The purpose of this study was to determine if better outcomes occur with use of robotic-arm assistance by comparing consecutive series of non-robotic assisted (NR-TKA) and robotic-arm assisted (NR-TKA) total knee arthroplasties with the same implant. 80 NR-TKAs and then 101 RA-TKAs were performed consecutively. 70 knees in each group that had a minimum two-year follow-up were retrospectively reviewed. Range of motion, Knee Society (KS) scores, and forgotten joint scores (FJS) were compared using Mann-Whitney U tests. Tourniquets, used for all cases, had their inflation time recorded. Component realignment to minimize soft tissue releases was used in both groups with the goal to stay within a mechanical alignment of 3° of varus to 2° of valgus. The use of soft tissue releases for balance were compared.Introduction
Methods
The purpose of bundled payment programs is to reduce cost via risk sharing, while still maintaining quality. If savings are achieved under a historic target price, the orthopedic surgeon will receive a monetary bonus. If costs are higher, a portion is deducted from payment to the orthopedic surgeon. The purpose of this study was to evaluate our experience with the Bundled Payments for Care Improvement Program (BPCI) when run by an orthopedic surgeon group to determine patient safety and who benefited the most financially. This program ran from January 2015 through September 2018. 3,186 Medicare total hip and knee replacements, elective (DRG 470) and for fracture (DRG 469), performed by our group were included. 90 day hospital and all postoperative expenditures were reconciled against our historic cost. All patients were medically optimized with discharge plans established preoperatively. We developed preferred skilled nursing facilities and home health care agencies with synergistic medical providers so that discharges were recommended as soon as appropriate. We hired two full-time case managers to have direct contact with patients pre-and post-operatively. Waiver assistance such as house and pet sitters were used if necessary at our expense. 35% of savings went to the convener, who acted as a liaison between our group and CMS. Expenditures for the 90-day period for all patients were calculated to determine where savings occurred and which entity benefitted financially.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
Total knee replacement (TKR) smart tibial trials
have load-bearing sensors which will show quantitative compartment
pressure values and femoral-tibial tracking patterns. Without smart
trials, surgeons rely on feel and visual estimation of imbalance
to determine if the knee is optimally balanced. Corrective soft-tissue
releases are performed with minimal feedback as to what and how
much should be released. The smart tibial trials demonstrate graphically
where and how much imbalance is present, so that incremental releases
can be performed. The smart tibial trials now also incorporate accelerometers
which demonstrate the axial alignment. This now allows the surgeon
the option to perform a slight recut of the tibia or femur to provide
soft-tissue balance without performing soft-tissue releases. Using
a smart tibial trial to assist with soft-tissue releases or bone
re-cuts, improved patient outcomes have been demonstrated at one
year in a multicentre study of 135 patients (135 knees). Cite this article:
The aim of this prospective multicentre study
was to report the patient satisfaction after total knee replacement (TKR),
undertaken with the aid of intra-operative sensors, and to compare
these results with previous studies. A total of 135 patients undergoing
TKR were included in the study. The soft-tissue balance of each
TKR was quantified intra-operatively by the sensor, and 18 (13%)
were found to be unbalanced. A total of 113 patients (96.7%) in
the balanced group and 15 (82.1%) in the unbalanced group were satisfied
or very satisfied one year post-operatively (p = 0.043). A review of the literature identified no previous study with
a mean level of satisfaction that was greater than the reported
level of satisfaction of the balanced TKR group in this study. Ensuring
soft-tissue balance by using intra-operative sensors during TKR
may improve satisfaction. Cite this article:
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
