Measured outcomes from knee joint arthroplasty (TKA) have primarily focused on surgeon-directed criteria, such as alignment, range of motion measured in the clinic, and implant durability, rather than on functional outcomes. There is strong evidence that subjective reporting by patients fails to capture objective real-life function.1,2 We believe that the recent emphasis on clinical outcomes desired by the patient, as well as the need to demonstrate value, requires a new approach to patient outcomes that directly monitors ambulatory activity after surgery. We have developed and tested a system that: 1) autonomously identifies patients who are not progressing well in their recovery from TKA surgery; 2) characterizes patient activity profiles; 3) automatically alerts health care providers of patients who should be seen for additional follow-up. We anticipate that such a system could decrease secondary procedures such as manipulation under anesthesia (MUA) and reduce hospital re-admission rates thereby resulting in significant cost savings to the patient, the care providers, and insurers. The components of the system include: 1) A sensor package that is mounted correctly in relation to the knee joint (Figure 1a) and is suitable for long term use; 2) An application that runs under the Android operating system to communicate with the sensor and to gather subjective information (pain, satisfaction, perceived stability etc. together with a photograph of the surgical site (Figure 1b); 3) Software to upload the data from the phone to a remote server; 4) An analysis and reporting package that generates, among other metrics, a profile describing the patient's activity throughout the day, trends in the recovery process, and alerts for abnormal findings (Figure 1c). The system was pilot tested on 12 patients (7 females) who underwent TKA. Complete days of data collection were scheduled for each patient every two weeks until 12 weeks, starting during the second week after surgery.Introduction
Methods
Excellent reconstruction of bone will be described induced by a synthetic biomaterial without a calcium phosphate mineral phase or growth factors, and with a pore size of 35 m. The material is fabricated by a process called sphere-templating and it can be made from many synthetic materials including hydrogels, silicones, polyurethanes and glasses. All pores are identical in size and interconnected. Studies from our group have shown optimal healing in soft tissue (as suggested by extensive vascularity and minimal fibrosis) for spherical pores of 30–40 m size. Sphere-templated hydrogel implants in bone were performed using the following procedure: Under appropriate anesthesia, 18–24month old NZW rabbits underwent medial parapatellar arthrotomy, with exposure of the medial femoral condyle. A 3.5 mm end-cutting drill, locked in a rigid armature, was used to create a host graft site at the center of the articular cartilage lesion, with depth of cut matched to the sphere-templated construct thickness of 2 mm. Animals were sacrificed at one day, 28 days, and 12 weeks. After sacrifice, the femora were isolated and the condyles dissected. Condyles were fixed in 4% paraformaldehyde at 4°C for 48 hrs, decalcified in Immunocal for 14 days at 4°C and paraffin embedded. Specimens were sectioned to a thickness and stained with Safranin- O/Fast Green, hematoxylin/eosin or Masson's trichrome. Prior to decalcification, selected samples were evaluated by micro-CT utilising a Skyscan 1076 microCT low dose in-vivo X-ray scanner, slice imaging and 3D image reconstruction. Both histologically, and with micro-CT imaging, excellent tissue and mineral reconstruction was observed in the sphere templated material. The contralateral control, drilled but without implant, showed essentially no reconstruction. Since the classical paradigm for bone reconstruction requires either autologous bone, cadaver bone, or calcium phosphate scaffolds with pores >150 microns, the healing observed here suggests new avenues for bone regeneration.
Two-stage revisions for the infected THA are associated with lower re-infection rates than directexchange (one-stage) revisions, and for this reason are favored in the U.S. However, the twostage approach may result in increased, but poorly quantified, surgical morbidity. We developed a decision analysis to compare direct-exchange revision to the two-stage approach for treating the infected THA. We performed a systematic literature search for papers that analyzed direct-and two-stage revisions for the treatment of chronic infections after THA, with a >
2 years follow-up. This provided frequencies of the most common postoperative (interim and final) health states. These were converted to monthly probabilities to permit decision analysis. We conducted and previously published two surveys to obtain utility values, one in experienced arthroplasty surgeons and another in patients. Using those probabilities and utilities, we created a Markov cohort modeling the postoperative health states seen during treatment of the infected THA. Sensitivity analysis was performed for each variable in the tree to verify the models robustness. Using a 12-month cycle, the Markov model favored direct-exchange revision over the twostage approach, regardless of whether surgeon-or patient-derived utilities were used (0.941 vs. 0.642 expected value (EV), and 0.889 vs. 0.551 EV, for patient-and surgeon-derived utilities, respectively; p<
0.01). These findings were also significant in a lifetime model with a ten-year life expectancy (p<
0.01). The findings were robust in sensitivity analyses using a clinically salient range of input variables. This decision analysis, which used a systematic review of the literature (for complication and outcome frequencies) and published study-specific survey data from patients and experienced surgeons (for utility values of those health states) found direct-exchange arthroplasty to be superior to the two-stage revision for treating the infected THA. This finding was unexpected, in that this is not our typical approach nor is it favored in this country.