Porous metaphyseal cones can be used for fixation in revision total knee arthroplasty (rTKA) and complex TKAs. This metaphyseal fixation has led to some surgeons using shorter cemented stems instead of diaphyseal engaging cementless stems with a potential benefit of ease of obtaining proper alignment without being beholden to the diaphysis. The purpose of this study was to evaluate short term clinical and radiographic outcomes of a series of TKA cases performed using 3D-printed metaphyseal cones. A retrospective review of 86 rTKAs and nine complex primary TKAs, with an average age of 63.2 years (SD 8.2) and BMI of 34.0 kg/m2 (SD 8.7), in which metaphyseal cones were used for both femoral and tibial fixation were compared for their knee alignment based on the type of stem used. Overall, 22 knees had cementless stems on both sides, 52 had cemented stems on both sides, and 15 had mixed stems. Postoperative long-standing radiographs were evaluated for coronal and sagittal plane alignment. Adjusted logistic regression models were run to assess malalignment hip-knee-ankle (HKA) alignment beyond ± 3° and sagittal alignment of the tibial and femoral components ± 3° by stem type.Aims
Methods
Porous metaphyseal cones are increasingly used for fixation in revision total knee arthroplasty (RTKA). Both cemented shorter length stems and longer diaphyseal engaging stems are currently utilized with metaphyseal cones with no clear evidence of superiority. The purpose of this study was to evaluate our experience with 3D printed titanium metaphyseal cones with both short cemented and longer cementless stems from a clinical and radiographic perspective. In total 136 3D printed titanium metaphyseal cones were implanted. The mean patient age was 63 and 48% were female. The mean BMI was 33 and the mean ASA class was 2.5. There were 42 femoral cones in which 28 cemented and 14 cementless stems were utilized. There were 94 tibial cones in which 67 cemented and 27 cementless stems were utilized. The choice for stem fixation was surgeon dependent and in general cones were utilized for AORI type 2 and 3 bone defects on the femur and tibia. The most common fixation scenario was short cemented stems on both the femur and tibia followed by cemented stem fixation on the tibia and cementless fixation on the femur. Clinical data such as revision, complication, and PRO was collected at last follow-up (minimum follow-up 1 year). Radiographic analysis included cone bony ingrowth and coronal and sagittal alignment on long-standing radiographs. Descriptive statistics were used to compare demographics between patients who had malalignment (HKA beyond +/− 3 degrees and flexion/extension beyond +/− 3 degrees). Adjusted logistic regression models were run to assess malalignment risk by stem type.Introduction
Methods
Surgical management of PJI remains challenging with patients failing treatment despite the best efforts. An important question is whether these later failures reflect reinfection or the persistence of infection. Proponents of reinfection believe hosts are vulnerable to developing infection and new organisms emerge. The alternative hypothesis is that later failure is a result of an organism that was present in the joint but was not picked up by initial culture or was not a pathogen initially but became so under antibiotic pressure. This multicenter study explores the above dilemma. Utilizing next-generation sequencing (NGS), we hypothesize that failures after two stage exchange arthroplasty can be caused by an organism that was present at the time of initial surgery but not isolated by culture. This prospective study involving 15 institutions collected samples from 635 revision total hip (n=310) and knee (n=325) arthroplasties. Synovial fluid, tissue and swabs were obtained intraoperatively for NGS analysis. Patients were classified per 2018 Consensus definition of PJI. Treatment failure was defined as reoperation for infection that yielded positive cultures, during minimum 1-year follow-up. Concordance of the infecting pathogen cultured at failure with NGS analysis at initial revision was determined.Introduction
Methods
The Bundled Payments for Care Improvement (BPCI) initiative has identified pathways for improving the value of care. However, patient-specific modifiable and non-modifiable risk factors may increase costs beyond the target payment. We sought to identify risk factors for exceeding our institution’s target payment, the so-called ‘bundle busters’. Using our data warehouse and Centers for Medicare and Medicaid Services (CMS) data we identified all 412 patients who underwent total joint arthroplasty and qualified for our institution’s BPCI model, between July 2015 and May 2017. Episodes where CMS payments exceeded the target payment were considered ‘busters’ (n = 123). Risk ratios (RRs) were calculated using a modified Poisson regression analysis.Aims
Patients and Methods
Recent studies of novel healthcare episode payment models, such as the Bundled Payments for Care Improvement (BPCI) initiative, have demonstrated pathways for improving value. However, these models may not provide appropriate payments for patients with significant medical comorbidities or complications. The objective of this study was to identify risk factors for exceeding our institution's target payment, the so-called “bundle busters.” After receiving an exemption from the Institutional Review Board, we queried our institutional data warehouse for all patients (n=412) that underwent total joint arthroplasty (TJA) of the hip (n=192), knee (n=207), or ankle (n=13), and qualified for our institution's bundled payments model during the study time period (July 2015 – May 2017). Patients with medical conditions that were not well controlled or were potentially optimizable were all sent for preoperative medical optimization prior to surgery. For each 90-day episode, patient characteristics, medical comorbidities, perioperative data, and payments from the Centers for Medicare and Medicaid Services (CMS) were obtained. Episodes where Medicare payments exceeded the target payment were considered “busters”. The busters were older, and had higher comorbidity scores (all, p<0.01). Variables were summarized using descriptive statistics and risk ratios were calculated using a modified Poisson regression analysis.Introduction
Methods
