Can a robot help a surgeon to predict a good total knee arthroplasty?

Robotic Total Knee Arthroplasty Surgeon Marketing: Do Claims Align With the Literature?

Background

Robotic total knee arthroplasty (R-TKA) utilization and marketing continue to rise. We examined the marketing on surgeon websites regarding R-TKA benefits and sought to determine if the claims were supported by existing literature.

Methods

A Google search identified 10 physician websites from each of the 5 largest U.S. markets by population with the term "robotic total knee arthroplasty city, state." Claims on websites about R-TKA were categorized. Literature from 2012-2022 was reviewed for data "for" or "against" each claim. Level of evidence for each publication was collected.

Results

Fifty websites were captured that included 59 surgeons. A specific R-TKA platform was mentioned on 68% of websites. Website claims about robotics were placed into 8 major categories. Literature review supported the claims of more precise/accurate, reduced injury to tissue, and less pain with more literature "for" than "against" the claims.

Conclusions

Claims made on physician websites regarding the benefits of R-TKA are variable and not definitively supported by existing literature. Most available data can be categorized into levels of evidence III, IV, and V. There is a paucity of level I evidence to support the various marketing statements. Physicians should be cognizant of both the claims made on their websites and the literature that could be used to support or refute those specific claims.

Robotic assisted Total Knee Arthroplasty (TKA) is not associated with increased patient satisfaction: a systematic review and meta-analysis

PURPOSE

Total knee arthroplasty (TKA) is a common orthopedic surgery, yet postoperative dissatisfaction persists in around 20% of cases. Robotic total knee arthroplasty (rTKA) promises enhanced precision, but its impact on patient satisfaction compared to conventional TKA remains controversial (cTKA). This systematic review aims to evaluate patient satisfaction post-rTKA and compare outcomes with cTKA.

METHODS

Papers from the following databases were identified and reviewed: PubMed, Scopus, Web of Science, and the Cochrane Online Library, using keywords like "Knee replacement," "Total knee arthroplasty," "Robotic," and "Patient satisfaction." Extracted data included patient satisfaction measures, Knee Society Score, Oxford Knee Score, Forgotten Joint Score, SF-36, HSS, and KOOS. Statistical analysis, including odds ratio and 95% CI was performed using R software. Heterogeneity was assessed using Cochrane's Q test.

RESULTS

The systematic review included 17 articles, involving 1148 patients (571 in the rTKA group and 577 in the cTKA group) assessing patient satisfaction following rTKA. An analysis of proportions reveals rTKA satisfaction rate was 95%, while for cTKA, it was 91%. A meta-analysis comparing rTKA and cTKA found no statistically significant difference in patient satisfaction. Additionally, various patient-reported outcome measures (PROMs) were examined, showing mixed results across different studies and follow-up periods.

CONCLUSIONS

The results of this study found no difference in patient satisfaction outcomes in the short to mid-term for rTKA compared to conventional methods. This study does not assert superiority for the robotic approach, highlighting the need for careful consideration of various factors influencing outcomes in knee arthroplasty.

Ligament Tension and Balance before and after Robotic-Assisted Total Knee Arthroplasty - Dynamic Changes with Increasing Applied Force

The optimal force applied during ligament balancing in total knee arthroplasty (TKA) is not well understood. We quantified the effect of increasing distraction force on medial and lateral gaps throughout the range of knee motion, both prior to and after femoral resections in tibial-first gap-balancing TKA. Twenty-five consecutive knees in 21 patients underwent robotic-assisted TKA. The posterior cruciate ligament was resected, and the tibia was cut neutral to the mechanical axis. A digital ligament tensioning tool recorded gaps and applied equal mediolateral loads of 70 N (baseline), 90 N, and 110 N from 90 degrees to full extension. A gap-balancing algorithm planned the femoral implant position to achieve a balanced knee throughout flexion. After femoral resections, gap measurements were repeated under the same conditions. Paired t-tests identified gap differences between load levels, medial/lateral compartments, and flexion angle. Gaps increased from 0 to 20 degrees in flexion, then remain consistent through 90 degrees of flexion. Baseline medial gap was significantly smaller than lateral gap throughout flexion (p <0.05). Increasing load had a larger effect on the lateral versus medial gaps (p <0.05) and on flexion versus extension gaps. Increasing distraction force resulted in non-linear and asymmetric gap changes mediolaterally and from flexion to extension. Digital ligament tensioning devices can give better understanding of the relationship between joint distraction, ligament tension, and knee stiffness throughout the range of flexion. This can aid in informed surgical decision making and optimal soft tissue tensioning during TKA.

Robotic-arm assisted total knee arthroplasty is associated with comparable functional outcomes but improved forgotten joint scores compared with conventional manual total knee arthroplasty at five-year follow-up

PURPOSE

This study reports the five-year functional outcomes from a prospective cohort study comparing robotic-arm assisted total knee arthroplasty (RO TKA) versus conventional manual total knee arthroplasty (CO TKA).

METHODS

This prospective single-surgeon study included 120 patients with symptomatic end-stage knee arthritis undergoing primary TKA. This included 60 consecutive patients undergoing CO TKA followed by 60 consecutive patients undergoing RO TKA using a semi-automated robotic device. Study patients were reviewed at one, two, and five years after surgery and the following outcomes recorded: The University of California at Los Angeles activity-level (UCLA), Knee Society Score (KSS), Oxford Knee Score (OKS) Forgotten Joint Score (FJS), and any complications.

RESULTS

There were no statistical differences between RO TKA and CO TKA in the median UCLA score (p = N.S), median KSS (p = N.S), and median OKS (p = N.S) at five-year follow-up. RO-TKA was associated with statistically significant improvements in the FJS at one (p = 0.001), two (p = 0.003), and five (p = 0.025) years of follow-up compared with CO TKA. There was no statistical difference in the incidence of knee stiffness requiring manipulation under anesthesia between the two treatment groups (p = N.S).

CONCLUSION

Patients in both treatment groups had excellent functional outcomes with comparable patient reported outcomes at five-year follow-up. RO TKA was associated with statistically significant improvements in the FJS compared with CO TKA, but these differences did not reach the minimal clinically important difference at any follow-up interval. There was no overall difference in complications between the two treatment groups at five-year follow-up.

LEVEL OF EVIDENCE

II (Prospective cohort study).

Prediction of early functional outcomes in patients after robotic-assisted total knee arthroplasty: a nomogram prediction model

BACKGROUND

Robotic-assisted total knee arthroplasty (RA-TKA) is becoming more and more popular as a treatment option for advanced knee diseases due to its potential to reduce operator-induced errors. However, the development of accurate prediction models for postoperative outcomes is challenging. This study aimed to develop a nomogram model to predict the likelihood of achieving a beneficial functional outcome. The beneficial outcome is defined as a postoperative improvement of the functional Knee Society Score (fKSS) of more than 10 points, 3 months after RA-TKA by early collection and analysis of possible predictors.

METHODS

This is a retrospective study on 171 patients who underwent unilateral RA-TKA at our hospital. The collected data included demographic information, preoperative imaging data, surgical data, and preoperative and postoperative scale scores. Participants were randomly divided into a training set ( N =120) and a test set ( N =51). Univariate and multivariate logistic regression analyses were employed to screen for relevant factors. Variance inflation factor was used to investigate for variable collinearity. The accuracy and stability of the models were evaluated using calibration curves with the Hosmer-Lemeshow goodness-of-fit test, consistency index and receiver operating characteristic curves.

RESULTS

Predictors of the nomogram included preoperative hip-knee-ankle angle deviation, preoperative 10-cm Visual Analogue Scale score, preoperative fKSS score and preoperative range of motion. Collinearity analysis with demonstrated no collinearity among the variables. The consistency index values for the training and test sets were 0.908 and 0.902, respectively. Finally, the area under the receiver operating characteristic curve was 0.908 (95% CI 0.846-0.971) in the training set and 0.902 (95% CI 0.806-0.998) in the test set.

CONCLUSION

A nomogram model was designed hereby aiming to predict the functional outcome 3 months after RA-TKA in patients. Rigorous validation showed that the model is robust and reliable. The identified key predictors include preoperative hip-knee-ankle angle deviation, preoperative visual analogue scale score, preoperative fKSS score, and preoperative range of motion. These findings have major implications for improving therapeutic interventions and informing clinical decision-making in patients undergoing RA-TKA.

Learning curve and short-term clinical outcomes of a new seven-axis robot-assisted total knee arthroplasty system: a propensity score-matched retrospective cohort study

OBJECTIVE

The purpose of the present study was to determine the learning curve for a novel seven-axis robot-assisted (RA) total knee arthroplasty (TKA) system and to explore whether it could provide superior short-term clinical and radiological outcomes compared with conventional surgery.

METHODS

In the present retrospective study, 90 patients who underwent RA-TKA were included in robot-assisted system (RAS) group and 90 patients who underwent conventional TKA were included in the conventional group. The duration of surgery and robot-related complications were recorded to evaluate the learning curve through cumulative sum and risk-adjusted cumulative sum methods. The demographic data, preoperative clinical data, preoperative imaging data, duration of surgery, alignment of the prosthesis, lower limb force line alignment, Knee Society score, 10-cm visual analog scale pain score and range of motion were compared between the RAS and conventional groups. In addition, the proficiency group was compared with the conventional group using propensity score matching.

RESULTS

RA-TKA was associated with a learning curve of 20 cases for the duration of surgery. There was no significant difference in indicators representing the accuracy of the prosthetic installation between the learning and proficiency phases in RA-TKA group patients. A total of 49 patients in the proficiency group were matched with 49 patients from the conventional group. The number of postoperative hip-knee-ankle (HKA) angle, component femoral coronal angle (CFCA), component tibial coronal angle (CTCA), and sagittal tibial component angle (STCA) outliers in the proficiency phase was lower than that in the conventional group, while deviations of the HKA angle, CFCA, CTCA, and STCA in the proficiency phase were significantly lower than those in the conventional group (P < 0.05).

CONCLUSION

In summary, from the learning curve data, 20 cases are required for a surgeon using a novel seven-axis RA-TKA system to enter the proficiency phase. In the proficiency group, compared with the conventional group using propensity score matching, the RAS was found to be superior to the conventional group in prosthesis and lower limb alignment.

Moving beyond radiographic alignment: applying the Wald Principles in the adoption of robotic total knee arthroplasty

The use of robotics in total knee arthroplasty (TKA) is growing at an exponential rate. Despite the improved accuracy and reproducibility of robotic-assisted TKA, consistent clinical benefits have yet to be determined, with most studies showing comparable functional outcomes and survivorship between robotic and conventional techniques. Given the success and durability of conventional TKA, measurable improvements in these outcomes with robotic assistance may be difficult to prove. Efforts to optimize component alignment within two degrees of neutral may be an attainable but misguided goal. Applying the "Wald Principles" of rationalization, it is possible that robotic technology may still prove beneficial, even when equivalent clinical outcomes as conventional methods, if we look beyond the obvious surrogate measures of success. Robotic systems may help to reduce inventory, streamline surgical trays, enhance workflows and surgical efficiency, optimize soft tissue balancing, improve surgeon ergonomics, and integrate artificial intelligence and machine learning algorithms into a broader digital ecosystem. This article explores these less obvious alternative benefits of robotic surgery in the field of TKA.

The evolution of robotic systems for total knee arthroplasty, each system must be assessed for its own value: a systematic review of clinical evidence and meta-analysis

INTRODUCTION

Robotic systems have been introduced to improve the precision of total knee arthroplasty. However, different robotic systems are available, each with unique features used to plan and execute the surgery. As such, due to this diversity, the clinical evaluation of each robotic platform should be separated.

METHODS

An extensive literature search of PubMed, Medline, Embase and Web of Science was conducted with subsequent meta-analysis. Randomised controlled trials, comparative studies, and cohort studies were included regarding robot-assisted total knee arthroplasty. Evaluated outcomes included clinical results, surgical precision, ligament balance, surgical time, learning curve, complications and revision rates. These were split up based on the robot-specific brand: ROBODOC (T-SOLUTION ONE), OMNIBOT, MAKO, NAVIO (CORI) and ROSA.

RESULTS

With a follow-up of more than 10 years, no improved clinical outcomes have been noted with the ROBODOC system compared to the conventional technique. If available, other platforms only present short-term clinical outcomes. Radiological outcomes are published for most robotic setups, demonstrating improved surgical precision compared to the conventional technique. Gap balance assessment is performed differently between all systems, leading to heterogeneous outcomes regarding its relationship on clinical outcomes. There is a similar learning curve based on operative time for all robotic platforms. In most studies, robot assistance requires longer operative time compared to the conventional technique. Complications and revision rates are published for ROBODOC and MAKO, without clear differences to conventional total knee arthroplasty.

CONCLUSION

The main finding of this systematic review is that the current evidence regarding each robotic system is diverse in quantity and quality. Each system has its own specificities and must be assessed for its own value. Regarding scientific literature, the generic term of robotic should be banned from the general conclusion.

LEVEL OF EVIDENCE

Systematic review level IV.

Revision Total Knee Arthroplasty Using Robotic Arm Technology

Total knee arthroplasty (TKA) is a highly successful operation for the treatment of end-stage osteoarthritis of the knee. Increasing use of computer-assisted and robotic-assisted total joint arthroplasty has been shown to improve component position, with short-term studies demonstrating improved survivability in unicompartmental knee arthroplasty. Robotic-assisted technology has been shown to be helpful in revising unicompartmental knee arthroplasty to TKA, as well as hip fusion to total hip arthroplasty, but few have described revision of a primary TKA. This case report describes the use of robotic-assisted technology in revision TKA. Robotic assistance during revision TKA may improve component alignment and increase prosthesis longevity. Future research is needed to investigate the effects on survivorship and cost.

Decoders configurations based on Unet family and feature pyramid network for COVID-19 segmentation on CT images

Coronavirus Disease 2019 (COVID-19) pandemic has been ferociously destroying global health and economics. According to World Health Organisation (WHO), until May 2021, more than one hundred million infected cases and 3.2 million deaths have been reported in over 200 countries. Unfortunately, the numbers are still on the rise. Therefore, scientists are making a significant effort in researching accurate, efficient diagnoses. Several studies advocating artificial intelligence proposed COVID diagnosis methods on lung images with high accuracy. Furthermore, some affected areas in the lung images can be detected accurately by segmentation methods. This work has considered state-of-the-art Convolutional Neural Network architectures, combined with the Unet family and Feature Pyramid Network (FPN) for COVID segmentation tasks on Computed Tomography (CT) scanner samples from the Italian Society of Medical and Interventional Radiology dataset. The experiments show that the decoder-based Unet family has reached the best (a mean Intersection Over Union (mIoU) of 0.9234, 0.9032 in dice score, and a recall of 0.9349) with a combination between SE ResNeXt and Unet++. The decoder with the Unet family obtained better COVID segmentation performance in comparison with Feature Pyramid Network. Furthermore, the proposed method outperforms recent segmentation state-of-the-art approaches such as the SegNet-based network, ADID-UNET, and A-SegNet + FTL. Therefore, it is expected to provide good segmentation visualizations of medical images.