al49 were not able to find robotic assistance advantages in terms of complications and revisions. The present meta-analysis found a considerable difference between R-UKA and C-UKA in terms of complications and revisions, with C-UKA showing both complication and revision rates almost twice as high compared to R-UKA (10.1% vs 5.2% and 7.2% vs 4.1%, respectively). The fact that these differences did not reach statistical significance is probably due to the relatively limited number of patients analyzed from the available literature. For instance, data from the Australian Orthopaedic Association National Joint Arthroplasty Registry and from a large USA database suggested that R-UKA was associated with reduced revision rates compared to C-UKA.54,55 Additionally, C-UKA was found to have a greater number of risk factors for revision procedures compared to R-UKA: these included high BMI, congestive heart failure, diabetes mellitus, hypertension, hypothyroidism, opioid dependency, and rheumatoid arthritis, suggesting that robotic technology may help in improving the outcomes of UKA in specific patient categories, especially when presenting particular comorbidities.55 These findings prove that, despite the longer operating time and the increased equipment required in the theatre, the use of robotic technology does not result in increased adverse events and could even help to reduce the complication and revision rates of UKA.
The sub-analysis of the medial UKA subgroup confirmed the results obtained in the main analysis. The analysis of KSS postoperative values showed a statistically significant difference of 5.0 points in favour of R-UKA, once again very close to the MCID value of 5.4 points. No significant difference was found in the analysis of radiological outcomes, while operating time favoured C-UKA of about 16 minutes. Complication and revision rates were considerably higher in C-UKA (9.2% vs 6.5% and 6.6% vs 3.2%, respectively), even if without reaching statistical significance. Unfortunately, it was not possible to perform a sub-analysis on the lateral UKA subgroup due to the limited number of studies focusing on this compartment. On the other hand, a sub-analysis could be performed focusing on the two most used systems: Mako and Navio. Even if both are semiautonomous robotic systems, the main difference between the two lies in the need for preoperative imaging: Mako requires a preoperative CT scan, while Navio is an imageless system. The sub-analysis of the Mako robotic system did not show any statistically significant difference compared to the conventional manual group in terms of TS, TCA, operating time, and complications. The sub-analysis of the Navio robotic system showed a statistically significant difference in favour of the R-UKA group in terms of KSS, confirming the results of the main analysis, and TS, while no difference was found in terms of operating time and revisions. Still, while these data are of interest (as the results could be linked to the specific system used) more data on each specific robotic system are required to clarify the benefits of the different approaches.
This systematic review and meta-analysis presents some limitations that require consideration. First, the studies analyzed presented a considerable heterogeneity of designs, with only six RCTs included (two of which are almost 20 years old). Due to the lack of randomization and retrospective nature of some studies, selection and recall bias cannot be completely excluded. Furthermore, the selected studies lacked standardization in data collection and reporting, particularly in terms of radiological outcomes. The lack of common outcome measures and associated postoperative follow-up timeframes resulted in a limited number of studies analyzed for each outcome. As such, a relatively small number of patients were included for each analysis and hence may not be fully representative of the general population. Not enough data were available for the analysis of surgeons’ experience between the two groups, with only one study reporting detailed information on this relevant aspect. Moreover, the included studies used different robotic systems and lacked objective data for the quantification of soft-tissue balancing, which represents a crucial factor for implant durability.56 Finally, there may be commercial bias in some of the studies: three studies received non-commercial grants, six received commercial funding, and five did not report if external funding or financial support was received. Despite these limitations, this meta-analysis provided important findings by quantifying the advantages and limitations of R-UKA, which reported overall encouraging results for improving the UKA outcome in the routine clinical practice. This is of clinical relevance. Indeed, if confirmed on a larger number of patients and possibly by more randomized controlled trials, the improvement in functional outcomes, complications, and revisions provided by R-UKA would represent a decisive advantage over C-UKA in the management of patients undergoing UKA.
References
1. Kayani B , Haddad FS . Robotic unicompartmental knee arthroplasty: Current challenges and future perspectives . Bone Joint Res . 2019 ; 8 ( 6 ): 228 – 231 . Crossref PubMed Google Scholar
2. Kleeblad LJ , Zuiderbaan HA , Hooper GJ , Pearle AD . Unicompartmental knee arthroplasty: state of the art . Journal of ISAKOS . 2017 ; 2 ( 2 ): 97 – 107 . Crossref Google Scholar
3. Christ AB , Pearle AD , Mayman DJ , Haas SB . Robotic-assisted unicompartmental knee arthroplasty: state-of-the art and review of the literature . J Arthroplasty . 2018 ; 33 ( 7 ): 1994 – 2001 . Crossref PubMed Google Scholar
4. Lonner JH , Klement MR . Robotic-assisted medial unicompartmental knee arthroplasty: options and outcomes . J Am Acad Orthop Surg . 2019 ; 27 ( 5 ): e207 – e214 . Crossref PubMed Google Scholar
5. Tyagi V , Farooq M . Unicompartmental knee arthroplasty: indications, outcomes, and complications . Conn Med . 2017 ; 81 ( 2 ): 87 – 90 . PubMed Google Scholar
6. Blaney J , Harty H , Doran E , et al. Five-year clinical and radiological outcomes in 257 consecutive cementless Oxford medial unicompartmental knee arthroplasties . Bone Joint J . 2017 ; 99-B ( 5 ): 623 – 631 . Crossref PubMed Google Scholar
7. Chalmers BP , Mehrotra KG , Sierra RJ , Pagnano MW , Taunton MJ , Abdel MP . Reliable outcomes and survivorship of unicompartmental knee arthroplasty for isolated compartment osteonecrosis . Bone Joint J . 2018 ; 100-B ( 4 ): 450 – 454 . Crossref PubMed Google Scholar
8. Walker T , Zahn N , Bruckner T , et al. Mid-term results of lateral unicondylar mobile bearing knee arthroplasty: a multicentre study of 363 cases . Bone Joint J . 2018 ; 100-B ( 1 ): 42 – 49 . Crossref PubMed Google Scholar
9. Kayani B , Tahmassebi J , Ayuob A , Konan S , Oussedik S , Haddad FS . A prospective randomized controlled trial comparing the systemic inflammatory response in conventional jig-based total knee arthroplasty versus robotic-arm assisted total knee arthroplasty . Bone Joint J . 2021 ; 103-B ( 1 ): 113 – 122 . Crossref PubMed Google Scholar
10. Karia M , Masjedi M , Andrews B , Jaffry Z , Cobb J . Robotic assistance enables inexperienced surgeons to perform unicompartmental knee arthroplasties on dry bone models with accuracy superior to conventional methods . Adv Orthop . 2013 ; 2013 : 481039 . Crossref PubMed Google Scholar
11. Moher D , Liberati A , Tetzlaff J , Altman DG , PRISMA Group . Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement . Int J Surg . 2010 ; 8 ( 5 ): 336 – 341 . Crossref PubMed Google Scholar
12. Downs SH , Black N . The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions . J Epidemiol Community Health . 1998 ; 52 ( 6 ): 377 – 384 . Crossref PubMed Google Scholar
13. Neyeloff JL , Fuchs SC , Moreira LB . Meta-analyses and Forest plots using a microsoft excel spreadsheet: step-by-step guide focusing on descriptive data analysis . BMC Res Notes . 2012 ; 5 ( 1 ): 52 . Crossref PubMed Google Scholar
14. Batailler C , Lording T , Naaim A , Servien E , Cheze L , Lustig S . No difference of gait parameters in patients with image-free robotic-assisted medial unicompartmental knee arthroplasty compared to a conventional technique: early results of a randomized controlled trial . Knee Surg Sports Traumatol Arthrosc . 2023 ; 31 ( 3 ): 803 – 813 . Crossref PubMed Google Scholar
15. Maritan G , Franceschi G , Nardacchione R , et al. Similar survivorship at the 5-year follow-up comparing robotic-assisted and conventional lateral unicompartmental knee arthroplasty . Knee Surg Sports Traumatol Arthrosc . 2023 ; 31 ( 3 ): 1063 – 1071 . Crossref PubMed Google Scholar
16. Banger M , Doonan J , Rowe P , Jones B , MacLean A , Blyth MJB . Robotic arm-assisted versus conventional medial unicompartmental knee arthroplasty: five-year clinical outcomes of a randomized controlled trial . Bone Joint J . 2021 ; 103-B ( 6 ): 1088 – 1095 . Crossref PubMed Google Scholar
17. Batailler C , White N , Ranaldi FM , Neyret P , Servien E , Lustig S . Improved implant position and lower revision rate with robotic-assisted unicompartmental knee arthroplasty . Knee Surg Sports Traumatol Arthrosc . 2019 ; 27 ( 4 ): 1232 – 1240 . Crossref PubMed Google Scholar
18. Blyth MJG , Anthony I , Rowe P , Banger MS , MacLean A , Jones B . Robotic arm-assisted versus conventional unicompartmental knee arthroplasty: exploratory secondary analysis of a randomised controlled trial . Bone Joint Res . 2017 ; 6 ( 11 ): 631 – 639 . Crossref PubMed Google Scholar
19. Canetti R , Batailler C , Bankhead C , Neyret P , Servien E , Lustig S . Faster return to sport after robotic-assisted lateral unicompartmental knee arthroplasty: a comparative study . Arch Orthop Trauma Surg . 2018 ; 138 ( 12 ): 1765 – 1771 . Crossref PubMed Google Scholar
20. Cobb J , Henckel J , Gomes P , et al. Hands-on robotic unicompartmental knee replacement: a prospective, randomised controlled study of the acrobot system . J Bone Joint Surg Br . 2006 ; 88-B ( 2 ): 188 – 197 . Crossref PubMed Google Scholar
21. Cool CL , Needham KA , Khlopas A , Mont MA . Revision analysis of robotic arm-assisted and manual unicompartmental knee arthroplasty . J Arthroplasty . 2019 ; 34 ( 5 ): 926 – 931 . Crossref PubMed Google Scholar
22. Crizer MP , Haffar A , Battenberg A , McGrath M , Sutton R , Lonner JH . Robotic assistance in unicompartmental knee arthroplasty results in superior early functional recovery and is more likely to meet patient expectations . Adv Orthop . 2021 ; 2021 : 4770960 . Crossref PubMed Google Scholar
23. Foissey C , Batailler C , Vahabi A , Fontalis A , Servien E , Lustig S . Better accuracy and implant survival in medial imageless robotic-assisted unicompartmental knee arthroplasty compared to conventional unicompartmental knee arthroplasty: two- to eleven-year follow-up of three hundred fifty-six consecutive knees . Int Orthop . 2023 ; 47 ( 2 ): 533 – 541 . Crossref PubMed Google Scholar
24. Gilmour A , MacLean AD , Rowe PJ , et al. Robotic-arm-assisted vs conventional unicompartmental knee arthroplasty. The 2-year clinical outcomes of a randomized controlled trial . J Arthroplasty . 2018 ; 33 ( 7S ): S109 – S115 . Crossref PubMed Google Scholar
25. Hansen DC , Kusuma SK , Palmer RM , Harris KB . Robotic guidance does not improve component position or short-term outcome in medial unicompartmental knee arthroplasty . J Arthroplasty . 2014 ; 29 ( 9 ): 1784 – 1789 . Crossref PubMed Google Scholar
26. Kayani B , Konan S , Tahmassebi J , Rowan FE , Haddad FS . An assessment of early functional rehabilitation and hospital discharge in conventional versus robotic-arm assisted unicompartmental knee arthroplasty . Bone Joint J . 2019 ; 101-B ( 1 ): 24 – 33 . Crossref PubMed Google Scholar
27. Lonner JH , John TK , Conditt MA . Robotic arm-assisted UKA improves tibial component alignment: a pilot study . Clin Orthop Relat Res . 2010 ; 468 ( 1 ): 141 – 146 . Crossref PubMed Google Scholar
28. MacCallum KP , Danoff JR , Geller JA . Tibial baseplate positioning in robotic-assisted and conventional unicompartmental knee arthroplasty . Eur J Orthop Surg Traumatol . 2016 ; 26 ( 1 ): 93 – 98 . Crossref PubMed Google Scholar
29. Mergenthaler G , Batailler C , Lording T , Servien E , Lustig S . Is robotic-assisted unicompartmental knee arthroplasty a safe procedure? A case control study . Knee Surg Sports Traumatol Arthrosc . 2021 ; 29 ( 3 ): 931 – 938 . Crossref PubMed Google Scholar
30. Negrín R , Duboy J , Iñiguez M , et al. Robotic-assisted vs conventional surgery in medial unicompartmental knee arthroplasty: a clinical and radiological study . Knee Surg Relat Res . 2021 ; 33 ( 1 ): 5 . Crossref PubMed Google Scholar
31. Park KK , Han CD , Yang IH , Lee WS , Han JH , Kwon HM . Robot-assisted unicompartmental knee arthroplasty can reduce radiologic outliers compared to conventional techniques . PLoS One . 2019 ; 14 ( 12 ): e0225941 . Crossref PubMed Google Scholar
32. Rodriguez F , Harris S , Jakopec M , et al. Robotic clinical trials of uni-condylar arthroplasty . Int J Med Robot . 2005 ; 1 ( 4 ): 20 – 28 . Crossref PubMed Google Scholar
33. Wong J , Murtaugh T , Lakra A , Cooper HJ , Shah RP , Geller JA . Robotic-assisted unicompartmental knee replacement offers no early advantage over conventional unicompartmental knee replacement . Knee Surg Sports Traumatol Arthrosc . 2019 ; 27 ( 7 ): 2303 – 2308 . Crossref PubMed Google Scholar
34. Wu C , Fukui N , Lin Y-K , et al. Comparison of robotic and conventional unicompartmental knee arthroplasty outcomes in patients with osteoarthritis: a retrospective cohort study . J Clin Med . 2021 ; 11 ( 1 ): 220 . Crossref PubMed Google Scholar
35. Insall JN , Dorr LD , Scott RD , Scott WN . Rationale of the Knee Society clinical rating system . Clin Orthop Relat Res . 1989 ; 248 : 13 – 14 . PubMed Google Scholar
36. Behrend H , Giesinger K , Giesinger JM , Kuster MS . The “forgotten joint” as the ultimate goal in joint arthroplasty: validation of a new patient-reported outcome measure . J Arthroplasty . 2012 ; 27 ( 3 ): 430 – 436 . Crossref PubMed Google Scholar
37. Ware J , Kosinski M , Keller SD . A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity . Med Care . 1996 ; 34 ( 3 ): 220 – 233 . Crossref PubMed Google Scholar
38. Patel KT , Lewis TL , Gill P , Chatterton M . The patient perspective, experience and satisfaction of day case unicompartmental knee arthroplasty: a short-term mixed-methods study . Knee . 2021 ; 33 : 378 – 385 . Crossref PubMed Google Scholar
39. Chin BZ , Tan SSH , Chua KCX , Budiono GR , Syn NL-X , O’Neill GK . Robot-assisted versus conventional total and unicompartmental knee arthroplasty: a meta-analysis of radiological and functional outcomes . J Knee Surg . 2021 ; 34 ( 10 ): 1064 – 1075 . Crossref PubMed Google Scholar
40. Zhang F , Li H , Ba Z , Bo C , Li K . Robotic arm-assisted vs conventional unicompartmental knee arthroplasty: a meta-analysis of the effects on clinical outcomes . Medicine (Baltimore) . 2019 ; 98 ( 35 ): e16968 . Crossref PubMed Google Scholar
41. Lee WC , Kwan YH , Chong HC , Yeo SJ . The minimal clinically important difference for Knee Society Clinical Rating System after total knee arthroplasty for primary osteoarthritis . Knee Surg Sports Traumatol Arthrosc . 2017 ; 25 ( 11 ): 3354 – 3359 . Crossref PubMed Google Scholar
42. Longo UG , De Salvatore S , Candela V , et al. Unicompartmental knee arthroplasty: minimal important difference and patient acceptable symptom state for the Forgotten Joint Score . Medicina (Kaunas) . 2021 ; 57 ( 4 ): 324 . Crossref PubMed Google Scholar
43. Bensa A , Sangiorgio A , Deabate L , Illuminati A , Pompa B , Filardo G . Robotic-assisted mechanically aligned total knee arthroplasty does not lead to better clinical and radiological outcomes when compared to conventional TKA: a systematic review and meta-analysis of randomized controlled trials . Knee surgery, sports traumatology, arthroscopy . 2023 ; 31 ( 11 ): 4680 – 4691 . Crossref PubMed Google Scholar
44. Abdel MP , Ollivier M , Parratte S , Trousdale RT , Berry DJ , Pagnano MW . Effect of postoperative mechanical axis alignment on survival and functional outcomes of modern total knee arthroplasties with cement: a concise follow-up at 20 years . J Bone Joint Surg Am . 2018 ; 100-A ( 6 ): 472 – 478 . Crossref PubMed Google Scholar
45. Scott RD . Three decades of experience with unicompartmental knee arthroplasty: mistakes made and lessons learned . Orthopedics . 2006 ; 29 ( 9 ): 829 – 831 . Crossref PubMed Google Scholar
46. Marullo M , Russo A , Spreafico A , Romagnoli S . Mild valgus alignment after lateral unicompartmental knee arthroplasty led to lower functional results and survivorship at mean 8-year follow-up . J Arthroplasty . 2023 ; 38 ( 1 ): 37 – 42 . Crossref PubMed Google Scholar
47. Hernigou P , Deschamps G . Alignment influences wear in the knee after medial unicompartmental arthroplasty . Clin Orthop Relat Res . 2004 ; 2004 ( 423 ): 161 – 165 . Crossref PubMed Google Scholar
48. Chen Z , Chen K , Yan Y , et al. Effects of posterior tibial slope on the mid-term results of medial unicompartmental knee arthroplasty . Arthroplasty . 2021 ; 3 ( 1 ): 11 . Crossref PubMed Google Scholar
49. Fu J , Wang Y , Li X , et al. Robot-assisted vs. conventional unicompartmental knee arthroplasty: systematic review and meta-analysis . Orthopade . 2018 ; 47 ( 12 ): 1009 – 1017 . Crossref PubMed Google Scholar
50. Bellemans J , Colyn W , Vandenneucker H , Victor J . The Chitranjan Ranawat award: is neutral mechanical alignment normal for all patients? The concept of constitutional varus . Clin Orthop Relat Res . 2012 ; 470 ( 1 ): 45 – 53 . Crossref PubMed Google Scholar
51. Vasso M , Del Regno C , D’Amelio A , Viggiano D , Corona K , Schiavone Panni A . Minor varus alignment provides better results than neutral alignment in medial UKA . Knee . 2015 ; 22 ( 2 ): 117 – 121 . Crossref PubMed Google Scholar
52. Chen X , Deng S , Sun M-L , He R . Robotic arm-assisted arthroplasty: the latest developments . Chin J Traumatol . 2022 ; 25 ( 3 ): 125 – 131 . Crossref PubMed Google Scholar
53. Sun Y , Liu W , Hou J , Hu X , Zhang W . Does robotic-assisted unicompartmental knee arthroplasty have lower complication and revision rates than the conventional procedure? A systematic review and meta-analysis . BMJ Open . 2021 ; 11 ( 8 ): e044778 . Crossref PubMed Google Scholar
54. Smith PG , McAuliffe MJ , McDougall C , et al. Hip, Knee and Shoulder Arthroplasty: 2023 Annual Report, Australian Orthopaedic Association National Joint Replacement Registry , Adelaide, South Australia : AOA . 2023 . https://aoanjrr.sahmri.com/documents/10180/1579982/AOA_NJRR_AR23.pdf/c3bcc83b-5590-e034-4ad8-802e4ad8bf5b?t=1695887126627 ( date last accessed 26 April 2024 ). Google Scholar
55. Vakharia RM , Sodhi N , Cohen-Levy WB , Vakharia AM , Mont MA , Roche MW . Comparison of patient demographics and utilization trends of robotic-assisted and non-robotic-assisted unicompartmental knee arthroplasty . J Knee Surg . 2021 ; 34 ( 6 ): 621 – 627 . Crossref PubMed Google Scholar
56. Meloni MC , Hoedemaeker RW , Violante B , Mazzola C . Soft tissue balancing in total knee arthroplasty . Joints . 2014 ; 2 ( 1 ): 37 – 40 . PubMed Crossref Google Scholar
Author contributions
A. Bensa: Conceptualization, Data curation, Formal analysis, Investigation, Validation, Visualization, Writing – original draft.
A. Sangiorgio: Data curation, Investigation, Writing – original draft.
L. Deabate: Investigation, Validation, Writing – review & editing.
A. Illuminati: Investigation, Methodology, Validation, Writing – review & editing.
B. Pompa: Data curation, Visualization, Writing – original draft.
G. Filardo: Conceptualization, Methodology, Project administration, Resources, Supervision, Validation, Writing – review & editing.
Funding statement
The authors received no financial or material support for the research, authorship, and/or publication of this article.
Data sharing
The data that support the findings for this study are available to other researchers from the corresponding author upon reasonable request.
Open access funding
The authors report that the open access funding for this manuscript was covered by Università della Svizzera italiana (USI).
© 2024 Bensa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND 4.0) licence, which permits the copying and redistribution of the work only, and provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc-nd/4.0/
