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In this study, we developed and validated a robotic testbench to investigate the biomechanical compatibility of three total knee arthroplasty (TKA) configurations under different loading conditions, including varus-valgus and internal-external loading across defined flexion angles. The testbench captured force-torque data, position, and quaternion information of the knee joint. A cadaver study was conducted, encompassing a native knee joint assessment and successive TKA testing, featuring femoral component rotations at -5°, 0°, and +5° relative to the transepicondylar axis of the femur. The native knee showed enhanced stability in varus-valgus loading, with the +5° external rotation TKA displaying the smallest deviation, indicating biomechanical compatibility. The robotic testbench consistently demonstrated high precision across all loading conditions. The findings demonstrated that the TKA configuration with a +5° external rotation displayed the minimal mean deviation under internal-external loading, indicating superior joint stability. These results contribute meaningful understanding regarding the influence of different TKA configurations on knee joint biomechanics, potentially influencing surgical planning and implant positioning. We are making the collected dataset available for further biomechanical model development and plan to explore the 6 Degrees of Freedom (DOF) robotic platform for additional biomechanical analysis. This study highlights the versatility and usefulness of the robotic testbench as an instrumental tool for expanding our understanding of knee joint biomechanics.

Purpose: The number of primary total knee arthroplasties (TKA) is expected to rise constantly. For patients and healthcare providers, the early identification of risk factors therefore becomes increasingly fundamental in the context of precision medicine. Others have already investigated the detection of risk factors by conducting literature reviews and applying conventional statistical methods. Since the prediction of events has been moderately accurate, a more comprehensive approach is needed. Machine learning (ML) algorithms have had ample success in many disciplines. However, these methods have not yet had a significant impact in orthopaedic research. The selection of a data source as well as the inclusion of relevant parameters is of utmost importance in this context. In this study, a standardized approach for ML in TKA to predict complications during surgery and an irregular surgery duration using data from two German arthroplasty-specific registries was evaluated., Methods: The dataset is based on two initiatives of the German Society for Orthopaedics and Orthopaedic Surgery. A problem statement and initial parameters were defined. After screening, cleaning and preparation of these datasets, 864 cases of primary TKA (2016-2019) were gathered. The XGBoost algorithm was chosen and applied with a hyperparameter search, a cross validation and a loss weighting to cope with class imbalance. For final evaluation, several metrics (accuracy, sensitivity, specificity, AUC) were calculated., Results: An accuracy of 92.0%, sensitivity of 34.8%, specificity of 95.8%, and AUC of 78.0% were achieved for predicting complications in primary TKA and 93.4%, 74.0%, 96.3%, and 91.6% for predicting irregular surgery duration, respectively. While traditional statistics (correlation coefficient) could not find any relevant correlation between any two parameters, the feature importance revealed several non-linear outcomes., Conclusion: In this study, a feasible ML model to predict outcomes of primary TKA with very promising results was built. Complex correlations between parameters were detected, which could not be recognized by conventional statistical analysis. Arthroplasty-specific data were identified as relevant by the ML model and should be included in future clinical applications. Furthermore, an interdisciplinary interpretation as well as evaluation of the results by a data scientist and an orthopaedic surgeon are of paramount importance., Level of Evidence: Level IV., (© 2022. The Author(s).)

Background/aim: Increasing economic pressure in modern healthcare necessitates an increase in efficiency in total knee arthroplasty (TKA) while maintaining high-quality outcomes. Removal of debris using pulsatile lavage (PL) during cement polymerization may considerably reduce the operative duration. However, water can penetrate the interface, resulting in impaired implant fixation. The aim of the present study was to investigate the impact of early-onset PL during bone cement polymerization on implant fixation and operative duration., Materials and Methods: Cemented implantation of tibial trays was performed in 20 fresh-frozen human tibiae from 10 donors in a matched-pair study design in two groups: 1) PL during cement polymerization; and 2) PL after completion of the polymerization process. The cement penetration depth was analysed by computed tomography (CT), and the pull-out force was measured to evaluate primary implant fixation. The duration of the procedure was recorded for both groups., Results: Comparable pull-out forces were observed in the experimental (2,213 N) and control groups (2,350 N; p=0.68). The mean depth of cement penetration was similar in both groups. PL during cement polymerization could decrease the operative duration by 10 min., Conclusion: The application of PL during cement polymerization could significantly reduce operative duration and had no adverse effect on the mechanical fixation of the tibial component., (Copyright © 2022, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Purpose: Artificial intelligence (AI) in healthcare is rapidly growing and offers novel options of data analysis. Machine learning (ML) represents a distinct application of AI, which is capable of generating predictions and has already been tested in different medical specialties with various approaches such as diagnostic applications, cost predictions or identification of risk factors. In orthopaedics, this technology has only recently been introduced and the literature on ML in knee arthroplasty is scarce. In this review, we aim to investigate which predictions are already feasible using ML models in knee arthroplasty to identify prerequisites for the effective use of this novel approach. For this reason, we conducted a systematic review of ML algorithms for outcome prediction in knee arthroplasty., Methods: A comprehensive search of PubMed, Medline database and the Cochrane Library was conducted to find ML applications for knee arthroplasty. All relevant articles were systematically retrieved and evaluated by an orthopaedic surgeon and a data scientist on the basis of the PRISMA statement. The search strategy yielded 225 articles of which 19 were finally assessed as eligible. A modified Coleman Methodology Score (mCMS) was applied to account for a methodological evaluation., Results: The studies presented in this review demonstrated fair to good results (AUC median 0.76/range 0.57-0.98), while heterogeneous prediction models were analysed: complications (6), costs (4), functional outcome (3), revision (2), postoperative satisfaction (2), surgical technique (1) and biomechanical properties (1) were investigated. The median mCMS was 65 (range 40-80) points., Conclusion: The prediction of distinct outcomes with ML models applying specific data is already feasible; however, the prediction of more complex outcomes is still inaccurate. Registry data on knee arthroplasty have not been fully analysed yet so that specific parameters have not been sufficiently evaluated. The inclusion of specific input data as well as the collaboration of orthopaedic surgeons and data scientists are essential prerequisites to fully utilize the capacity of ML in knee arthroplasty. Future studies should investigate prospective data with specific and longitudinally recorded parameters., Level of Evidence: III., (© 2022. The Author(s).)

Background: Since arthritis of the knee is one of the most common pathologies in industrialized nations, there has been a growing interest in fast-track total knee arthroplasty (TKA). However, while one of the main concerns is the role of a tourniquet, the available data are inconclusive., Aim: This study sought to assess the link between postoperative outcomes and use of a tourniquet in TKA. Our goal was to determine whether it is justified to forego tourniquet use as indicated by the fast-track concept., Methods: The participants (n = 108) in this retrospective, non-randomized study were assigned into two groups after they satisfied the inclusion criteria: primary gonarthrosis or secondary gonarthrosis without previous arthrotomy. TKA was performed without (Group I, n = 55) or with (Group II, n = 53) a tourniquet. The postoperative outcome was evaluated in terms of postoperative pain, based on a numeric rating scale (NRS) and the need for pain medication, and postoperative function, based on range of motion (ROM) and walking tests., Results: Overall, no significant correlations were observed between tourniquet use and postoperative pain according to the NRS. Group I required less oxycodone, but more non-opioids. There was no significant difference in the improvement in pre- to postoperative ROM with regard to tourniquet use. The final walking distance was significantly longer in Group I., Conclusions: These results suggest that there is no strongly significant link between the postoperative outcome and the use of a tourniquet. However, further studies will be needed to determine whether a tourniquet may have some other impact on TKA.

The increasing implantation rates of knee arthroplasties are associated with a growing prevalence of complications like periprosthetic fractures. Underlying patient, implant and/or operation technique-related risk factors contribute to these fractures which often occur after minor trauma. In the diagnostic process, fracture dislocation, implant stability, and integrity of the extensor mechanism have to be assessed. Valid classification systems are available to guide treatment decisions. Treatment goals are precise reposition, stable fixation, restoration of function, and early mobilization. In the case of an operative revision, the surgeon has to know the implanted device and has to be prepared for extended procedures and revision arthroplasty. Less invasive fixation devices like retrograde nailing or LISS are often sufficient to stabilize femoral supracondylar fractures, while loosening of the implant often requires extended exchange arthroplasty. Tibial fractures are often associated with osteolysis and bone loss which has to be addressed with bone grafts or augmented revision implants. Long-stemmed implants allow bypassing of the reconstructed defect and provide a stable solution for early mobilization. Patella fractures with stable or asymptomatic implants and continuity of the extensor mechanism should be treated conservatively. If reconstruction becomes necessary, results are often associated with significant functional limitations.

Total knee arthroplasty (TKA) is one of the most frequent orthopaedic surgical procedures. Despite continuous improvements in the endoprostheses, instruments, and operative techniques, revision TKA has a rate of about 10% of overall TKA. In addition to the restoration of the periprosthetic bone stock and a precise alignment, the choice of an adequate implant, which meets the patient's specific requirements, has high impact on the outcome. The most significant differences between implants involve the degree of reconstructed joint area (uni-, bi-, tri-compartimental) and the order of the constraining forces between the femoral and tibial component. Implants for revision TKA commonly range from un- or semiconstrained resurfacing implants to fully constrained hinged endoprostheses. In case of severe osseous, ligamentous, and/or muscular defects, special tumor endoprostheses or implants for arthrodesis might be an alternative option.

Arthrofibrosis is one of the most common complications after total knee arthroplasty with an overall incidence of approximately 10%. Nevertheless, published data are rare and clinical trials mostly include small and heterogeneous patient series resulting in controversial conclusions. Clinically, arthrofibrosis after knee arthroplasty is defined as (painful) stiffness with scarring and soft tissue proliferation. Differentiation between local (peripatellar) and generalized fibrosis is therapeutically relevant. Histopathology typically shows subsynovial fibrosis with synovial hyperplasia, chronic inflammatory infiltration, and excessive and unregulated proliferation of collagen and fibroblasts. Diagnostic strategies are based on the exclusion of differential causes for painful knee stiffness, and especially the exclusion of low-grade infections represents a diagnostic challenge. Early and intensive physiotherapy combined with sufficient analgesia should be initiated as a basic therapy. The next therapeutic steps for persisting arthrofibrosis include closed manipulation and open arthrolysis. Arthroscopic interventions should be limited to local fibrosis. Revision arthroplasty represents a rescue surgery, often associated with recurrence of fibrosis. Prevention of arthrofibrosis by sufficient analgesia and early physiotherapy remains the best treatment option for painful stiffness after knee arthroplasty.

Reconstruction of the extensor mechanism in extended revision after total knee replacement and tumor surgery remains a clinically relevant problem. Due to large tibial bone defects with resection of the extensor insertion area, the specific problem of patella ligament refixation frequently arises. Several biological approaches and augmentation techniques have been published. Most of these are associated with a high rate of revision surgery because of failed replacement of the extensor mechanism and unsatisfactory functional outcome. Surgical reconstruction of these tendon defects is complicated by the difficulty of completely neutralizing tensional force across the repair. To overcome this problem, methods have been developed to reinforce the reconstruction with overlapping flaps; in addition, artificial materials are being increasingly used for tension neutralization. These artificial strips need special fixation mechanisms on the tibial component and specific technical modifications of the prosthesis. The present study gives an overview of reconstruction modalities of the extensor mechanism and provides an improved technology for better reconstruction by using artificial strips combined with specific modifications of the tibial component.

Background: Arthrotic deformities with changes in knee geometry can produce difficulties in implanting long stem knee prosthesis systems using intramedullary alignment. They can result in incorrect lower limb axis and prosthesis positioning. The aim of the presented study was to measure knee geometry in patients with varus and valgus gonarthrosis in order to define diagnosis related differences., Methods: A total of 75 patients with indication for total knee arthroplasty were divided in two groups using the weight bearing lower limb axis: patients with varus gonarthrosis (n=43) and with valgus gonarthrosis (n=32). Angles and extensions, important for knee prosthesis implantation, were measured, digitalized and analyzed. The results were investigated for diagnosis specific differences., Results: After regulation of the measured extension in mean femur/tibia lengths, significant diagnosis specific differences were found: femur condyles were widened towards pathologic weight bearing (P<0.044), and the mechanical tibia axis of the varus gonarthrosis group is transferred to the lateral side (P<0.046) and in projection over the lateral internal cortical substance., Conclusion: The significant differences in deformed arthrotic knees indicate that for an optimal postoperative result the use of standard implants is not always sufficient. Modular knee prosthesis systems can provide adequately for individual demands.