Background. Periprosthetic infections remain a devastating problem in the field of joint arthroplasty. In the following study, the results of a two-stage treatment protocol for chronic periprosthetic infections using an intraoperatively molded cement prosthesis-like spacer (CPLS) are presented. Methods. Seventy-five patients with chronically infected knee prosthesis received a two-stage revision procedure with the newly developed CPLS between June 2006 and June 2011. Based on the microorganism involved, patients were grouped into either easy to treat (ETT) or difficult to treat (DTT) and treated accordingly. Range of motion (ROM) and the knee society score (KSS) were utilized for functional assessment. Results. Mean duration of the CPLS implant in the DTT group was 3.6 months (range 3–5 months) and in the ETT group 1.3 months (range 0.7–2.5 months). Reinfection rates of the final prosthesis were 9.6% in the ETT and 8.3% in the DTT group with no significant difference between both groups regarding ROM or KSS (P = 0.87, 0.64, resp.). Conclusion. The results show that ETT patients do not necessitate the same treatment protocol as DTT patients to achieve the same goal, emphasizing the need to differentiate between therapeutic regimes. We also highlight the feasibility of CLPS in two-stage protocols.
In this paper, we describe the design of an interactive glove, 'Teleglove' in order to investigate new ways of crafting and interacting with mobile applications through wearable technology. The system we designed was a simple control to answer a call, end a call and make it silent by just pressing two fingers of the glove, grounded in basic interaction challenges with touch screens using ordinary gloves. The glove was built quickly using newly available small-scale sensor board and connects to a smartphone via the ANT+ protocol. The robust and simple interaction with the application using the glove suggests many opportunities for practices of crafting similar systems on a broader scale.
The accurate positioning of the prosthetic components is essential for achieving successful results in medial unicompartmental knee arthroplasty (mUKA). The tibial component rotation in image-based robotic-assisted UKA is usually based on tibial bony landmarks matched to the pre-operative CT model. The study aimed to evaluate whether setting the tibial rotation on femoral CT-based landmarks allows congruent knee kinematics. We retrospectively analyzed data from 210 consecutive image-based robotic-assisted mUKA cases. In every case, we set the tibia rotation landmark parallel to the posterior condylar axis and centered it on the trochlea groove defined on the preoperative CT scan. The implant positioning was primarily set parallel to this rotation landmark and then adjusted based on tibial sizes avoiding component over- or under-hang. During surgery, we recorded the knee kinematics under valgus stress to reduce the arthritic deformity. A femoral-tibial contact point was recorded over the entire range of motion and displayed as a tracking profile on the tibia implant. The femoro-tibial tracking angle (FTTA) was then calculated based on a tangent line to the femoro-tibial tracking-points and the difference to the femur-based rotation landmark. In 48% of the cases, we could position the tibia component exactly to the femoral rotation landmark, whereas in 52% of cases, minimal adjustments were made to avoid component’s under- or over-hang. The mean tibia component rotation (TRA) with reference to our femur-based landmark was +0.24° (SD ± 2.9°). The femur-based tibia rotation landmark showed a high correspondence to the FTTA with 60% of the cases having less than 1° of deviation. Mean FTTA was +0.7° (SD ± 2.2°). The mean difference between the absolute value of the TRA and the FTTA (|TRA| − |FTTA|) was −0.18° (SD ± 2°). Setting the tibial component rotation based on CT scan femoral landmarks and not on tibial anatomical landmarks is a reliable method to obtain congruent knee kinematics during image-based robotic-assisted medial UKA with less the 2° deviations on average.
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