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

Surgical factors play a critical role in predicting functional outcomes using machine learning in robotic-assisted total knee arthroplasty

PURPOSE

Predictive models help determine predictive factors necessary to improve functional outcomes after total knee arthroplasty (TKA). However, no study has assessed predictive models for functional outcomes after TKA based on the new concepts of personalised surgery and new technologies. This study aimed to develop and evaluate predictive modelling approaches to predict the achievement of minimal clinically important difference (MCID) in patient-reported outcome measures (PROMs) 1 year after TKA.

METHODS

Four hundred thirty robotic-assisted TKAs were analysed in this retrospective study. The mean age was 67.9 ± 7.9 years; the mean body mass index (BMI) was 32.0 ± 6.8 kg/m2. The following PROMs were collected preoperatively and 1-year postoperatively: knee injury and osteoarthritis outcome score for joint replacement, Western Ontario and McMaster Universities osteoarthritis index (WOMAC) Function, WOMAC Pain. Demographic data, preoperative CT scan, implant size, implant position on the robotic system and characteristics of the joint replacement procedure were selected as predictive variables. Four machine learning algorithms were trained to predict the MCID status at 1-year post-TKA for each PROM survey. 'No MCID' was chosen as the target. Models were evaluated by class discrimination (F1-score) and area under the receiver operating characteristic curve (ROC-AUC).

RESULTS

The best-performing model was ridge logistic regression for WOMAC Function (area under the curve [AUC]  = 0.80, F1 = 0.48, sensitivity = 0.79, specificity = 0.62). Variables most strongly contributing to not achieving MCID status were preoperative PROMs, high BMI and femoral resection depth (posterior and distal), supporting functional positioning principles. Conversely, variables contributing to a positive outcome (achieving MCID) were medial/lateral alignment of the tibial component, whether the procedure was an outpatient surgery and whether the patient received managed Medicare insurance.

CONCLUSION

The most predictive variables included preoperative PROMs, BMI and surgical planning. The surgical predictive variables were valgus femoral alignment and femoral rotation, reflecting the benefits of personalised surgery. Including surgical variables in predictive models for functional outcomes after TKA should guide clinical and surgical decision-making for every patient.

LEVEL OF EVIDENCE

Level III.

Robotic-assisted unicompartmental knee arthroplasty improves functional outcomes, complications, and revisions

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.

Gender does not influence outcomes and complications in medial unicompartmental knee arthroplasty

PURPOSE

The impact of gender on the outcomes of unicompartmental knee arthroplasty (UKA) remains a topic of active discussion with limited exploration thus far. The study aims to elucidate the gender effect on clinical outcomes, complications, pre- and postoperative radiological outcomes following the implantation of a medial UKA at mid-term follow-up in a large section of patients.

METHODS

This was a single-centre, retrospective cohort study encompassing patients undergoing medial UKA between 2011 and 2019. The International Knee Society (IKS) Knee and Function score, patient satisfaction, complications, revisions, pre- and postoperative radiological outcomes (coronal plane alignment, femoral and tibial component positioning, posterior tibial slope) were evaluated. Survival rate at the time of the last follow-up was also recorded.

RESULTS

Of the 366 knees that met the inclusion criteria, 10 were lost to follow-up, accounting for a 2.7% loss. Mean follow-up was 5.2 ± 2 years [2.1-11.3]. Out of the total population, 205 patients were females (57.6%, 205/356) and 151 were males (42.4%, 151/356). Men exhibited superior pre- and postoperative IKS function scores (p = 0.017). However, no significant differences were observed between women and men regarding improvements of IKS Knee and Function scores, radiographic outcomes and implant survivorship.

CONCLUSION

At a mean follow-up of 5 years, this study revealed no significant impact of gender on clinical outcomes and complications in patients undergoing medial UKA. Furthermore, no significant differences were evident in radiographic outcomes, implant positioning and knee phenotype.

LEVEL OF EVIDENCE

Level III.

Osteoarthritis year in review 2023: Biomechanics

Biomechanics plays a significant yet complex role in osteoarthritis (OA) onset and progression. Identifying alterations in biomechanical factors and their complex interactions is critical for gaining new insights into OA pathophysiology and identification of clearly defined and modifiable mechanical treatment targets. This review synthesized biomechanics studies from March 2022 to April 2023, from which three themes relating to human gait emerged: (1) new insights into the pathogenesis of OA using computational modeling and machine learning, (2) technology-enhanced biomechanical interventions for OA, and (3) out-of-lab biomechanical assessments of OA. We further highlighted future-focused areas which may continue to advance the field of biomechanics in OA, with a particular emphasis on exploiting technology to understand and treat biomechanical mechanisms of OA outside the laboratory. The breadth of studies included in this review highlights the complex role of biomechanics in OA and showcase numerous innovative and outstanding contributions to the field. Exciting cross-disciplinary efforts integrating computational modeling, mobile sensors, and machine learning methods show great promise for streamlining in vivo multi-scale biomechanics workflows and are expected to underpin future breakthroughs in the understanding and treatment of biomechanics in OA.

Cruciate-substituting and posterior-stabilised total knee arthroplasties had similar gait patterns in the short term

PURPOSE

Surgeons want to achieve native kinematics in primary total knee arthroplasty (TKA). Cruciate-substituting (CS) implants could restore the knee kinematics more efficiently than posterior-stabilised (PS) TKA. This study aimed to compare gait patterns in patients with CS or PS TKA at 6 months. The hypothesis was that CS implants would demonstrate comparable gait parameters to PS implants at 6 months.

METHODS

In this prospective case-control study, 38 primary TKA without coronal laxity were divided into 2 groups: 19 cruciate-substituting (CS) and 19 posterior-stabilised (PS) implants. The type of prosthesis was determined according to the surgical period. Exclusion criteria were TKA revision, associated procedures and inability to walk on a treadmill. Gait analysis was conducted on a treadmill 6 months postoperatively for each patient with a knee assessment device (KneeKG®). Gait characteristics included analysis in three spatial dimensions (flexion-extension, abduction-adduction, internal-external rotation, anterior-posterior translation). Clinical outcomes (Knee Society Score and Forgotten Joint Score) were compared between both groups at 6 months postoperatively.

RESULTS

At 6 months, the gait analysis did not demonstrate any significant difference between CS and PS implants. The range and the maximum anteroposterior translation were similar in both groups (9.2 ± 6.5 mm in CS group vs. 8.1 ± 3 mm in PS group (n.s.); and - 5.2 ± 5 mm in CS group vs. - 6.3 ± 5.9 mm in PS group (n.s.), respectively). The internal/external rotation, the flexion, and the varus angle were similar between CS and PS implants. The KSS Knee score was higher at 6 months in the CS group than in the PS group (92.1 ± 5.6 vs. 84.8 ± 8.9 (p < 0.01)).

CONCLUSION

Cruciate-substituting and posterior-stabilised TKA had similar gait patterns at 6 months postoperatively, despite a non-equivalent posterior stabilisation system. CS prostheses were an interesting option for primary TKA for knee kinematics restoration without requiring a femoral box.

LEVEL OF EVIDENCE

Prospective, case-control study; Level II.

Robotic Versus Conventional Unicompartmental Knee Surgery: A Comprehensive Systematic Review and Meta-Analysis

Robotic-assisted surgery is a computer-controlled technique that may improve the accuracy and outcomes of unicompartmental total knee arthroplasty (TKA), a partial knee replacement surgery. The purpose of a meta-analysis about robotic-assisted versus conventional surgery for unicompartmental TKA is to compare the effectiveness of these two methods based on the current evidence. Our meta-analysis can help inform clinical decisions and guidelines for surgeons and patients who are considering unicompartmental TKA as a treatment option. We searched four online databases for studies that compared the two methods until March 2023. We used RevMan software to combine the data from the studies. We calculated the mean difference (MD) and the 95% confidence interval (CI) for each outcome, which are statistical measures of the difference and the uncertainty between the two methods. We included 16 studies in our analysis. We found that robotic-assisted surgery had a better hip-knee-ankle angle, which is a measure of how well the knee is aligned, than conventional surgery (MD = 0.86, 95% CI = 0.16-1.56). We also found that robotic-assisted surgery had a better Oxford Knee score, which is a measure of how well the knee functions, than conventional surgery (MD = 3.03, 95% CI = 0.96-5.110). This study compared the results of conventional and robotic-assisted unicompartmental knee arthroplasty in 12 studies. We concluded that robotic-assisted surgery may have some benefits over conventional surgery in terms of alignment and function of the knee. However, we did not find any significant difference between the two methods in terms of other outcomes, such as pain, range of motion, health status, and joint awareness. Therefore, we suggest that more research is needed to confirm these results and evaluate the long-term effects and cost-effectiveness of robotic-assisted surgery.

A Systematic Review of Diagnostic Accuracy and Clinical Applications of Wearable Movement Sensors for Knee Joint Rehabilitation

In clinical practice, only a few reliable measurement instruments are available for monitoring knee joint rehabilitation. Advances to replace motion capturing with sensor data measurement have been made in the last years. Thus, a systematic review of the literature was performed, focusing on the implementation, diagnostic accuracy, and facilitators and barriers of integrating wearable sensor technology in clinical practices based on a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. For critical appraisal, the COSMIN Risk of Bias tool for reliability and measurement of error was used. PUBMED, Prospero, Cochrane database, and EMBASE were searched for eligible studies. Six studies reporting reliability aspects in using wearable sensor technology at any point after knee surgery in humans were included. All studies reported excellent results with high reliability coefficients, high limits of agreement, or a few detectable errors. They used different or partly inappropriate methods for estimating reliability or missed reporting essential information. Therefore, a moderate risk of bias must be considered. Further quality criterion studies in clinical settings are needed to synthesize the evidence for providing transparent recommendations for the clinical use of wearable movement sensors in knee joint rehabilitation.