Introduction of ROSA robotic-arm system for total knee arthroplasty is associated with a minimal learning curve for operative time

Improved Efficiency and Intraoperative Planning With 1 Robot-Assisted Total Knee Arthroplasty System

Background

Robotic-assisted total knee arthroplasty (rTKA) has garnered significant interest for its potential to enhance surgical precision and accuracy. However, the adoption of such systems poses concerns, including longer operative times and learning curves, potentially reducing efficiency. This study aimed to evaluate the learning curve associated with the Robotic Surgical Assistant (ROSA) system for rTKA.

Methods

This retrospective review analyzed the first 75 ROSA rTKA procedures performed by each of 2 fellowship-trained arthroplasty surgeons (150 total procedures) at a high-volume institution. Time stamps within the robotic software were recorded for each case, along with tourniquet time. Statistical analyses included descriptive statistics, t-tests, and multilevel regression.

Results

Comparison of each surgeon's first 20 and last 20 cases revealed significant decreases in tourniquet time (61.4-56.7 minutes; P = .0417) and planning time (13.49-6.68 minutes; P = .0078). Landmark femur and tibia times remained stable (P = .6542 and P = .9440). Knee state evaluation time showed a trend of reduction from 9.22 to 7.33 minutes (P = .1335), and resection time from 13.66 to 12.92 minutes (P = .4372). Regression analysis indicated significant reductions in tourniquet time (β = -0.11; P = .0089) and planning time (β = -0.08; P = .0064).

Conclusions

This study demonstrates that execution of ROSA rTKA becomes more efficient over the first 75 cases. The greatest improvement with experience is the time spent on the planning panel, the cognitive portion of the procedure. These data provide surgeons with the confidence that the technical portions of the case are quick to learn and guide industry to focus on teaching effective adjustments on the planning panel.

Survivorship in robotic total knee arthroplasty compared with conventional total knee arthroplasty: A systematic review and meta-analysis

BACKGROUND

Total knee arthroplasty (TKA) is the gold standard surgical management for end-stage knee osteoarthritis (OA). Robotic TKA (rTKA) was developed to improve bone preparation accuracy and increase reproducibility. In many settings internationally, rTKA systems have significantly higher costs for patients, and survivorship outcomes are unclear. There are several prior meta-analyses, but these focused on clinical and radiologic outcomes, and to our knowledge, none have evaluated survival. Differences in survival between semi-active or active robotic systems are also not well investigated.

STUDY DESIGN

Meta-analysis.

METHODS

A random-effects meta-analysis was conducted on comparative studies between robotic-assisted TKAs and conventional TKAs (cTKAs) in patients undergoing TKA for primary knee OA. We searched MEDLINE, Embase, Cochrane Library, and SCOPUS from inception to 19 December 2024. Outcomes assessed were the implant survival in robotic-assisted TKA compared to conventional methods in standard primary knee OA cases, with subgrouping between active and semi-active systems performed. Secondary outcomes included associated complications, post-operative pain scores, and functional outcomes.

RESULTS

A total of 20 comparative studies were included in the meta-analysis. Among them, 2,804 patients underwent cTKA, while 2,599 underwent rTKA. At two years, the pooled survivorship rate was 97.9% (95% CI: 96-99) in the conventional group and 98.3% (95% CI: 96.2-99.2) in the robotic group. There were no significant differences between the groups (P = 0.7). There were no significant differences between the robotic (semi-active) group and the conventional group (P = 0.5) on further unpaired T-Testing. Between 2 and 5 years, pooled survivorship rates in the conventional group were 96.8% (95% CI: 90.3-99) and 97.1% (95% CI: 91.3-99) in the robotic group. There were no significant differences between groups (P = 0.9). At ten years postoperatively, pooled survivorship rates in the conventional group were 96.9% (95% CI: 95-98) and 97.8% (95% CI: 96.7-98.5) in the robotic group. There were no significant differences between the groups (P = 0.3).

CONCLUSION

Conventional TKA is non-inferior to rTKA at short and long-term follow-up with regard to implant survival, complications, and postoperative pain scores, while rTKA shows subtle improvements in functional outcome measures.

TRIAL REGISTRATION

CRD42024540997.

Operative Time Learning Curve for an Image-Free Robotic Arm Assisted Total Knee Arthroplasty: A Cumulative Sum Analysis

Background

Robotic arm assisted total knee arthroplasty (RA-TKA) aims to improve accuracy in bone resection, implant positioning, and joint alignment compared to manual TKA (M-TKA). However, the learning curve of RA-TKA can disrupt operating room efficiency, increase complications, and raise costs. This study examines the operative time learning curve of RA-TKA using a single robotic system.

Methods

The study analyzed the first 80 RA-TKA and the last 80 M-TKA cases performed by a single surgeon using the VELYS robotic system after transitioning from M-TKA. Cases were subdivided into groups of 20 and compared to M-TKA cases. A cumulative summation analysis identified the learning curve phases.

Results

Three phases were identified: Phase 1 (initial learning, cases 1-9), Phase 2 (increased competence, plateau from cases 10-52), and Phase 3 (post-learning, optimized performance from cases 53-80). Mean surgical time for RA-TKA was 42.4 ± 8.7 minutes, compared to 35.3 ± 7.0 minutes for M-TKA (P < .001). Early RA-TKA cases (1-20) had significantly longer times than late RA-TKA cases (61-80) and M-TKA cases (P < .05). Late RA-TKA times were comparable to M-TKA (P = .06).

Conclusions

RA-TKA is an enabling surgical tool that can be integrated efficiently into a surgical workflow with a rapid learning curve of 9 cases.

Rapid reduction in surgical time and high level of accuracy in alignment and femoral component size prediction in robotic-assisted total knee arthroplasty with ROSA Knee System

Purpose

Robotic-assisted total knee arthroplasty (RA-TKA) has gained popularity for its potential ability to improve surgical precision and patient outcomes, despite concerns about its long learning curve and increased operative times. The aim of this study is to evaluate the learning curve of the ROSA® Knee System, the relationship between each phase of the learning curve and the accuracy of the robotic system in femoral component size and knee alignment prediction.

Methods

A single surgeon retrospective analysis of total operative time (TOT) and total robotic time was conducted. The first 60 cases of RA-TKA performed between July 2023 and March 2024 were included. Six (10%) patients were excluded due to incomplete surgical reports. A cumulative sum analysis was used to identify the learning and proficiency phases of the surgeon's learning curve. Moreover, femoral component size prediction accuracy and the difference between planned and achieved knee alignment were analyzed.

Results

The projected learning curve showed a significant reduction in TOT after 10 cases, with mean time decreasing from 62.6 ± 7.92 min in the learning phase to 49.9 ± 8.10 min in the proficiency phase (p = 0.0008). The robotic procedure accounted for 48% and 42% of the TOT in the learning and proficiency phases, respectively. Prediction in femoral component size was accurate in 92.6% of cases. The difference between planned and achieved knee alignment was not statistically significant (1.1° ± 0.9°).

Conclusions

The ROSA® Knee System allows a rapid learning curve in RA-TKA, with a significant reduction in operative time after the first 10 cases. An experienced orthopaedic surgeon specialized in knee arthroplasty can quickly reach a proficiency phase, maintaining high accuracy in alignment and femoral component sizing. These findings suggest that the ROSA® system is an effective and reliable tool for CR RA-TKA, offering precise and reproducible outcomes.

Level of Evidence

IV.

High in-vivo accuracy of a novel robotic-arm-assisted system for total knee arthroplasty

PURPOSE

Robotic-assisted total knee arthroplasty (TKA) has been shown to improve the accuracy and precision of bony resections and implant position. However, the in vivo accuracy of the full surgical workflow has not been widely reported. The primary objective of this study is to determine the accuracy and precision of a robotic-arm-assisted system throughout the intraoperative workflow.

METHODS

This was a retrospective cohort study of adult patients who underwent primary TKA with various workflows and alignment targets by three arthroplasty-trained surgeons with previous experience using the ROSA® Knee System (Zimmer Biomet) over a 3-month follow-up period. Accuracy and precision were determined by measuring the difference between various workflow time points, including the final preoperative plan (PP), robot-validated (RV) resection angle and postoperative radiographs (PR). The absolute mean difference between the measurements determined accuracy, and the standard deviation represented precision. The lateral distal femoral angle, medial proximal tibial angle, femoral flexion angle and tibial slope were measured on postoperative coronal long-leg radiographs and true short-leg lateral radiographs.

RESULTS

A total of 77 patients were included in the final analyses. The accuracy for the coronal femoral angle was 1.62 ± 1.11°, 0.75 ± 0.79° and 1.96 ± 1.29° for the differences between PP and PR, PP and RV and RV and PR. The tibial coronal accuracy was 1.44 ± 1.03°, 0.81 ± 0.67° and 1.57 ± 1.14° for PP/PR, PP/RV and RV/PR, respectively. Femoral flexion accuracy was 1.39 ± 1.05°, 0.83 ± 0.59° and 1.81 ± 1.21° for PP/PR, PP/RV and RV/PR, respectively. Tibial slope accuracy was 0.99 ± 0.72°, 1.19 ± 0.87° and 1.63 ± 1.11°, respectively. The proportion of patients within 3° was 93.2%, 95.3%, 97.3% and 94.6% for the distal femur, proximal tibia, femoral flexion and tibial slope angles when the final intraoperative plan was compared to PRs. No patients had a postoperative complication at the final follow-up.

CONCLUSIONS

The ROSA Knee System has acceptable accuracy and precision of coronal and sagittal plane resections with few outliers at various steps throughout the platform's entire workflow in vivo.

LEVEL OF EVIDENCE

Level III.

Comparable results in total knee arthroplasty using the ROSA knee system versus the conventional technique: A retrospective propensity-matched cohort study

PURPOSE

Robotic-assisted total knee arthroplasty (RA-TKA) is an increasingly popular alternative that may increase the accuracy of conventional TKA techniques. This study aims to evaluate RA-TKA accuracy and compare its radiographic and clinical outcomes to conventional TKA (cTKA).

METHODS

A retrospective examination of patients with bi- or tricompartmental knee osteoarthritis who underwent RA-TKA (RObotic Surgical Assistant system) or cTKA and were prospectively documented in the TKA registry. Accuracy was assessed using standardized radiographic implant position evaluations, namely femoral and tibial coronal angles and femoral and tibial sagittal angles. Baseline demographics, surgery details and 6- and 12-month post-TKA patient-reported outcomes (PROMs; e.g., Oxford Knee Score [OKS] and Core Outcome Measures Index) were compared between RA-TKA and propensity score-matched cTKA patients.

RESULTS

Overall correlation between preset and 6-week postoperative angle measurements for RA-TKA was low with significant differences noted only for mean tibial sagittal angles (84.6° [RA-TKA] vs. 82.3° [cTKA]) (p < 0.001). The study groups were demographically similar, although RA-TKA patients had slightly longer operative times and higher blood loss but shorter inpatient stays. There were sustainable improvements in all PROMs already at 6 months, yet RA-TKA patients had significantly higher OKS values over their conventional counterparts at this time point.

CONCLUSION

Radiological and clinical outcomes were comparable between RA-TKA and cTKA. The robotic-assisted system demonstrated higher accuracy in the coronal than sagittal plane and RA-TKA patients achieved better short-term outcomes for pain and disability. While both methods are similar in the hands of a skilled surgeon, long-term studies are necessary to establish clear method superiority.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Accuracy and Outcomes of a Novel Cut-Block Positioning Robotic-Arm Assisted System for Total Knee Arthroplasty: A Systematic Review and Meta-Analysis

Background

The primary objective of this study was to determine the accuracy and precision of component positioning of the ROSA Robotic System for total knee arthroplasty (TKA).

Methods

A Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic review was conducted using 4 electronic databases (MEDLINE, EMBASE, Pubmed, and Cochrane Library) to identify all clinical and radiological studies reporting information about the use and results of the ROSA system. The criteria for inclusion were published research articles evaluating the accuracy of component positioning, learning curve, component alignment, complications, and functional outcomes in adults who underwent robotic-assisted TKA. The National Institutes of Health Quality Assessment Tool was used to evaluate the quality of all the included studies.

Results

A total of 26 studies were assessed for eligibility, and 17 met the inclusion criteria. Nine studies reported on the accuracy and precision of component positioning. The ROSA platform for TKA had a cutting error of less than 0.6° for all coronal and sagittal parameters. Pooled analysis demonstrated accuracy within 0.61-1.87° and precision within 0.97-1.34° when the final intraoperative plan was compared to postoperative radiographs with fewer outliers. Four studies reported improved functional scores with ROSA-assisted TKA than conventional TKA within 1 year of surgery. There was no difference in overall complication rates when compared to conventional TKA.

Conclusions

The ROSA system is both highly accurate and precise, with fewer outliers when analyzed at various time points, including postoperative standing radiographs. Future studies with robust methodology and longer follow-up are required to demonstrate whether these findings have any clinical benefits in the long term.

Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion

Deep learning (DL) in orthopaedics has gained significant attention in recent years. Previous studies have shown that DL can be applied to a wide variety of orthopaedic tasks, including fracture detection, bone tumour diagnosis, implant recognition, and evaluation of osteoarthritis severity. The utilisation of DL is expected to increase, owing to its ability to present accurate diagnoses more efficiently than traditional methods in many scenarios. This reduces the time and cost of diagnosis for patients and orthopaedic surgeons. To our knowledge, no exclusive study has comprehensively reviewed all aspects of DL currently used in orthopaedic practice. This review addresses this knowledge gap using articles from Science Direct, Scopus, IEEE Xplore, and Web of Science between 2017 and 2023. The authors begin with the motivation for using DL in orthopaedics, including its ability to enhance diagnosis and treatment planning. The review then covers various applications of DL in orthopaedics, including fracture detection, detection of supraspinatus tears using MRI, osteoarthritis, prediction of types of arthroplasty implants, bone age assessment, and detection of joint-specific soft tissue disease. We also examine the challenges for implementing DL in orthopaedics, including the scarcity of data to train DL and the lack of interpretability, as well as possible solutions to these common pitfalls. Our work highlights the requirements to achieve trustworthiness in the outcomes generated by DL, including the need for accuracy, explainability, and fairness in the DL models. We pay particular attention to fusion techniques as one of the ways to increase trustworthiness, which have also been used to address the common multimodality in orthopaedics. Finally, we have reviewed the approval requirements set forth by the US Food and Drug Administration to enable the use of DL applications. As such, we aim to have this review function as a guide for researchers to develop a reliable DL application for orthopaedic tasks from scratch for use in the market.

A novel robotic surgical assistant for total knee arthroplasty has a learning curve ranging from 6 to 14 cases and exhibits high accuracy in tibial bone cuts

BACKGROUND

The adoption of robot-assisted total knee arthroplasty (TKA) aims to enhance the precision of implant positioning and limb alignment. Despite its benefits, the adoption of such technology is often accompanied by an initial learning curve, which may result in increased operative times. This study sought to determine the learning curve for the ROSA (Robotic Surgical Assistant) Knee System (Zimmer Biomet) in performing TKA and to evaluate the accuracy of the system in executing bone cuts and angles as planned. The hypothesis of this study was that cumulative experience with this robotic system would lead to reduced operative times. Additionally, the ROSA system demonstrated reliability in terms of the accuracy and reproducibility of bone cuts.

METHODS

In this retrospective observational study, we examined 110 medical records from 95 patients who underwent ROSA-assisted TKA performed by three surgeons. We employed the cumulative summation methodology to assess the learning curves related to operative time. Furthermore, we evaluated the accuracy of the ROSA Knee System in performing TKA by comparing planned versus validated values for femoral and tibial bone cuts and angles.

RESULTS

The learning curve for the ROSA Knee System spanned 14, 14, and 6 cases for the respective surgeons, with operative times decreasing by 22 min upon reaching proficiency (70.8 vs. 48.9 min; p < 0.001). Significant discrepancies were observed between the average planned and validated cuts and angles for femoral bone cuts (0.4 degree ± 2.4 for femoral flexion, 0.1 degree ± 0.6 for femoral coronal alignment, 0.3 mm ± 1.2 for distal medial femoral resection, 1.4 mm ± 8.8 for distal lateral femoral resection) and hip-knee-ankle axis alignment (0.3 degree ± 1.9 )(p < 0.05) but not for tibial bone cuts. Differences between planned and validated measurements during the learning and proficiency phases were nonsignificant across all parameters, except for the femoral flexion angle (0.42 degree ± 0.8 vs. 0.44 degree ± 2.7) (p = 0.49).

CONCLUSION

The ROSA Knee System can be integrated into surgical workflows after a modest learning curve of 6 to 14 cases. The system demonstrated high accuracy and reproducibility, particularly for tibial bone cuts. Acknowledging the learning curve associated with new robot-assisted TKA technologies is vital for their effective implementation.

Complications and Learning Curve Associated with an Imageless Burr-Based (CORI) Robotic-Assisted Total Knee Arthroplasty System: Results from First 500 Cases

Background

The use of robotic-assisted total knee arthroplasty (RA-TKA) is gaining traction. There is evidence to suggest that RA-TKA can help to optimize the precision and accuracy of implant positioning and that there may be protective effects on surrounding bony and soft tissues. Yet, there are important differences between the various RA-TKA systems currently on the market. One such newly introduced RA-TKA system uses imageless technology and performs bony cuts with the use of a burr-based device. The learning curve and complications unique to this system have yet to be assessed.

Methods

We evaluated 500 consecutive RA-TKA cases using a newly developed burr-based and imageless system which were done by a single surgeon between the months of October 2021 and February 2023. Operative times were recorded and compared to the previous 150 conventional TKA cases allowing for the learning curve to be calculated using the CUSUM method. Intraoperative and postoperative complications were categorically profiled.

Results

The learning curve of this RA-TKA system was found to be 6 cases. Intraoperative complications included unintended bony over resection (n = 3), soft tissue injury (n = 2), and robotic system hardware (n = 2) or software (n = 2) malfunction. Postoperative complications consisted of superficial pin site infection (n = 1) and periprosthetic fracture near the pin sites (n = 1). There were no identified cases of prosthetic joint infection, instability events, or wound complications.

Conclusions

The learning curve and the complication profile of a newly introduced imageless and burr-based RA-TKA system were described. This information serves to guide surgeons in adopting this technology and can counsel them regarding the potential pitfalls and challenges associated with its integration into practice. The work sheds light on the complexity and learning curve of the recently released imageless burr-based RA-TKA system. This important information is intended to help surgeons accept this cutting-edge technology by providing advice on any errors and difficulties that can occur when integrating it into clinical practice. This information can help surgeons navigate the complexities of integrating this new burr-based robotic technology into knee replacement procedures, enabling them to make well-informed decisions and receive guidance.

Robots on the Stage: A Snapshot of the American Robotic Total Knee Arthroplasty Market

» Computer-assisted robots aid orthopaedic surgeons in implant positioning and bony resection. Surgeons selecting a robot for their practice are faced with numerous options. This study aims to make the choice less daunting by reviewing the most commonly used Food and Drug Administration-approved robotic total knee arthroplasty platforms in the American arthroplasty market.» Modern total knee arthroplasty (TKA) robots use computer guidance to create a virtual knee model that serves as the surgeon's canvas for resection planning.» Most available robotic TKA (rTKA) systems are closed semiactive systems that restrict implant use to those of the manufacturer.» Each system has distinct imaging requirements, safety features, resection methods, and operating room footprints that will affect a surgeon's technique and practice.» Robots carry different purchase, maintenance, and equipment costs that will influence patient access across different socioeconomic groups.» Some studies show improved early patient-reported outcomes with rTKA, but long-term studies have yet to show clinical superiority over manual TKA.

Analysis of the Initial Learning Curve for Robotic-Assisted Total Knee Arthroplasty Using the ROSA® Knee System

Background/Objectives: Total knee arthroplasty (TKA) is a frequent procedure in orthopedic surgery. Advances in TKA include the development of robotic-assisted systems. Training in raTKA entails a learning curve to achieve proficiency comparable to conventional manual TKA (maTKA). Methods: We conducted a prospective study of the learning curve in raTKA using the Robotic Surgical Assistant (ROSA) Knee System. The study included 180 patients (90 raTKAs; 90 maTKAs) and three surgeons (one with >15 years of experience in maTKA). The cumulative sum control chart method (CUSUM) was used to define the transition from the learning phase to the mastered phase in raTKA. Results: The learning curves were 43 cases (experienced surgeons) and 61 cases (all surgeons). Mean operative times for both phases in raTKA were longer than in maTKA (p < 0.001). In raTKA, operative times in the learning phase were longer compared to those in the mastered phase (p < 0.001). Operative times in the learning and mastered phases for all surgeons in raTKA were significantly longer compared to those in maTKA (p < 0.001); however, operative times of the experienced surgeon in the mastered phase of raTKA and in maTKA showed no differences. Conclusions: The learning curve in raTKA is dependent upon the surgeon's previous experience in maTKA.

Robotic Total Knee Arthroplasty: An Update

Total knee arthroplasty (TKA) is a gold standard surgical procedure to improve pain and restore function in patients affected by moderate-to-severe severe gonarthrosis refractory to conservative treatments. Indeed, millions of these procedures are conducted yearly worldwide, with their number expected to increase in an ageing and more demanding population. Despite the progress that has been made in optimizing surgical techniques, prosthetic designs, and durability, up to 20% of patients are dissatisfied by the procedure or still report knee pain. From this perspective, the introduction of robotic TKA (R-TKA) in the late 1990s represented a valuable instrument in performing more accurate bone cuts and improving clinical outcomes. On the other hand, prolonged operative time, increased complications, and high costs of the devices slow down the diffusion of R-TKA. The advent of newer technological devices, including those using navigation systems, has made robotic surgery in the operatory room more common since the last decade. At present, many different robots are available, representing promising solutions to avoid persistent knee pain after TKA. We hereby describe their functionality, analyze potential benefits, and hint at future perspectives in this promising field.

Narrative review in learning curve and pediatric robotic training program

Background and Objective

Studying learning curve (LC) for robotic procedures and developing an adequate training program are two fundamental steps to standardize robotic procedures. With this aim, we analyzed the literature to study the LCs of different robotic procedures and the availability of standardized training problems.

Methods

The PubMed database was searched in the period from January 1995 to September 2022. Articles presenting LC and potential training programs in the pediatric population were chosen.

Key Content and Findings

Twenty papers were screened describing LC of robotic-assisted laparoscopic pyeloplasty (n=12), fundoplication (n=4), cholecystectomy (n=2), choledochal cyst resection (n=1), nephrectomy/partial nephrectomy (n=1) and lingual tonsillectomy (n=1), with a total of 1,251 procedures. In 10 studies there was only one single surgeon; nine had more than one; one did not specify how many surgeons participated. Twelve papers were retrospective single-center, three multicentric retrospective, four prospective and one was compared a retrospective case series to a prospective cohort. Most of these studies focused on operative time as the primary outcome. It was analyzed as the only outcome in three articles, along with complications in 14, time to discharge in eight, blood loss in three and pain killer use in three. The selected studies analyzed LC impacting operative planning (n=20), training (n=10) and costs (n=2).

Conclusions

There is still a long way to go to complete a standardized functional training for robotic surgery procedures in pediatric surgery. Moreover, the progressive reduction in costs expected in the years to come will play a key role in progressing the diffusion of this technology enabling the collection of data necessary to create a standardized pediatric surgery robotic training program.

The learning curve to ROSA: cases needed to match the surgery time between a robotic-assisted and a manual primary total knee arthroplasty

PURPOSE

Limited published data regarding the ROSA (Robotic Surgical Assistant) learning curve exist. This study evaluated the number of cases needed for an expert orthopaedic surgeon to master the ROSA system and match the operative time of robotic (raTKAs) and manual primary total knee arthroplasties (mTKAs).

METHODS

This retrospective comparative cohort study included two hundred patients with primary knee osteoarthritis. The study group consisted of an expert surgeon's first 100 raTKAs. The control group included 100 patients that underwent mTKAs from the same surgeon during the same period. The consecutive cases in each group were divided into ten subgroups, each of 10 cases. The groups were comparable concerning age, sex, BMI and Kellgren-Lawrence classification. We compared each subgroup's operative time and complications in mTKA and raTKA groups. We performed a cumsum analysis to construct the ROSA learning curve.

RESULTS

The first non-significant difference between the mTKAs and raTKAs operative times was observed in the subgroup of 62 to 71 cases. Till then, the operative time has been significantly lower for the mTKA than the raTKA group. The following groups of tens analysis (8th, 9th and 10th) showed no operative time difference between groups. The learning curve analysis demonstrated that the surgeon switched to the mastering phase from case 73 onwards. The two groups had no complication rate differences.

CONCLUSION

Our study demonstrated that about 70 cases are necessary for a senior surgeon to balance operative time between mTKAs and raTKAs using the ROSA system.

Initial Learning Curve for Robot-Assisted Total Knee Arthroplasty in a Dedicated Orthopedics Center

Background and objectives: Our study aimed to assess the learning curve for robot-assisted (RA) total knee arthroplasty (TKA) in our hospital, compare operative times between RA-TKAs and manual TKAs, and assess the early complications rate between the two approaches. Methods: We included 39 patients who underwent RA-TKA and 45 control patients subjected to manual TKA in the same period and operated on by the same surgical staff. We collected demographic and patient-related data to assess potential differences between the two groups. Results: No statistical differences were recorded in regard to age, BMI, sex, Kellgren-Lawrence classification, or limb alignment between patients undergoing RA-TKA and manual TKA, respectively. Three surgeons transitioned from the learning to the proficiency phase in our study after a number of 6, 4, and 3 cases, respectively. The overall operative time for the learning phase was 111.54 ± 20.45 min, significantly longer compared to the average of 86.43 ± 19.09 min in the proficiency phase (p = 0.0154) and 80.56 ± 17.03 min for manual TKAs (p < 0.0001). No statistically significant difference was recorded between the global operative time for the proficiency phase TKAs versus the controls. No major complications were recorded in either RA-TKA or manual TKA groups. Conclusions: Our results suggest that experienced surgeons may adopt RA-TKA using this platform and quickly adapt without significant complications.

Learning curve for robot-assisted knee arthroplasty; optimizing the learning curve to improve efficiency

The introduction of robot-assisted (RA) systems in knee arthroplasty has challenged surgeons to adopt the new technology in their customized surgical techniques, learn system controls, and adjust to automated processes. Despite the potential advantages of RA knee arthroplasty, some surgeons remain hesitant to adopt this novel technology owing to concerns regarding the cumbersome adaptation process. This narrative review addresses the learning-curve issues in RA knee arthroplasty based on the existing literature. Learning curves exist in terms of the operative time and stress level of the surgical team but not in the final implant positions. The factors that reduce the learning curve are previous experience with computer-assisted surgery (including robot or navigation systems), specialization in knee surgery, high volume of knee arthroplasty, optimization of the RA workflow, sequential implementation of RA surgery, and consistency of the surgical team. Worse clinical outcomes may occur in the early postoperative period, but not in the later period, in RA knee arthroplasty performed during the learning phase. No significant differences were observed in implant survival or complication rates between the RA knee arthroplasties performed during the learning and proficiency phases.

Technological innovations in shoulder replacement: current concepts and the future of robotics in total shoulder arthroplasty

BACKGROUND

Total shoulder arthroplasty (TSA) has been rapidly evolving over the last several decades, with innovative technological strategies being investigated and developed in order to achieve optimal component precision and joint alignment and stability, preserve implant longevity, and improve patient outcomes. Future advancements such as robotic-assisted surgeries, augmented reality, artificial intelligence, patient-specific instrumentation (PSI) and other peri- and preoperative planning tools will continue to revolutionize TSA. Robotic-assisted arthroplasty is a novel and increasingly popular alternative to the conventional arthroplasty procedure in the hip and knee but has not yet been investigated in the shoulder. Therefore, the purpose of this study was to conduct a narrative review of the literature on the evolution and projected trends of technological advances and robotic assistance in total shoulder arthroplasty.

METHODS

A narrative synthesis method was employed for this review, rather than a meta-analysis or systematic review of the literature. This decision was based on 2 primary factors: (1) the lack of eligible, peer-reviewed studies with high-quality level of evidence available for review on robotic-assisted shoulder arthroplasty, and (2) a narrative review allows for a broader scope of content analysis, including a comprehensive review of all technological advances-including robotics-within the field of TSA. A general literature search was performed using PubMed, Embase, and Cochrane Library databases. These databases were queried by 2 independent reviewers from database inception through November 11, 2022, for all articles investigating the role of robotics and technology assistance in total shoulder arthroplasty. Inclusion criteria included studies describing "shoulder arthroplasty" and "robotics."

RESULTS

After exclusion criteria were applied, 4 studies on robotic-assisted TSA were described in the review. Given the novelty of this technology and limited data on robotics in TSA, these studies consisted of a literature review, nonvalidated experimental biomechanical studies in sawbones models, and preclinical proof-of-concept cadaveric studies using prototype robotic technology primarily in conjunction with PSI. The remaining studies described the technological advancements in TSA, including PSI, computer-assisted navigation, artificial intelligence, machine learning, and virtual, augmented, and mixed reality. Although not yet commercially available, robotic-assisted TSA confers the theoretical advantages of precise humeral head cuts for restoration of proximal humerus anatomy, more accurate glenoid preparation, and improved soft-tissue assessment in limited early studies.

CONCLUSION

The evidence for the use of robotics in total hip arthroplasty and total knee arthroplasty demonstrates improved component accuracy, more precise radiographic measurements, and improved early/mid-term patient-reported and functional outcomes. Although no such data currently exist for shoulder arthroplasty given that the technology has not yet been commercialized, the lessons learned from robotic hip and knee surgery in conjunction with its rapid adoption suggests robotic-assisted TSA is on the horizon of innovation. By achieving a better understanding of the past, present, and future innovations in TSA through this narrative review, orthopedic surgeons can be better prepared for future applications.

A Systematic Review and Meta-Analysis of Conventional Versus Robotic-Assisted Total Knee Arthroplasty

This study aims to compare the outcomes and advantages of total knee arthroplasty (TKA) performed using conventional surgical techniques with those conducted using robotic-assisted methods in terms of operation time, Oxford knee score, range of motion, tourniquet time, and Western Ontario and McMaster Universities Arthritis index. We performed a literature search through five databases, namely, PubMed, Cochrane Central, Scopus, Embase, and Web of Science, from inception until July 3, 2023. Randomized clinical trials (RCTs) and cohorts comparing conventional TKA with robotic-assisted TKA were included. The risk of bias of the included RCTs was determined using the Cochrane risk of bias tool and the National Institutes of Health tool for cohort studies. We conducted a meta-analysis using Review Manager 5.4. To analyze continuous data, we calculated the mean difference (MD) along with its corresponding 95% confidence interval (CI). By synthesizing data from a comprehensive analysis, the study unveiled noteworthy distinctions between robotic-assisted arthroplasty and conventional arthroplasty across critical parameters. First, a substantial alteration in the hip-knee-ankle (HKA) angle was observed, with the robotic-assisted approach demonstrating a significant difference (MD = 0.84, 95% CI = 0.25-1.43, p = 0.005). Second, in terms of operative time, a notable reduction in surgical duration was noted with conventional TKA (MD = 16.85, 95% CI = 8.08-25.63, p = 0.0002). The assessment of tourniquet time exhibited a significantly longer duration for robotic-assisted arthroplasty (MD = 35.70, 95% CI = 27.80-43.61, p < 0.001). Our findings indicate that conventional TKA outperforms robotic-assisted TKA, primarily due to its shorter operative and tourniquet times, along with a more favorable change in the HKA angle. However, it is worth noting that robotic-assisted TKA showed a slight advantage in pain outcomes, although this advantage was not statistically significant. To gain a more comprehensive understanding, we recommend conducting a large-scale randomized controlled trial that directly compares both TKA methods. This trial should evaluate costs and long-term outcomes while ensuring consistent follow-up durations among studies. Such an approach would greatly assist orthopedic decision-making and contribute to improved TKA outcomes.

Robotic-assisted total knee arthroplasty is not associated with increased risk of postoperative deep vein thrombosis

PURPOSE

Prolongation of operation time due to registration and pin insertion has been reported with robotic-assisted total knee arthroplasty (RATKA), and there has been concern about an increase in the postoperative incidence of deep vein thrombosis (DVT). In this study, we compared the incidence of DVT after RATKA with that after conventional manual TKA (mTKA).

METHODS

This consecutive retrospective series included 141 knees that underwent primary TKA using the Journey II system. The CORI robot was used. There were 60 RATKAs and 81 mTKAs. Doppler ultrasound was performed in all patients on postoperative day 7 to determine whether DVT was present.

RESULTS

The operation time was longer in the RATKA cohort (99.5 min vs 78.0 min, p < 0.001). The overall incidence of DTV was 43.9% (62/141 knees), all of which were asymptomatic. There was no significant difference in incidence of DVT between RATKA and mTKA (50.0% vs 39.5%, p = 0.23). Use of the robot did not affect the incidence of DVT following TKA (odds ratio 1.02, 95% confidence interval 0.40-2.60; p = 0.96).

CONCLUSION

The incidence of DVT was not significantly different between RA-TKA and mTKA. Multiple logistic regression indicated that RATKA is not associated with increased risk of postoperative DVT.

LEVEL OF EVIDENCE

IV.

Concordance in Radiological Parameters of Different Knee Views After Total Knee Arthroplasty

Background Total knee arthroplasty (TKA) is a cost-effective treatment for the end-stage of knee osteoarthritis. Despite the improvements in this surgery, a significant percentage of patients still report dissatisfaction after knee arthroplasty. Radiological results have been used to predict clinical outcomes and satisfaction after knee replacement. This study aims to evaluate the concordance of a set of radiographic views to assess alignment on total knee arthroplasty. Methods A concordance study was designed with 105 patients (130 TKA) that underwent conventional total knee arthroplasty cruciate-retaining design recruited for the study and scheduled for their annual radiograph control. Measurements were performed on the following radiograph after total knee replacement: full-length standing anteroposterior and lateral radiograph, anteroposterior standing, lateral and axial knee view, and the knee "seated view". A musculoskeletal radiologist and a knee surgeon were recruited to perform the radiological measurement and then estimate the interobserver agreement.  Results There was an excellent correlation between Limb Length (LL), Hip-knee-ankle angle (HKA), Sagittal mechanical tibial component alignment (smTA), extension lateral and medial joint space (eLJS and eMJS), 90º flexion lateral and medial joint space (fLJS and fMJS) and Sagittal anatomic lateral view tibial component alignment (saLTA); the good correlation between Mechanical lateral femoral component alignment (mLFA), Sagittal anatomic tibial component alignment (saTA), Sagittal anatomic lateral view femoral component alignment 2 (saLFA2), Patella Height (PH); and moderate to poor correlation for the rest of measurements. Conclusion Excellent and good concordance can be achieved for radiographic measurements in different knee views to assess results after TKA. These findings must encourage future studies to address functional and survival outcomes using all knee views and not just one plane.

Individualized alignment and ligament balancing technique with the ROSA® robotic system for total knee arthroplasty

PURPOSE

Higher patient's expectations and dissatisfaction following total knee arthroplasty are well-documented phenomena. Despite the implications of different patients' related factors both modifiable and nonmodifiable, in the last decade a lot of emphasis has been focused on surgical technique, implant alignment and stability both as a cause and a potential solution of several problems.

METHODS

Different alignment and balancing techniques have been recently described and the introduction of new technologies such as computer and robotic-assisted surgery have been the basis for their optimization. In this paper, the surgical technique of the ROSA Knee System will be described focusing on the potential alignment options and the ligament balancing technique. The current literature available about the system will also be analyzed.

RESULTS

The ROSA® robotic system have been recently introduced in the market and presents specific and peculiar features to optimize ligament balancing and an individualized alignment of the implant in a three dimensional prospective.

DISCUSSION

The system is showing a favourable gap balancing technique and the possibility to create an individualized alignment. Preliminary results have now been shown in the literature both on the accuracy of the system and on clinical outcomes.

CONCLUSIONS

Preliminary results are promising both in terms of accuracy of the system and of clinical outcomes.