Aims. Patient dissatisfaction following primary total knee arthroplasty (TKA) with manual jig-based instruments has been reported to be as high as 30%. Robotic-assisted total knee arthroplasty (RA-TKA) has been increasingly used in an effort to improve patient outcomes, however there is a paucity of literature examining patient satisfaction after RA-TKA. This study aims to identify the incidence of patients who were not satisfied following RA-TKA and to determine factors associated with higher levels of dissatisfaction. Methods. This was a retrospective review of 674 patients who underwent primary TKA between October 2016 and September 2020 with a minimum two-year follow-up. A five-point Likert satisfaction score was used to place patients into two groups: Group A were those who were very dissatisfied, dissatisfied, or neutral (Likert score 1 to 3) and Group B were those who were satisfied or very satisfied (Likert score 4 to 5). Patient demographic data, as well as preoperative and postoperative patient-reported outcome measures, were compared between groups. Results. Overall, 45 patients (6.7%) were in Group A and 629 (93.3%) were in Group B. Group A (vs Group B) had a higher proportion of male sex (p = 0.008), preoperative chronic opioid use (p < 0.001), preoperative psychotropic medication use (p = 0.01), prior anterior cruciate ligament (ACL) reconstruction (p < 0.001), and preoperative symptomatic lumbar spine disease (p = 0.004). Group A was also younger (p = 0.023). Multivariate analysis revealed preoperative opioid use (p = 0.012), prior ACL reconstruction (p = 0.038), male sex (p = 0.006), and preoperative psychotropic medication use (p = 0.001) as independent predictive factors of patient dissatisfaction. Conclusion. The use of RA-TKA demonstrated a high rate of patient satisfaction (629 of 674, 93.3%). Demographics for patients not satisfied following RA-TKA included: male sex, chronic opioid use, chronic psychotropic medication use, and prior ACL reconstruction. Patients in these groups should be identified preoperatively and educated on realistic expectations given their comorbid conditions. Cite this article: Bone Jt Open 2024;5(9):758–765

Aims. Implant waste during total hip arthroplasty (THA) represents a significant cost to the USA healthcare system. While studies have explored methods to improve THA cost-effectiveness, the literature comparing the proportions of implant waste by intraoperative technology used during THA is limited. The aims of this study were to: 1) examine whether the use of enabling technologies during THA results in a smaller proportion of wasted implants compared to navigation-guided and conventional manual THA; 2) determine the proportion of wasted implants by implant type; and 3) examine the effects of surgeon experience on rates of implant waste by technology used. Methods. We identified 104,420 implants either implanted or wasted during 18,329 primary THAs performed on 16,724 patients between January 2018 and June 2022 at our institution. THAs were separated by technology used: robotic-assisted (n = 4,171), imageless navigation (n = 6,887), and manual (n = 7,721). The primary outcome of interest was the rate of implant waste during primary THA. Results. Robotic-assisted THA resulted in a lower proportion (1.5%) of implant waste compared to navigation-guided THA (2.0%) and manual THA (1.9%) (all p < 0.001). Both navigated and manual THA were more likely to waste acetabular shells (odds ratio (OR) 4.5 vs 3.1) and polyethylene liners (OR 2.2 vs 2.0) compared to robotic-assisted THA after adjusting for demographic and perioperative factors, such as surgeon experience (p < 0.001). While implant waste decreased with increasing experience for procedures performed manually (p < 0.001) or with navigation (p < 0.001), waste rates for robotic-assisted THA did not differ based on surgical experience. Conclusion. Robotic-assisted THAs wasted a smaller proportion of acetabular shells and polyethylene liners than navigation-guided and manual THAs. Individual implant waste rates vary depending on the type of technology used intraoperatively. Future studies on implant waste during THA should examine reasons for non-implantation in order to better understand and develop methods for cost-saving. Cite this article: Bone Jt Open 2024;5(8):715–720

Aims. Sagittal plane imbalance (SPI), or asymmetry between extension and flexion gaps, is an important issue in total knee arthroplasty (TKA). The purpose of this study was to compare SPI between kinematic alignment (KA), mechanical alignment (MA), and functional alignment (FA) strategies. Methods. In 137 robotic-assisted TKAs, extension and flexion stressed gap laxities and bone resections were measured. The primary outcome was the proportion and magnitude of medial and lateral SPI (gap differential > 2.0 mm) for KA, MA, and FA. Secondary outcomes were the proportion of knees with severe (> 4.0 mm) SPI, and resection thicknesses for each technique, with KA as reference. Results. FA showed significantly lower rates of medial and lateral SPI (2.9% and 2.2%) compared to KA (45.3%; p < 0.001, and 25.5%; p < 0.001) and compared to MA (52.6%; p < 0.001 and 29.9%; p < 0.001). There was no difference in medial and lateral SPI between KA and MA (p = 0.228 and p = 0.417, respectively). FA showed significantly lower rates of severe medial and lateral SPI (0 and 0%) compared to KA (8.0%; p < 0.001 and 7.3%; p = 0.001) and compared to MA (10.2%; p < 0.001 and 4.4%; p = 0.013). There was no difference in severe medial and lateral SPI between KA and MA (p = 0.527 and p = 0.307, respectively). MA resulted in thinner resections than KA in medial extension (mean difference (MD) 1.4 mm, SD 1.9; p < 0.001), medial flexion (MD 1.5 mm, SD 1.8; p < 0.001), and lateral extension (MD 1.1 mm, SD 1.9; p < 0.001). FA resulted in thinner resections than KA in medial extension (MD 1.6 mm, SD 1.4; p < 0.001) and lateral extension (MD 2.0 mm, SD 1.6; p < 0.001), but in thicker medial flexion resections (MD 0.8 mm, SD 1.4; p < 0.001). Conclusion. Mechanical and kinematic alignment (measured resection techniques) result in high rates of SPI. Pre-resection angular and translational adjustments with functional alignment, with typically smaller distal than posterior femoral resection, address this issue. Cite this article: Bone Jt Open 2024;5(8):681–687

Aims. The aims of this study were: 1) to describe extended restricted kinematic alignment (E-rKA), a novel alignment strategy during robotic-assisted total knee arthroplasty (RA-TKA); 2) to compare residual medial compartment tightness following virtual surgical planning during RA-TKA using mechanical alignment (MA) and E-rKA, in the same set of osteoarthritic varus knees; 3) to assess the requirement of soft-tissue releases during RA-TKA using E-rKA; and 4) to compare the accuracy of surgical plan execution between knees managed with adjustments in component positioning alone, and those which require additional soft-tissue releases. Methods. Patients who underwent RA-TKA between January and December 2022 for primary varus osteoarthritis were included. Safe boundaries for E-rKA were defined. Residual medial compartment tightness was compared following virtual surgical planning using E-rKA and MA, in the same set of knees. Soft-tissue releases were documented. Errors in postoperative alignment in relation to planned alignment were compared between patients who did (group A) and did not (group B) require soft-tissue releases. Results. The use of E-rKA helped restore all knees within the predefined boundaries, with appropriate soft-tissue balancing. E-rKA compared with MA resulted in reduced residual medial tightness following surgical planning, in full extension (2.71 mm (SD 1.66) vs 5.16 mm (SD 3.10), respectively; p < 0.001), and 90° of flexion (2.52 mm (SD 1.63) vs 6.27 mm (SD 3.11), respectively; p < 0.001). Among the study population, 156 patients (78%) were managed with minor adjustments in component positioning alone, while 44 (22%) required additional soft-tissue releases. The mean errors in postoperative alignment were 0.53 mm and 0.26 mm among patients in group A and group B, respectively (p = 0.328). Conclusion. E-rKA is an effective and reproducible alignment strategy during RA-TKA, permitting a large proportion of patients to be managed without soft-tissue releases. The execution of minor alterations in component positioning within predefined multiplanar boundaries is a better starting point for gap management than soft-tissue releases. Cite this article: Bone Jt Open 2024;5(8):628–636

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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.

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Unicompartmental knee arthroplasty (UKA) is the preferred treatment for anterior medial knee osteoarthritis (OA) owing to the rapid postoperative recovery. However, the risk factors for UKA failure remain controversial.

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To perform an incremental cost-utility analysis and assess the impact of differential costs and case volume on the cost-effectiveness of robotic arm-assisted unicompartmental knee arthroplasty (rUKA) compared to manual (mUKA).

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction.

Cite this article: Bone Joint Res 2023;12(7):447–454.

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Computer-assisted 3D preoperative planning software has the potential to improve postoperative stability in total hip arthroplasty (THA). Commonly, preoperative protocols simulate two functional positions (standing and relaxed sitting) but do not consider other common positions that may increase postoperative impingement and possible dislocation. This study investigates the feasibility of simulating commonly encountered positions, and positions with an increased risk of impingement, to lower postoperative impingement risk in a CT-based 3D model.

Abstract. Robotic-assisted total knee arthroplasty (TKA) has proven higher accuracy, fewer alignment outliers, and improved short-term clinical outcomes when compared to conventional TKA. However, evidence of cost-effectiveness and individual superiority of one system over another is the subject of further research. Despite its growing adoption rate, published results are still limited and comparative studies are scarce. This review compares characteristics and performance of five currently available systems, focusing on the information and feedback each system provides to the surgeon, what the systems allow the surgeon to modify during the operation, and how each system then aids execution of the surgical plan. Cite this article: Bone Jt Open 2023;4(1):13–18

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The aim of this study was to compare a bicruciate-retaining (BCR) total knee arthroplasty (TKA) with a posterior cruciate-retaining (CR) TKA design in terms of kinematics, measured using fluoroscopy and stability as micromotion using radiostereometric analysis (RSA).

Aims. The aim of this study was to report patient and clinical outcomes following robotic-assisted total knee arthroplasty (RA-TKA) at multiple institutions with a minimum two-year follow-up. Methods. This was a multicentre registry study from October 2016 to June 2021 that included 861 primary RA-TKA patients who completed at least one pre- and postoperative patient-reported outcome measure (PROM) questionnaire, including Forgotten Joint Score (FJS), Knee Injury and Osteoarthritis Outcomes Score for Joint Replacement (KOOS JR), and pain out of 100 points. The mean age was 67 years (35 to 86), 452 were male (53%), mean BMI was 31.5 kg/m. 2. (19 to 58), and 553 (64%) cemented and 308 (36%) cementless implants. Results. There were significant improvements in PROMs over time between preoperative, one- to two-year, and > two-year follow-up, with a mean FJS of 17.5 (SD 18.2), 70.2 (SD 27.8), and 76.7 (SD 25.8; p < 0.001); mean KOOS JR of 51.6 (SD 11.5), 85.1 (SD 13.8), and 87.9 (SD 13.0; p < 0.001); and mean pain scores of 65.7 (SD 20.4), 13.0 (SD 19.1), and 11.3 (SD 19.9; p < 0.001), respectively. There were eight superficial infections (0.9%) and four revisions (0.5%). Conclusion. RA-TKA demonstrated consistent clinical results across multiple institutions with excellent PROMs that continued to improve over time. With the ability to achieve target alignment in the coronal, axial, and sagittal planes and provide intraoperative real-time data to obtain balanced gaps, RA-TKA demonstrated excellent clinical outcomes and PROMs in this patient population. Cite this article: Bone Jt Open 2022;3(7):589–595

Aims. No predictive model has been published to forecast operating time for total knee arthroplasty (TKA). The aims of this study were to design and validate a predictive model to estimate operating time for robotic-assisted TKA based on demographic data, and evaluate the added predictive power of CT scan-based predictors and their impact on the accuracy of the predictive model. Methods. A retrospective study was conducted on 1,061 TKAs performed from January 2016 to December 2019 with an image-based robotic-assisted system. Demographic data included age, sex, height, and weight. The femoral and tibial mechanical axis and the osteophyte volume were calculated from CT scans. These inputs were used to develop a predictive model aimed to predict operating time based on demographic data only, and demographic and 3D patient anatomy data. Results. The key factors for predicting operating time were the surgeon and patient weight, followed by 12 anatomical parameters derived from CT scans. The predictive model based only on demographic data showed that 90% of predictions were within 15 minutes of actual operating time, with 73% within ten minutes. The predictive model including demographic data and CT scans showed that 94% of predictions were within 15 minutes of actual operating time and 88% within ten minutes. Conclusion. The primary factors for predicting robotic-assisted TKA operating time were surgeon, patient weight, and osteophyte volume. This study demonstrates that incorporating 3D patient-specific data can improve operating time predictions models, which may lead to improved operating room planning and efficiency. Cite this article: Bone Jt Open 2022;3(5):383–389

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Intraoperative pressure sensors allow surgeons to quantify soft-tissue balance during total knee arthroplasty (TKA). The aim of this study was to determine whether using sensors to achieve soft-tissue balance was more effective than manual balancing in improving outcomes in TKA.

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This systematic review aims to compare the precision of component positioning, patient-reported outcome measures (PROMs), complications, survivorship, cost-effectiveness, and learning curves of MAKO robotic arm-assisted unicompartmental knee arthroplasty (RAUKA) with manual medial unicompartmental knee arthroplasty (mUKA).

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The Forgotten Joint Score-12 (FJS-12) is a validated patient-reported outcome measure (PROM) tool designed to assess artificial prosthesis awareness during daily activities following total hip arthroplasty (THA). The patient-acceptable symptom state (PASS) is the minimum cut-off value that corresponds to a patient’s satisfactory state-of-health. Despite the validity and reliability of the FJS-12 having been previously demonstrated, the PASS has yet to be clearly defined. This study aims to define the PASS of the FJS-12 following primary THA.

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It is unknown whether gap laxities measured in robotic arm-assisted total knee arthroplasty (TKA) correlate to load sensor measurements. The aim of this study was to determine whether symmetry of the maximum medial and lateral gaps in extension and flexion was predictive of knee balance in extension and flexion respectively using different maximum thresholds of intercompartmental load difference (ICLD) to define balance.

Aims. This study aimed to evaluate the accuracy of implant placement with robotic-arm assisted total hip arthroplasty (THA) in patients with developmental dysplasia of the hip (DDH). Methods. The study analyzed a consecutive series of 69 patients who underwent robotic-arm assisted THA between September 2018 and December 2019. Of these, 30 patients had DDH and were classified according to the Crowe type. Acetabular component alignment and 3D positions were measured using pre- and postoperative CT data. The absolute differences of cup alignment and 3D position were compared between DDH and non-DDH patients. Moreover, these differences were analyzed in relation to the severity of DDH. The discrepancy of leg length and combined offset compared with contralateral hip were measured. Results. The mean values of absolute differences (postoperative CT-preoperative plan) were 1.7° (standard deviation (SD) 2.0) (inclination) and 2.5° (SD 2.1°) (anteversion) in DDH patients, and no significant differences were found between non-DDH and DDH patients. The mean absolute differences for 3D cup position were 1.1 mm (SD 1.0) (coronal plane) and 1.2 mm (SD 2.1) (axial plane) in DDH patients, and no significant differences were found between two groups. No significant difference was found either in cup alignment between postoperative CT and navigation record after cup screws or in the severity of DDH. Excellent restoration of leg length and combined offset were achieved in both groups. Conclusion. We demonstrated that robotic-assisted THA may achieve precise cup positioning in DDH patients, and may be useful in those with severe DDH. Cite this article: Bone Joint Res 2021;10(10):629–638

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The aim of this study was to compare the clinical outcomes of robotic arm-assisted bi-unicompartmental knee arthroplasty (bi-UKA) with conventional mechanically aligned total knee arthroplasty (TKA) during the first six weeks and at one year postoperatively.

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To explore the clinical relevance of joint space width (JSW) narrowing on standardized-flexion (SF) radiographs in the assessment of cartilage degeneration in specific subregions seen on MRI sequences in knee osteoarthritis (OA) with neutral, valgus, and varus alignments, and potential planning of partial knee arthroplasty.