Total Knee Replacement Model Research Articles

Is an x-ray of the knee sufficient to assess the alignment of the leg? A study of total joint replacement with surgical navigation.

Background: Understanding the femorotibial mechanical axis (FTMA) of the leg is a necessary requirement to assess the outcome of total knee replacement (TKR). Short radiographs, which only capture the knee joint and do not include the center of the femoral head and center of the ankle, only provide us the anatomical axis (FTAA), and not the FTMA. The purpose of this study was to compare the FTMA and FTAA before and after navigated TKR. Methods: In 130 patients undergoing surgery to implant the same TKR model, an x-ray was taken including the hip, knee and ankle. Images were analysed using a computer program that calculates the mechanical and anatomical axis of the femur, tibia and femorotibial joint. An image-free navigation system with femorotibial tensioned gap technique was used for the arthroplasty implantation. After surgery, a new long x-ray was taken, where the measurements indicated above were taken again. Results: Pre-operative x-rays showed a mean difference of 6º between FTAA and FTMA (p<0.001). No significant interaction was seen with patient height, but it was in patients with varus deformity and higher BMI (p=0.029); the greatest discrepancy between the anatomical and mechanical axis of the limb was found in individuals with excess weight. After TKR, the mean FTMA was modified to achieve a neutral axis (180° ±3°), as well as a concentration of the figures that showed great pre-procedure disparity, which was verified by the difference in the pre- and post-operative SD (11.85 versus 3.13). The maximum difference between FTAA and FTMA, which stood at 18º before decreased to 5.5º post-TKR. Conclusions: There is a major discrepancy between the FTAA and FTMA that increases when there is pre-operative varus deformity and in patients with excess weight. After TKR, the FTMA became concentrated, and the mean axis shifted towards the neutral axis. Performing x-rays that only include the knee is not useful for assessing the limb’s alignment prior to or after TKR.

Impact of total knee replacement on trajectories of structure and symptoms in knee osteoarthritis - data from osteoarthritis initiative

Purpose: Understanding patterns of symptomatic and structural progression has been a major research focus in knee osteoarthritis (OA). Latent class growth analysis is a statistical approach that aims to identify clusters of subjects with similar progression trajectories. This approach has been used recently in knee OA to uncover longitudinal trajectories of both structural (e.g., quantitative MRI, joint space width (JSW), bone shape) and symptom (e.g., WOMAC Pain) progression. In longitudinal studies, it is common for subjects to drop out before the scheduled end of follow-up. Previous studies have shown that subjects undergoing total knee replacement (TKR) progress more quickly in the years leading up to TKR than subjects not undergoing the procedure. By not accounting for dropout due to TKR in estimating disease trajectories, we may fail to identify a trajectory of rapid progressors. Our objective was to evaluate the impact of incorporating TKR on estimates of structure (JSW) and symptom (WOMAC Pain) trajectories in knee OA. Methods: We used data from the Osteoarthritis Initiative (OAI), a multicenter, longitudinal, observational study of knee OA. We selected knees with radiographic, symptomatic OA at baseline (KL 2+, WOMAC Pain greater than 0). Eligible subjects had at least one follow-up visit. To assess joint structure we used serial measures of fixed JSW at x=0.25 in the medial tibiofemoral compartment, measured annually from baseline to year 4, and at years 6 and 8. WOMAC Pain was used to assess symptoms (0 - 100, 100 worst), assessed annually through year 9. After selecting patients with baseline pain, we modeled trajectories starting at year 1 to avoid modeling regression to the mean. We used latent class growth analysis (LGCA) to identify distinct subgroups, separately for JSW and pain. While LCGA can handle missing data under the missing at random assumption, these models on their own do not accommodate informative dropout. Thus, we used an extension of the LCGA framework to jointly model longitudinal outcome and time to TKR using joint latent class mixed models. We used the BIC, posterior group membership probability, and sufficient sample size per group (n=50) to select the final models. Results: We used data from 1,578 subjects with radiographic, symptomatic knee OA at baseline. 157 (10%) of subjects underwent TKR, with median time from baseline to TKR 5.5 years. On average, subjects undergoing TKR increased in pain by 2.3 points per year (19 points over 8 years) while subjects not undergoing TKR increased by 0.21 points per year (1.7 points over 8 years). Subjects undergoing TKR decreased in JSW by 0.31mm per year (2.5mm over 8 years) while subjects not undergoing TKR decreased in JSW by 0.09mm per year (0.75mm over 8 years). We found three distinct JSW trajectories. In our final model the majority (84%) of the cohort was in a stable trajectory, 5.9% of the cohort was in a late progression trajectory, and 8.4% of the cohort was an early progression trajectory (Figure 1). While the number and shape of trajectories was largely unchanged when we moved from the initial JSW model to the final joint JSW and TKR model, 32% of TKRs were re-classified, most from the stable to a progressing trajectory. In our initial model of pain trajectories we found 4 distinct trajectories: stable low pain (70%), rapidly increasing pain (13%), rapidly decreasing pain (5%) and increasing high pain (12%) (Figure 2a). After incorporating TKR our model identified a fifth trajectory. The increasing high pain trajectory (year 1 WOMAC pain 40) was split into a moderate increasing pain trajectory (year 1 WOMAC pain 28) and a high pain trajectory (year 1 WOMAC pain 52) (Figure 2b). 68% of TKRs were re-classified, most from the stable to increasing pain trajectory, stable to moderate pain, or the high to moderate pain. In the final model, only 2% of TKRs are in the stable pain trajectory, compared to 42% in the initial model. Conclusions: In longitudinal studies restricting analysis to completers may lead to underestimation of disease progression. In analyses seeking to uncover latent subgroups this could result in subjects being misclassified or entire trajectories being missed. Investigators studying disease progression in OA should consider the potential impact of dropout due to TKR, particularly when a large proportion of subjects undergo the procedure.View Large Image Figure ViewerDownload Hi-res image Download (PPT)View Large Image Figure ViewerDownload Hi-res image Download (PPT)

The Cost-Effectiveness of Oral Direct Factor Xa Inhibitors Compared with Low-Molecular-Weight Heparin for the Prevention of Venous Thromboembolism Prophylaxis in Total Hip or Knee Replacement Surgery

Major orthopedic surgery is associated with a high risk of venous thromboembolism (VTE). Anticoagulants are recommended to prevent VTE, and recently an oral direct factor Xa inhibitor (FXaI) was approved for this indication. We compared the cost-effectiveness of FXaIs with low-molecular-weight heparin (LMWH) in patients undergoing total hip replacement (THR) or total knee replacement (TKR) surgery. A decision-tree model was developed to compare the cost-effectiveness of oral direct FXaIs (rivaroxaban, apixaban, and edoxaban) to subcutaneous LMWHs (enoxaparin and dalteparin), with separate models for THR and TKR. The analysis was conducted over a 180-day postoperative time horizon from the U.S. Medicare perspective. The model was developed using TreeAge Pro 2011 (TreeAge Software Inc., Williamstown, MA, USA). Efficacy and safety data (probabilities of distal and proximal deep vein thrombosis, symptomatic pulmonary embolism, and major bleeding) were derived from a systematic review and meta-analysis of phase II and III clinical trials. Costs and quality-adjusted life-years (QALYs) are reported. One-way and probabilistic sensitivity analyses were performed to evaluate parameter uncertainty. In the THR model, the average costs per patient for FXaIs and LMWHs were $18,762 and $18,897, respectively, and the QALYs were 0.938 and 0.932. In the TKR model, the average cost per patient for FXaIs and LMWHs were $18,804 and $18,991, respectively, and the QALYs were 0.935 and 0.931. In both models, FXaIs dominated LMWH (less costly and more efficacious). Neither model was sensitive to changes in any of the variables in the one-way sensitivity analyses. Probabilistic sensitivity analysis indicated that FXaIs were cost-effective in more than 99% of iterations in the THR population and in 98% of iterations in the TKR population assuming a willingness-to-pay threshold of $50,000/QALY. Oral direct FXaIs may be an economically dominant strategy compared with LMWHs for VTE prophylaxis in patients undergoing either THR or TKR surgery.

Gait cycle comparions of cruciate sacrifice for total knee design.-explicit finite element

Joint kinematics and contact mechanics dictate the success of current total knee replacement (TKR) devices. Computational contact prediction is a feasible way of evaluating new TKR designs prior to physical testing and implementation. Previous finite element (FE) knee models have generally been used to predict stresses on contact areas and/or areas subjected to static or quasi-static loading. Explicit dynamic FE analyses have recently been used to effectively predict TKR kinematics and contact mechanics during dynamic loading conditions. In this study, we compared the functional load transmission and kinematic performance of two posterior-stabilized designs, standard and post-cam TKR versions, over a standardized loading cycle using three-dimensional contact finite element analysis. Our objective was to develop and experimentally validate an explicit FE TKR model that incorporates femoral-bearing articulations. Finite element-based computational contact pressure predictions were applied to gait cycles using both force-controlled and displacement-controlled inputs. A standard prosthesis showed a reduction in contact pressure compared with post-cam prosthesis components, as it redistributed the knee motion to two articulating interfaces with more linear motions at each interface. In this FE analysis, the wear of TKR bearings was dependent on kinematics at the articulating surfaces and on prosthesis design.

Probabilistic Finite Element Prediction of the Active Lower Limb Model

The scope of this paper is to explore the input parameters of a Finite Element (FE) model of an active lower limb that are most influential in determining the size and the shape of the performance envelope of the kinematics and peak contact pressure of the knee tibial insert introduced during a Total Knee Replacement (TKR) surgery. The active lower limb FE model simulates the stair ascent and it provides a more complicated setup than the isolated TKR model which includes the femoral component and the tibial insert. It includes bones, TKR implant, soft tissues and applied forces. Two probabilistic methods are used together with the FE model to generate the performance envelopes and to explore the key parameters: the Monte Carlo Simulation Technique (MCST) and the Response Surface Method (RSM). It is investigated how the uncertainties in a reduced set of 22 input variables of the FE model affect the kinematics and peak contact pressure of the knee tibial insert. The kinematics is reported in the Grood and Suntay system, where all motion is relative to the femoral component of the TKR. Reported tibial component kinematics are tibio-femoral flexion angle, anterior-posterior and medial-lateral displacement, internal-external and varus-valgus rotation (i.e. abduction-adduction), while the reported patella kinematics are patella-femoral flexion angle, medial-lateral shift and medial-lateral tilt. Tibio-femoral and patella-femoral contact pressures are also of interest. Following a sensitivity analysis, a reduced set of input variables is derived, which represent the set of key parameters which influence the performance envelopes. The findings of this work are paramount to the orthopedic surgeons who may want to know the key parameters that can influence the performance of the TKR for a given human activity.

A Cost-Effectiveness Model Comparing Rivaroxaban and Dabigatran Etexilate with Enoxaparin Sodium as Thromboprophylaxis after Total Hip and Total Knee Replacement in the Irish Healthcare Setting

It has been estimated that major orthopaedic surgery has the highest risk of venous thromboembolism (deep vein thrombosis and pulmonary embolism) when compared with other surgery. Two new orally active anticoagulants have recently become licensed in Ireland for the primary prevention of venous thromboembolism in adult patients undergoing elective total hip replacement (THR) or total knee replacement (TKR). Rivaroxaban (Xarelto) is a direct factor Xa inhibitor and dabigatran etexilate (Pradaxa) is a prodrug of the active compound dabigatran, which inhibits thrombin. To evaluate the cost effectiveness of rivaroxaban and dabigatran etexilate compared with enoxaparin sodium for the prophylaxis of venous thromboembolism in patients undergoing elective THR and TKR in the Irish healthcare setting. The evaluation was conducted from the Irish health-payer perspective. A static decision-tree model was developed with a 180-day post-surgery time horizon. Separate models for the disease states THR and TKR were run to accommodate the different venous thromboembolism risks associated with each procedure. Outcome measures were QALYs and life-years gained (LYG). Costs were valued in euro, year 2008 values. One-way sensitivity analysis of all probabilities in the model was performed. A probabilistic sensitivity analysis using second-order Monte Carlo simulation was performed to determine the probability of cost effectiveness at euro 45,000 per QALY threshold. In the THR base-case model, rivaroxaban dominated both dabigatran etexilate and enoxaparin sodium. The incremental cost-effectiveness ratios for dabigatran etexilate relative to enoxaparin were euro 23,934 per LYG and euro 17,835 per QALY. In the TKR base-case model, rivaroxaban dominated both dabigatran etexilate and enoxaparin sodium. Dabigatran etexilate also dominated enoxaparin sodium. In the one-way sensitivity analysis, the THR model was robust to all but four probability variations; the TKR model was robust to all variations. At a cost-effectiveness threshold of euro 45,000 per QALY, the probability that rivaroxaban was the most cost-effective strategy after THR was 39%, followed by dabigatran etexilate at 32% and enoxaparin sodium at 29%. The probability that rivaroxaban was the most cost-effective strategy after TKR was 46%, followed by dabigatran etexilate at 30% and enoxaparin sodium at 24%. Base-case analysis indicates that when both rivaroxaban and dabigatran etexilate are compared with enoxaparin sodium, rivaroxaban is the less costly and more effective option after THR and TKR. Probabilistic sensitivity analysis indicates that rivaroxaban is the most cost-effective strategy at a cost-effectiveness threshold of euro 45,000 per QALY; however, there is uncertainty regarding this strategy being more cost effective than dabigatran etexilate when both are compared with enoxaparin sodium.

Explicit finite element modeling of total knee replacement mechanics

Joint kinematics and contact mechanics dictate the success of current total knee replacement (TKR) devices. Efficient computer models present an effective way of evaluating these characteristics. Predicted contact stress and area due to articulations at the tibio-femoral and patello-femoral interfaces indicate potential clinical performance. Previous finite element (FE) knee models have generally been used to predict contact stresses and/or areas during static or quasi-static loading conditions. Explicit dynamic FE analyses have recently been used to efficiently predict TKR kinematics and contact mechanics during dynamic loading conditions. The objective of this study was to develop and experimentally validate an explicit FE TKR model that incorporates tibio-femoral and patello-femoral articulations. For computational efficiency, we developed rigid body analyses that can reasonably reproduce the kinematics, contact pressure distribution, and contact area of a fully deformable system. Results from the deformable model showed that the patello-femoral and tibio-femoral kinematics were in good agreement with experimental knee simulator measurements. Kinematic results from the rigid body analyses were nearly identical to those from the fully deformable model, and the contact pressure and contact area correlation was acceptable given the great reduction in analysis time. Component mesh density studied had little effect on the predicted kinematics, particularly for the patellar component, and small effects on the predicted contact pressure and area. These analyses have shown that, at low computational cost, a force-control dynamic simulation of a gait cycle can yield useful and predictable results.