Mid-level constraint designs for total knee arthroplasty (TKA) are intended to reduce coronal plane laxity. Our aims were to compare kinematics and ligament forces of the Zimmer Biomet Persona posterior-stabilized (PS) and mid-level designs in the coronal, sagittal, and axial planes under loads simulating clinical exams of the knee in a cadaver model. We performed TKA on eight cadaveric knees and loaded them using a robotic manipulator. We tested both PS and mid-level designs under loads simulating clinical exams via applied varus and valgus moments, internal-external (IE) rotation moments, and anteroposterior forces at 0°, 30°, and 90° of flexion. We measured the resulting tibiofemoral angulations and translations. We also quantified the forces carried by the medial and lateral collateral ligaments (MCL/LCL) via serial sectioning of these structures and use of the principle of superposition.Aims
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Surgeons commonly resect additional distal femur during primary total knee arthroplasty (TKA) to correct a flexion contracture. However, the effect of joint line proximalization on TKA kinematics is unclear. Thus, our goal was to quantify the effect of additional distal femoral resection on knee extension and mid-flexion laxity. Six computational knee models with TKA-specific capsular and collateral ligament properties were implanted with a contemporary posterior-stabilized TKA. A 10° flexion contracture was modeled to simulate a capsular contracture. Distal femoral resections of +2 mm and +4 mm were simulated for each model. The knees were then extended under standardized torque to quantify additional knee extension achieved. Subsequently, varus and valgus torques of ±10 Nm were applied as the knee was flexed from 0° to 90° at the baseline, +2 mm, and +4 mm distal resections. Coronal laxity, defined as the sum of varus and valgus angulation with respective torques, was measured at mid-flexion.Introduction
Methods
Manipulation under anesthesia (MUA) remains the gold standard to address restricted range of motion (ROM) within 3–6 months after primary total knee arthroplasty (TKA). However, there is little data on the outcomes of MUA with different types of anesthesia. We sought to compare the outcomes of patients undergoing MUA with intravenous (IV) sedation and neuraxial anesthesia. We identified 548 MUAs after primary TKA (136 IV sedation, 413 neuraxial anesthesia) at a single institution from 2016–2019. Mean age was 62 years and 349 patients (64%) were female. Mean body mass index was 32 kg/m2. The mean time from primary TKA to MUA was 10 weeks. Mean pre-MUA ROM was similar between each group; mean pre-MUA extension was 4.2° (p=0.35) and mean pre-MUA flexion was 77° (p=0.56). Patient demographics were statistically similar between both groups. We compared immediate complications, including fracture, extensor mechanism disruptions, and wound complications, Visual analogue pain scores (VAS), length of stay (LOS), and immediate and 3 month follow-up ROM between these groups.Introduction
Methods
Obesity has been shown to be an independent risk factor for aseptic loosening of the tibia and smaller implant size has been correlated with increased risk of failure of tibial components in obese patients [1,2]. Many surgeons have noted that obese patients, especially females, not uncommonly will have small implant sizes. As such, we hypothesized that obesity was not directly correlated with total knee arthroplasty (TKA) implant sizes. The purpose of this study was to determine if increasing body mass index (BMI), height, and/or weight is associated with implant size in primary TKA. The institutional registry of a single academic center was reviewed to identify all primary TKAs performed between 2005 and 2016. Those without minimum 2-year follow-up or with incomplete implant data were excluded. The different manufacturer's implant designs were categorized based on anteroposterior and mediolateral dimensions of the femoral and tibial component sizes and cross sectional area was determined. BMI was categorized by the World Health Organization (WHO) obesity scale (Class I: BMI 30 to <35, Class II: BMI 35 to <40, Class III: BMI 40 kg/m2 or greater). Patient demographics including sex, height, weight, and BMI were analyzed to evaluate correlations with implant size using Pearson correlation coefficients.Background
Methods
Whether anterior referencing (AR) or posterior referencing (PR) are optimal to position and size the femoral component in Total Knee Arthroplasty (TKA) remains controversial. This controversy stems, in part, from a lack of understanding of whether one technique more consistently balances the medial/lateral collateral ligaments (MCL & LCL) in flexion and extension. Therefore, our goal was to compare AR and PR in terms of: (1) maximum MCL and LCL forces in passive flexion, and (2) medial and lateral gaps at full extension and 90‖ of flexion. In addition, we identified geometric landmarks that could help predict the ligament forces during flexion. Computational models of six knees were virtually implanted with TKAs based on our previously-developed framework. AR and PR were simulated in each of the six models. A Posterior Stabilized implant was utilized. Standard AR and PR cuts and component positioning were simulated with the femoral component aligned parallel to the transepicondylar axis. In both AR and PR models, the distal femoral cut and the proximal tibial cut were perpendicular to the femoral and tibial mechanical axis, respectively. The amount of posterior bone resected with AR knees ranged from 4.2 to 10.8 mm, and with PR knees ranged from 4.2 to 8 mm. Ligament properties were standardized to reflect a balanced knee at full extension. Passive flexion under 500 N of compression was applied and the MCL and LCL forces were predicted. A new measure, the MCL ratio, that incorporated the femoral insertion of the anterior fiber of MCL relative to the posterior and distal femoral cuts was estimated (Fig. 1). A varus/valgus moment of 6 Nm was applied at full extension and 90‖ of flexion, and the corresponding lateral and medial gaps were measured.Introduction
Methods
