Studies have shown that as many as 1 in 5 patients is dissatisfied following total knee replacement (TKA). There has also been a large reported disparity between surgeon and patient perception of clinical “success”. It has long been shown that surgeon opinion of procedural outcomes is inflated when compared with patient-reported outcomes. Additionally, TKA recipients have consistently reported higher pain levels, greater inhibition of function, and lower satisfaction than total hip replacement (THA) recipients. It is imperative that alternative methods be explored to improve TKA patient satisfaction. Therefore, the purpose of this study was to determine whether or not patients with a balanced TKA, as measured using intraoperative sensors, exhibit better clinical outcomes. 310 patients scheduled for TKA surgery were enrolled in a 6 center, randomized controlled trial, resulting in two patient groups: a sensor-guided TKA group and a surgeon-guided TKA group. Intraoperative load sensors were utilized in all cases, however in one group the surgeon used the feedback to assist in balancing the knee and in the other group the surgeon balanced without load data and the sensor was used to blindly record the joint balance. For this evaluation, the two groups were pooled and categorized as either balanced or unbalanced, as defined by a mediolateral load differential less than 15 lbf (previously described in literature). Clinical outcomes data were collected at 6 weeks, 6 months and 1 year post- operatively, including Knee Society Satisfaction and the Forgotten Joint Score. Using linear mixed models, these outcome measures were compared between the balanced and unbalanced patient groups.Introduction & Aims
Methods
The traditional method of soft-tissue balancing during TKA is subjective in nature, and stiffness and instability are common indications for revision, suggesting that TKA balancing by subjective assessment is suboptimal. This study examines the intraoperative mediolateral loads measured with a nanosensor-enabled tibial insert trial and the sequential balancing steps used to achieve quantitative balance. Data obtained from a prospective multicenter study was assessed to determine the effect of targeted ligament release on intra-articular loading, and to understand which types of releases are necessary to achieve quantified ligament balance. A group of 129 patients received sensor-assisted TKA, as part of a prospective multicenter study. Medial and lateral loading data were collected pre-release, during any sequential releases, and post-release. All data were collected at 10, 45, and 90 degrees during range of motion testing. Ligament release type, release technique type, and resultant loading were collected.Introduction & Aims
Methods
Total knee arthroplasty (TKA) is currently one of the most common elective surgical procedures in the United States. The increase in the proportion of younger patients in receipt of surgery, in concert with a dramatic rise in the incidence of obesity, has contributed to the on-going, exponential increase in the number of arthroplasties performed annually. Despite materials advances for implants, the U.S. revision burden has remained static for the last decade. According to the 2013 CMS MEDPAR file the typical CMS reimbursement falls far short of costs incurred by the hospital, resulting in an average net loss of revenue of $9,539; and over 90% of hospitals lose money for every revision case performed. Today, approximately 5% of all primaries performed will result in an early revision (< 3 years). In order to understand ways with which to mitigate the incidence of early revision due to mechanical complications, a multicentric group of sensor-assisted patients was follow-up out to 3 years. In this study, 278 sensor-assisted patients were followed out to 3 years. The intraoperative devices used in this study contain microsensors and a processing unit. Kinetic and center of load location data are projected, in real-time, to a screen. Because of the wireless nature of the intraoperative sensors, the patella can be reduced, and kinematic data can be evaluated through the range of motion. For each patient, the soft-tissue envelope was balanced to within a mediolateral differential of 15 lbf., through the ROM, as per the suggestion of previously reported literature. The average patient profile indicates: age = 69.7 years, BMI = 30.4, gender distribution = 36% male/64% female. Any adverse event within the 3-year follow-up interval was captured. By 3 years, 1 patient in this population has required revision surgeon due to mechanical complicatons. Overall adverse events included: pain in hip (3), pain in contralateral knee (2), wound drainage (3), DVT (1), death (1), stiffness in operative knee (2), infection (3), global pain (2), back pain (2). Based on the average reported number of early revisions that occur in the U.S. (5% of primaries), it was anticipated for this patient group to require approximately 13 revisions by the 3-year follow-up interval. Using 2013 CMS MEDPAR data, these 13 revisions would have resulted in $124,007 cost-to-hospital. However, only 1 revision (0.4%) was observered, therefore $114,468 in additional costs were spared for the aggregate of participating hospitals. This data suggests that the incorporation of kinetic sensors in TKA may assist the surgeon in achieving soft-tissue balance and thereby avoiding adverse mechanical complications that require surgical intervention.
Total knee arthroplasty (TKA) patients are consistently reported to be less satisfied than total hip arthroplasty (THA) patients. A patient's perception of success of his/her own total knee is dictated by their levels of post-operative pain and function, and many return to follow-up visits with inexplicable pain and stiffness that contradict favorable radiographic results. Several of these chief complaints that contribute to dissatisfaction are associated with soft-tissue imbalance. Therefore, in an effort to thoroughly understand the post-operative impact of soft-tissue balance on satisfaction, a multicenter study was conducted to evaluate the satisfaction outcomes of quantifiably balanced patients. In this study, 102 sensor-assisted patients were followed out to 3 years. The intraoperative devices used in this study project kinetic loading (lbf.) and center of load location data, in real-time, to a screen. Because of the wireless nature of the intraoperative sensors, the patella can be reduced, and kinematic data can be evaluated through the range of motion. The target balance window that was used in this study has been previously reported in literature and includes: 1) a mediolateral differential of 15 lbf., through the ROM, and 2) Sagittal plane stability as determined by a posterior drawer analysis. A robust, face-validated satisfaction survey was administered at 3-year follow-up and included 7 questions with answers on a 5-point Likert scale. At 3 years, post-operatively, 97.2% of this patient group reported being “satisfied” to “very satisfied” with their procedure, in comparison to the 81% average TKA satisfaction reported in literature (df = 11). The comparative literature included annual satisfaction intervals from 1 to 5 years (n = 33,775) which is comparable to the interval reported in this patient group. The sensor-assisted patient group exhibited a 16% increase in the proportion of satisfaction over what is currently reported in the comparative literature (p = 0.001). Despite the success rate of TKA, unfavorable patient-reported satisfaction continues to present a problem for operative recipients and surgeons. Because satisfaction is dependent upon several variables – including pain, function, and activity levels – the satisfaction survey used in this study represents a more accurate account of patient perception than many traditional surveys. It was shown that sensor-balanced TKA patients exhibited a 16% increase in the proportion of those reporting being “satisfied” to “very satisfied”, over the average satisfaction reported in literature. Allowing the surgeon to quantitatively balance the soft-tissue envelope, dynamically, has continued to a significant decrease in the proportion of dissatisfaction.
Instability after total knee arthroplasty (TKA) represents, in excess of, 7% of reasons for implant failure. This mode of failure is correlated with soft-tissue imbalance, and has continued to be problematic despite advances in implant technology. Thus, understanding the options available to execute safe and effective soft-tissue release is critical to mitigating future complications due to instability. This study aimed to use intraoperative sensors to evaluate a multiple needle puncturing technique (MNPT), in comparison with traditional transection-based release, to determine its biomechanical and clinical efficacy. Seventy-five consecutive, cruciate-retaining TKAs were performed, as part of an 8-site multicenter study. All procedures were performed with the use of an intraoperative sensor to ensure quantitative balance, as per previously reported literature. Of the 75-patient cohort, 50 patients were balanced with the MNPT; 20 patients were balanced with traditional transection. All patients were followed out to 1-year, and administered KSS, WOMAC, and satisfaction. Alignment and ROM was captured for all patients, pre-operatively and at the 1-year follow-up interval.Introduction
Methods
Achieving balance in TKA is critical in assuring favorable outcomes. But, in order to achieve quantifiably balanced loading values, is it more advantageous to make bony corrections or release soft-tissue? The answer to this question will be paramount in evaluating the most appropriate surgical techniques for use with new dynamic technology, thereby maximizing favorable clinical outcomes. Therefore, the purpose of this investigation was to evaluate a possible quantitative loading threshold, using intraoperative sensors, which may dictate surgical correction of bone versus soft-tissue release. A retrospective analysis of 122 multicenter patients, in receipt of sensor-assisted primary TKA, was conducted. 40 lbs. was used as a threshold, above which bone was corrected; below which soft-tissue was corrected. All patients were categorized in to the following groups: Group A – candidates for bony correction, but received soft-tissue correction; Group B – candidates for soft-tissue/receiving soft-tissue; Group C – candidates for bony correction/receiving bony correction.INTRODUCTION
METHODS
Patient-reported satisfaction is a critical measure in understanding the clinical success of total knee arthroplasty. Yet, satisfaction levels in TKA patients are generally lower than THA patients; and surgeon-patient agreeability regarding clinical success is typically in discordance. Thus, the purpose of this evaluation was to report on the one-year satisfaction data of a group of sensor-assisted TKA patients, and compare that data to the average satisfaction reported in literature, as measured by a meta-analysis. One hundred and thirty five patients received TKA utilizing intra-operative sensing technology to evaluate soft-tissue balance as part of a prospective multicenter study. Patients were classified by two groups: “balanced” and “unbalanced”. Quantitative “balance” was defined as a mediolateral intercompartmental loading difference of ≤ 15 pounds; all loading exceeding 15 pounds was classified as “unbalanced”. At the one-year follow-up visit, a 7-question patient satisfaction survey was administered. The answering schema of this survey was modeled using a modified five-point Likert scale, ranging from “True” to “False” (or “Very Satisfied” to “Very Dissatisfied,” where appropriate). A meta-analysis of literature was performed and studies selected for inclusion in this analysis were required to meet the following criteria: all patients were in receipt of a primary TKA; satisfaction data was collected post-operatively; and the proportion of patients who were “satisfied” to “very satisfied” was statistically described.INTRODUCTION
METHODS
The cost associated with the TKA revision burden is projected to reach 13 billion dollars, annually. Complications reported by post-TKA patients include: pain (44%, multilocational), sensation of instability (21% reason for revision), and joint stiffness (17% reason for revision); problems that may be attributed to soft-tissue imbalance. One of the possible reasons for the substantial prevalence of such complications is the subjectivity associated with defining soft-tissue balance. A priority must be placed on developing new objective methods with which to avoid costly post-operative complications, including the integration of intraoperative sensing technology. The purpose of this evaluation was to report on the disparity between the patient-reported outcomes scores of quantitatively balanced versus unbalanced patients, at 1-year, using a group of 135 multicenter patients. 135 prospective patients, from 8 U.S. sites, have had primary TKA performed with the use of intraoperative sensors. Patients were classified by two groups: “balanced” and “unbalanced”. Quantitative “balance” was defined as a mediolateral intercompartmental loading difference of ≤ 15 pounds; all loading exceeding 15 pounds was classified as “unbalanced”. For all patients, the following kinematic data was captured: varus/valgus stability, anteroposterior stability, flexion contracture (if any), extension lag (if any), anatomic alignment, and ROM. Also at each clinical follow-up visit, activity levels and two patient-reported outcomes measures were administered, including: the American Knee Society Score (KSS), and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC).INTRODUCTION
METHODS
During primary total knee arthroplasty, the surgeon may encounter excessive medial collateral ligament tension while addressing a varus knee. This may be due to medial ligament/capsular complex contractures, and/or, due to the creation of a 0 degree mechanical axis in a varus knee. This tension leads to increased loading in the medial compartment, which contributes to an unbalanced extension and flexion gap. If uncorrected, this imbalance can lead to unfavorable clinical outcomes, including: pain, accelerated polyethylene degradation, joint instability, and limited ROM. Currently, intercompartmental soft-tissue balance is obtained by a subjective surgeon's “feel”. However, this method of judging soft-tissue tension is both variable and unreliable. Most surgeons can detect gross instability, but judging ligament tension is difficult. The following technique describes the integration of intraoperative microelectronic tibial inserts to assess and modify ligament tension, utilizing real-time dynamic sensor feedback 500 TKAs were performed between September 2012 and April 2013, by three collaborating surgeons. All surgeons used the same implant system, compatible with an embedded microelectronic tibial insert with which to receive real-time feedback of femoral contact points and joint kinetics. Intraoperative kinematic data, displayed loading patterns consistent with identifiable intercompartmental imbalance through a full ROM. All mediolateral imbalance, secondary to an excessively tight medial compartment, was addressed with the technique described herein.Introduction
Methods
Flexion instability of the knee accounts for, up to, 22% of reported revisions following TKA. It can present in the early post-operative phase or present— secondary to a rupture of the PCL— in the late post-operative phase. While most reports of instability occur in conjunction with cruciate retaining implants, instability in a posterior-stabilized knee is not uncommon. Due to the prevalence of revision due to instability, the purpose of constructing the following techniques is to utilize intraoperative sensors to quantify flexion gap stability. 500 posterior cruciate-retaining TKAs were performed between September 2012 and April 2013, by four collaborating surgeons. All surgeons used the same implant system, compatible with a microelectronic tibial insert with which to receive real-time feedback of femoral contact points and joint kinetics. Intraoperative kinematic data, as reported on-screen by the VERASENSE™ knee application, displayed similar loading patterns consistent with identifiable sagittal plane abnormalities. These abnormalities were classified as: “Balanced Flexion Gap,” “Flexion Instability” and “Tight Flexion Gap.” All abnormalities were addressed with the techniques described herein.Introduction
Methods
Proper soft-tissue balance is important for achieving favorable clinical outcomes following TKA, as ligament imbalance can lead to pain, stiffness or instability, accelerated polyethylene wear, and premature failure of implants. Until recently, soft-tissue balancing was accomplished by subjective surgeon feel and by use of static spacer blocks. Now, nanonsensor-embedded implant trials allow surgeons to quantify peak load and center of load in the medial and lateral compartments during the procedure, and to adjust ligament tension and implant positioning accordingly. The purpose of this 3-year, multicenter study is to evaluate 500 patients who have received primary TKA with the use of intraoperative sensors in order to correlate quantified ligament balance to clinical outcomes. To date, 7 centers have contributed 215 patients who have undergone primary TKA with the use of intraoperative sensors. Patients are seen at a pre-operative visit (within 3 months prior to surgery), and post-operatively at 6 weeks, 6 months, and at 1, 2, and 3-year anniversaries. Standard demographic and surgical data is collected for each patient, including: age at time of surgery, BMI, operative side, gender, race, and primary diagnosis. At each interval, anatomic alignment and range of motion are assessed; KSS and WOMAC evaluations are administered; and a set of standard radiographs is collected, including: standing anteroposterior, standing-lateral, and the sunrise patellar view. Intraoperative loads were recorded for pre- and post-release joint states. All soft-tissue release techniques were recorded. “Optimal” soft-tissue balance was defined as a medial-lateral load difference of less than or equal to 15 lbs.Introduction
Methods
