Determining proper joint tension in reverse total shoulder arthroplasty (rTSA) can be a challenging task for shoulder surgeons. Often, this is a subjective metric learned by feel during fellowship training with no real quantitative measures of what proper tension encompasses. Tension too high can potentially lead to scapular stress fractures and limitation of range of motion (ROM), whereas tension too low may lead to instability. New technologies that detect joint load intraoperatively create the opportunity to observe rTSA joint reaction forces in a clinical setting for the first time. The purpose of this study was to observe the differences in rTSA loads in cases that utilized two different humeral liner sizes. Ten different surgeons performed a total of 37 rTSA cases with the same implant system. During the procedure, each surgeon reconstructed the rTSA implants to his or her own preferred tension. A wireless load sensing humeral liner trial (VERASENSE for Equinoxe, OrthoSensor, Dania Beach, FL) was used in lieu of a traditional plastic humeral liner trial to provide real-time load data to the operating surgeon during the procedure. Two humeral liner trial sizes were offered in 38mm and 42mm curvatures and were selected each case based on surgeon preference. To ensure consistent measurements between surgeons, a standardized ROM assessment consisting of four dynamic maneuvers (maximum internal to external rotation at 0°, 45°, and 90° of abduction, and a maximum flexion/extension maneuver) and three static maneuvers (arm overhead, across the body, and behind the back) was completed in each case. Deidentified load data in lbf was collected and sorted based on which size liner was selected. Differences in means for minimum and maximum load values for the four dynamic maneuvers and differences in means for the three static maneuvers were calculated using 2-tailed unpaired t-tests.INTRODUCTION
METHODS
Close to 30% of the surgical causes of readmission within 90 days post-total knee arthroplasty (TKA) and nearly half of those occurring in the first 2 years are caused by instability, arthrofibrosis, and malalignment, all of which may be addressed by improving knee balance. Furthermore, the recently launched Comprehensive Care for Joint Replacement (CJR) initiative mandates that any increase in post-acute care costs through 90-days post-discharge will come directly from the bundle payment paid to providers. Post-discharge costs, including the cost of readmissions for complications are one of the largest drivers of the 90-day cost of care. It is hypothesized that balanced knees post-TKA will lower the true provider costs within the 90-day bundle. Cost, outcomes and resource utilization data were collected from three independent surgeons pre- and post- adoption of intraoperative technology developed to provide real-time, quantitative load data within the knee. In addition, data were collected from Medicare claims, hospital records, electronic medical records (EMR), clinical, and specialty databases. The cohorts consisted of 932 patients in the pre-adoption group and 709 patients in the post-adoption group. These 2 groups were compared to the CMS national average data from 291,201 cases. The groups were controlled for age, sex, state, and BMI with no major differences between cohorts. The cost factors considered were the length of hospital stay, physician visits and physical therapy visits in addition to post-operative complications (e.g., manipulation under anesthesia (MUA) and aseptic revision).Introduction
Methods
Patient recovery after total knee arthroplasty remains highly variable. Despite the growing interest in and implementation of patient reported outcome measures (e.g. Knee Society Score, Oxford Knee Score), the recovery process of the individual patient is poorly monitored. Unfortunately, patient reported outcomes represent a complex interaction of multiple physiological and psychological aspects, they are also limited by the discrete time intervals at which they are administered. The use of wearable sensors presents a potential alternative by continuously monitoring a patient's physical activity. These sensors however present their own challenges. This paper deals with the interpretation of the high frequency time signals acquired when using accelerometer-based wearable sensors. During a preliminary validation, five healthy subjects were equipped with two wireless inertial measurement units (IMUs). Using adhesive tape, these IMU sensors were attached to the thigh and shank respectively. All subjects performed a series of supervised activities of daily living (ADL) in their everyday environment (1: walking, 2: stair ascent, 3: stair descent, 4: sitting, 5: laying, 6: standing). The supervisor timestamped the performed activities, such that the raw IMU signals could be uniquely linked to the performed activities. Subsequently, the acquired signals were reduced in Python. Each five second time window was characterized by the minimum, maximum and mean acceleration per sensor node. In addition, the frequency response was analyzed per sensor node as well as the correlation between both sensor nodes. Various machine learning approaches were subsequently implemented to predict the performed activities. Thereby, 60% of the acquired signals were used to train the mathematical models. These models were than used to predict the activity associated with the remaining 40% of the experimentally obtained data.Introduction & Aims
Method
Sensor technology is seeing increased utility in joint arthroplasty, guiding surgeons in assessing the soft tissue envelope intra-operatively (OrthoSensor, FL, USA). Meanwhile, surgical navigation systems are also transforming, with the recent introduction of inertial measurement unit (IMU) based systems no longer requiring optical trackers and infrared camera systems in the operating room (i.e. OrthAlign, CA, USA). Both approaches have now been combined by embedding an IMU into an intercompartmental load sensor. As a result, the alignment of the tibial varus/valgus cut is now measured concurrently with the mediolateral tibiofemoral contact load magnitudes and locations. The wireless sensor is geometrically identical to the tibial insert trial and is placed on the tibial cutting plane after completing the proximal tibial cut. Subsequently, the knee is moved through a simple calibration maneuver, rotating the tibia around the heel. As a result, the sensor provides a direct assessment of the obtained tibial varus/valgus alignment. This study presents the validation of this measurement. In an in-vitro setting, sensor-based alignment measurements were repeated for several simulated conditions. First, the tibia was cut in near-neutral alignment as guided by a traditional, marker-based surgical navigation system (Stryker, MI, USA). Subsequently, the sensor was inserted and a minimum of five repeated sensor measurements were performed. Following these measurements, a 3D printed shim was inserted between the sensor and the tibial cutting plane, introducing an additional 2 or 4 degrees of varus or valgus, with the measurements then being repeated. Again, for each condition, a minimum of five sensor measurements were performed. Following completion of the tests, a computed tomography (CT) scan of the tibia was obtained and reconstructed using open source software (3DSlicer).Introduction and Aims
Method
Over the last decade, sensor technology has proven its benefits in total knee arthroplasty, allowing the quantitative assessment of tension in the medial and lateral compartment of the tibiofemoral joint through the range of motion (VERASENSE, OrthoSensor Inc, FL, USA). In reversal total shoulder arthroplasty, it is well understood that stability is primarily controlled by the active and passive structures surrounding the articulating surfaces. At current, assessing the tension in these stabilizing structures remains however highly subjective and relies on the surgeons’ feel and experience. In an attempt to quantify this feel and address instability as a dominant cause for revision surgery, this paper introduces an intra-articular load sensor for reverse total shoulder arthroplasty (RTSA). Using the capacitive load sensing technology embedded in instrumented tibial trays, a wireless, instrumented humeral trial has been developed. The wireless communication enables real-time display of the three-dimensional load vector and load magnitude in the glenohumeral joint during component trialing in RTSA. In an in-vitro setting, this sensor was used in two reverse total shoulder arthroplasties. The resulting load vectors were captured through the range of motion while the joint was artificially tightened by adding shims to the humeral tray.Introduction & Aims
Method
Cementless unicondylar knee implants are intended to offer surgeons the potential of a faster and less invasive surgery experience in comparison to cemented procedures. However, initial 8 week fixation with micromotion less than 150µm is crucial to their survivorship1 to avoid loosening2. Test methods by Davignon et al3 for micromotion were used to assess fixation of the MAKO UKR Tritanium (MAKO) (Stryker, NJ) and the Oxford Cementless UKR (Biomet, IN). Data was analyzed to determine the activities of daily living (ADL) that generate the highest forces and displacements4, 5. Stair ascent with 3.2BW compressive posterior tibial load was identified to be an ADL which may cause the most micromotion5. Based on previous studies6, 10,000 cycles was set as the run-time. The AP and IE profiles were scaled back to 60% for the Oxford samples to prevent the congruent insert from dislocating. A four-axis test machine (MTS, MN) was used. The largest size UKRs were prepared per manufacturer's surgical technique. Baseplates were inserted into Sawbones (Pacific Research, WA) blocks1. Femoral components were cemented to arbors. The medial compartment was tested, and the lateral implants were attached to balance the loads. Five tests were conducted for each implant with a new Sawbones and insert for each test per the test method3. The ARAMIS System (GOM, Germany) was used to measure relative motion between the baseplate and the Sawbones at three anteromedial locations (Fig. 1). Peak-Peak (P-P) micromotion was calculated in the compressive and A/P directions. FEA studies replicating the most extreme static loading positions for MAKO micromotion were conducted to compare with the physical test results using ANSYS14.5 (ANSYS, PA).Introduction
Methods
Recent advances in 3D printing enable the use of custom patient-specific instruments to place drill guides and cutting slots for knee replacement surgery. However, such techniques limit the ability to intra-operatively adjust an implant plan based on soft-tissue tension and/or joint pathology observed in the operating room, e.g. cruciate ligament integrity. It is hypothesized that given the opportunity, a skilled surgeon will make intra-operative adjustments based on intra-operative information not captured by the hard tissue anatomy reconstructed from a pre-operative CT scan or standing x-ray. For example, tibiofemoral implant gaps measured intra-operatively are an indication of soft-tissue tension in the patient's knee, and may influence a surgeon to adjust implant position, orientation or size. This study investigates the frequency and magnitude of intra-operative adjustments from a single orthopedic surgeon during 38 unicondylar knee arthroplasty (UKA) cases. For each patient, a pre-operative plan was created based on the bony anatomy reconstructed from the pre-operative CT. This plan is analogous to a plan created with patient-specific cutting blocks or customized implants. With robotic technology that utilizes pre-operative imaging, intra-operative navigation and robotic execution, this “anatomic” plan can be fine-tuned and adjusted based on the soft tissue envelop measured intra-operatively. The relative positions of the femur and the tibia are measured intra-operatively under a valgus load (for medial UKA, varus load for lateral UKA) for each patient from extension to deep knee flexion and used to compute the predicted space between the implants (gaps) throughout flexion. The planned position, orientation and size of the components can then be adjusted to achieve an optimal dynamic ligament balance prior to any bony cuts. This is the plan that is then executed under robotic guidance. Intra-operative adjustments are defined as any size, position or orientation changes occurring intra-operatively to the pre-operative anatomic plan.Introduction
Methods
Bicompartmental knee arthroplasty (BKA) is an alternative to total knee arthroplasty (TKA) for degenerative joint disease when present in only two compartments. BKA spares the cruciate ligaments and preserves bone in the healthy compartment, possibly leading to better knee kinematics and clinical outcomes when compared to TKA. While BKA is a technically demanding procedure when performed with manual instrumentation, robotic assistance allows for accurate implant placement and soft tissue balancing of the joint. Robotic unicompartmental knee arthroplasty (UKA) has shown favorable clinical outcomes and survivorship at short term (2 year) follow up compared to manual UKA. The purpose of this study is to evaluate the short term functional outcomes and survivorship of patients undergoing robotically assisted BKA. 45 patients (48 knees) were identified in an initial and consecutive single surgeon series receiving robotically assisted BKA to correct disease in the medial and patellofemoral compartments. As part of an IRB approved study, every patient in the series was contacted at a minimum two year (±2 months) follow up and asked a series of questions to determine implant survivorship and functional outcomes (using the patient portion of the Knee Society Score). 9 patients were lost to follow up and 1 patient was deceased. 35 patients (38 knees) at a minimum two year follow up enrolled in the study for an enrollment rate of 79%. There are 22 male patients and 13 female patients; the average age at time of surgery is 67.0 ± 6.8 and the average BMI is 29.5 ± 4.6. Five patients in this series also qualified for a 5 year follow up assessment.INTRODUCTION
METHODS
Preoperative templating of femoral and tibial components can assist in choosing the appropriate implant size prior to TKA. While weight bearing long limb roentograms have been shown to provide benefit to the surgeon in assessing alignment, disease state, and previous pathology or trauma, their accuracy in size prediction is continually debated due to scaling factors and rotated views. Further, they represent a static time point, accounting for boney anatomy only. A perceived benefit of robotic-assisted surgery is the ability to pre-operatively select component sizes with greater accuracy based on 3D information, however, to allow for flexibility in refining based on additional data only available at the time of surgery. The purpose of this study was to determine the difference of pre-operative plans in size prediction of the tibia, femur, and polyethylene insert. Eighty four cases were enrolled at three centers as part of an Investigational Device Exemption to evaluate a robotic-assisted TKA. All patients had a CT scan as part of a pre-operative planning protocol. Scans were segmented and implant sizes predicted based on the patients boney morphology and an estimated 2mm cartilage presence. Additional information such as actual cartilage presence and soft tissue effects on balance and kinematics were recorded intra-operatively. Utilizing this additional information, surgical plans were fine tuned if necessary to achieve minimal insert thickness and balance. Data from the Preoperative CT plan sizing and final size were compared to determine the percentage of size and within one size accuracy.Introduction
Methods
Total knee arthroplasty (TKA) using conventional instrumentation has been shown to be a safe and effective way of treating end stage osteoarthritis by restoring function and alleviating pain. As robotic technology is developed to assist surgeons with intra-operative decision making such as joint balancing and component positioning, the safety of these advancements must be established. Furthermore, functional recovery and clinical outcomes should achieve comparable results to the gold standard of conventional instrumentation TKA. Eighty-seven subjects (89 knees) underwent robotic arm assisted TKA by one of three investigators as part of an FDA and IRB approved Investigational Device Exemption (IDE). To achieve the primary endpoint of intra-operative patient safety using a robotic arm assisted cutting tool, the investigators completed questionnaires to assess a series of complications related to soft tissue damage associated with conventional TKA. Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Knee Society Knee Scores (KSS) were collected pre-operatively and at three month follow-up.Introduction
Methods
Total knee arthroplasty (TKA) is a well established treatment option for patients with end stage osteoarthritis. Conventional TKA with manual instruments has been shown to be a cost effective and time efficient surgery. While robotic-assisted operative systems have been shown to have benefits in surgical accuracy, they have also been reported to have longer surgical times. The purpose of this work was to determine surgical time and learning curve for a novel robotic-assisted TKA platform. Eighty-five subjects underwent robotic-assisted TKA by one of three investigators as part of an FDA and IRB approved Investigational Device Exemption (IDE). All patients received a cruciate retaining total knee implant system. Intra-operative safety, Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Knee Society Scores (KSS) were collected pre-operatively and at three month follow-up. In addition, surgical times were collected as part of a TKA work flow. To identify activities related to surgical steps required for robotic procedures specific time stamps were determined from the system. Capture of the hip center to final bone cut was used to define case time and identify robotic learning curve. Descriptive statistics were used to analyze results.Introduction
Methods
Bi-compartmental knee arthroplasty (BKA) is an alternative to total knee arthroplasty (TKA) for degenerative joint disease when present in only two compartments. BKA spares the cruciate ligaments and preserves bone in the healthy compartment, possibly leading to better knee kinematics and clinical outcomes when compared to TKA. While BKA is a technically demanding procedure when performed with manual instrumentation, robotic assistance allows for accurate implant placement and soft tissue balancing of the joint. Robotic unicompartmental knee arthroplasty (UKA) has shown favourable clinical outcomes and survivorship at short term (2 year) follow up compared to manual UKA. The purpose of this study is to evaluate the short term functional outcomes and survivorship of patients undergoing robotically assisted BKA. 45 patients (48 knees) were identified in an initial and consecutive single surgeon series receiving robotically assisted BKA to correct disease in the medial and patellofemoral compartments. As part of an IRB approved study, every patient in the series was contacted at a minimum two year (±2 months) follow up and asked a series of questions to determine implant survivorship and functional outcomes (using the patient portion of the Knee Society Score). 9 patients were lost to follow up and 1 patient was deceased. 35 patients (38 knees) at a minimum two year follow up enrolled in the study for an enrolment rate of 79%. There are 22 male patients and 13 female patients; the average age at time of surgery is 67.0 ± 6.8 and the average BMI is 29.5 ± 4.6. Five patients in this series also qualified for a 5 year follow up assessment.Introduction
Methods
Isolated lateral compartment osteoarthritis (OA) occurs in 5–10% of knees with OA [1, 2]. Lateral unicompartmental knee arthroplasty (LUKA) emerged as a treatment to this disease in the early 80s but challenging surgical technique has limited the prevalence of this treatment option [1–3]. A robotic-arm assisted surgical technique (MAKO Surgical Corp.) has emerged as a way to achieve precise implant positioning which can potentially improve surgical outcomes. The purpose of this study was to evaluate short term outcomes for patients that received LUKA using a novel robotic-arm assisted surgical technique.Introduction
Objectives
High BMI has been classically regarded as a contraindication for unicompartmental knee arthroplasty (UKA) as it can potentially lead to poor clinical outcomes and a higher risk of failure. In recent years, UKA has increased in popularity and, as a result, patient selection criteria are beginning to broaden. However, UKA performed manually continues to be technically challenging and surgical technique errors may result in suboptimal implant positioning. UKA performed with robotic assistance has been shown to improve component positioning, overall limb alignment, and ligament balancing, resulting in overall improved clinical outcomes. The purpose of this study is to examine the effect of high BMI in patients receiving UKA with robotic assistance. 1007 patients (1135 knees) were identified in an initial and consecutive multi-surgeon multi-center series receiving robotically assisted medial UKA, with a fixed bearing metal backed onlay tibial component. As part of an IRB approved study, every patient in the series was contacted at a minimum two year (±2 months) follow up and asked a series of questions to determine implant survivorship and satisfaction. 160 patients were lost to follow up, 35 patients declined to participate, and 15 patients were deceased. 797 patients (909 knees) at a minimum two year follow up enrolled in the study for an enrollment rate of 80%. 45% of the patients were female. The average age at time of surgery was 69.0 ± 9.5 (range: 39–93). BMI data was available for 887 knees; the average BMI at time of surgery was 29.4 ± 4.9. Patients were stratified in to five categories based on their BMI: normal (< 25; 16%), overweight (25–30; 46%), obese class I (30–35; 25%), obese class II (35–40; 11%) and obese class III (>40; 2%).Introduction
Methods
Bicompartmental knee arthroplasty (BKA) is an alternative to total knee arthroplasty (TKA) for degenerative joint disease when present in only two compartments. BKA spares the cruciate ligaments and preserves bone in the healthy compartment, possibly leading to better knee kinematics and clinical outcomes when compared to TKA. While BKA is a technically demanding procedure when performed with manual instrumentation, robotic assistance allows for accurate implant placement and soft tissue balancing of the joint. Robotic unicompartmental knee arthroplasty (UKA) has shown favorable clinical outcomes and survivorship at short term (2 year) follow up compared to manual UKA. The purpose of this study is to evaluate the short term functional outcomes and survivorship of patients undergoing robotically assisted BKA. 45 patients (48 knees) were identified in an initial and consecutive single surgeon series receiving robotically assisted BKA to correct disease in the medial and patellofemoral compartments. As part of an IRB approved study, every patient in the series was contacted at a minimum two year (±2 months) follow up and asked a series of questions to determine implant survivorship and functional outcomes (using the patient portion of the Knee Society Score). 9 patients were lost to follow up and 1 patient was deceased. 35 patients (38 knees) at a minimum two year follow up enrolled in the study for an enrollment rate of 79%. There are 22 male patients and 13 female patients; the average age at time of surgery is 67.0 ± 6.8 and the average BMI is 29.5 ± 4.6. Five patients in this series also qualified for a 5 year follow up assessment.INTRODUCTION
METHODS
Component positioning in total hip arthroplasty (THA) is critical to achieve optimal patient outcomes. Recent literature has shown acetabular component positioning may be inaccurate using traditional techniques. Robotic-assisted THA is a recent platform introduced to decrease the risk of malpositioned components. However, to date, a paucity of data is available comparing the intra-operative component position generated by the navigation system to post-operative radiographs. The purpose of this study was to compare the component position measurements of a navigation system, used during robotic-assisted THA, to component position measurements obtained on post-operative radiographs.Background
Purpose
Unicompartmental Knee Arthroplasty (UKA) has been offered as a tissue sparing alternative to total knee arthroplasty (TKA) for treatment of early to mid-stage osteoarthritis (OA). While the spared tissue and retention of cruciate ligaments may result in faster recovery, smaller incision, less bone resection, decreased pain and blood loss and more normal kinematics and function, UKA has shown unpredictable results in practice, which may be due to variations in surgical techniques1. Recently a robotic-assisted technique has been introduced as a means to provide more consistent and reproducible surgical results. In this study, the early return to function was measured to determine proposed benefits between UKA and TKA. Patients requiring either UKA or TKA were prospectively enrolled in this IRB approved study. Each patient received pre-operative education regarding their expected physical therapy (PT) regimen, which was uniform for all patients. PT was determined to be concluded when each patient reached an achievable functional endpoint with each of the following 5 criteria: range of motion from 5 to 115 degrees, recovery of flexion and extension strength to 4/5 of pre-operative strength, gait with minimal limp and without an assistive device for 250 feet and ability to ascend and descend a flight of stairs with step over gait and good control. The number of PT visits to reach each functional goal was recorded.Introduction
Methods
Several recent reports have documented high frequency of malpositioned acetabular components, even amongst high volume arthroplasty surgeons. Robotic assisted total hip arthroplasty (THA) has the potential to improve component positioning; however, to our knowledge there are no reports examining the learning curve during the adoption of robotic assisted THA. The purpose of this study was to examine the learning curve of robotic assisted THA as measured by component position, operative time, intra-operative technical problems, and complications.Background
Purpose
Component malposition in total hip arthroplasty (THA) contributes to wear, dislocation, and leg length discrepancy (LLD). Robotic assisted total hip arthroplasty (rTHA) utilises computer-assisted haptically guided bone preparation and implant insertion to improve accuracy. The goal of this study is to compare accuracy and clinical outcome with manual THA (mTHA) and rTHA at minimum 1 year follow-up interval. Consecutive primary THA performed by one fellowship trained surgeon included: the first 100 mTHAs in his clinical practice (Group1- year 2000), the last 100 mTHAs before rTHA use (Group2- year 2010), and the first 100 rTHA (Group3- year 2011). All THAs utilised cementless implants, cross-linked polyethylene, and a posterior approach. Comparisons included age, sex, diagnosis, implant head size, blood loss (EBL), operative time, LLD, early dislocation and infection. Acetabular abduction (AAB), anteversion (AAV), and LLD were measured using validated software (Martell Hip Analysis Suite). The Lewinnek safe zone defined accuracy (AAB- 30°-50°, AAV- 5°-25°). Statistical analysis included ANOVA, Chi squared, and Fisher tests. Power analysis demonstrated adequate sample sizes. No differences were noted regarding group demographics. Average operative times varied: Group 1, 2, and 3- (160, 129, and 143 minutes, respectively). No deep infections occurred in any group. LLD greater than 1.5 cm varied: Groups 1, 2, and 3 (9%, 1%, 1%, respectively). Dislocation rates varied: Groups 1, 2, and 3- (5%, 3%, and 0%, respectively). EBL was less with rTHA than mTHA (Groups 1, 2, 3: 533cc, 437cc, 357cc, respectively). Average implant head size increased comparing Groups 1, 2, and 3 (31mm, 34.6mm, and 35.2mm, respectively). AAB accuracy varied: Groups 1, 2, and 3 (66%, 91%, and 98%, respectively). AAB greater than 55 degrees varied: Groups 1, 2, and 3 (15%, 1%, and 0%, respectively). There was a 3% fractured acetabular liner rate in Group 1, all cases occurred with AAB > 55 degrees, and AAB greater than 55 degrees correlated with increased acetabular liner fracture rate (20% vs. 0%, P < 0.05). No cases of fractured acetabular liners occurred in Group 2 or 3. rTHA improved AAV accuracy compared with mTHA (Group 2- 48%, Group 3- 75%; p<0.0001). Improved acetabular component accuracy with rTHA correlated with lower dislocation rates compared with mTHA (p<0.001). Total hip arthroplasty performed with traditional manual techniques has demonstrated excellent clinical outcomes in the majority of patients with many THA designs if components are placed accurately. Limitations in mTHA remain that alter results if accurate component placement is not achieved. In our study, clinical experience over 10 years improved AAB accuracy with mTHA, but AAV remained problematic. rTHA improved AAB and AAV accuracy compared with mTHA and demonstrated reduced early dislocation rates, improved rate of LLD, and reduced acetabular liner fracture risk compared with mTHA (p<0.05). Average rTHA operative times were 14 minutes longer than mTHA (Group 2), but this was not associated with increased EBL or infection rates. Further study is needed to evaluate whether the short term clinical and radiographic advantages noted with rTHA compared with mTHA will be maintained at longer follow up intervals.
Successful clinical outcomes following unicompartmental knee arthroplasty (UKA) depend on component positioning, soft tissue balance and overall limb alignment which can be difficult to achieve using manual instrumentation. Recently, robotically guided technology has been used to improve post-operative implant positioning, and limb alignment in UKA with the expectation that this will result in greater implant longevity. This multi-center study examines the survivorship of this robotically guided procedure coupled with a novel, anatomically designed UKA implant at two years follow up. This study examines the two year survivorship and patient satisfaction of an anatomically designed UKA implant using a new robotically guided technology that has been shown to improve implant positioning and alignment.INTRODUCTION
OBJECTIVES
