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The preoperative differentiation between septic and aseptic loosening after total hip or knee arthroplasty is essential for successful therapy and relies in part on biomarkers. The objective of this study was to assess synovial and serum levels of inflammatory proteins as diagnostic tool for periprosthetic joint infection and compare their accuracy with standard tests. 120 patients presenting with a painful knee or hip endoprosthesis for surgical revision were included in this prospective trial. Blood samples and samples of intraoperatively acquired joint fluid aspirate were collected. White blood cell count, C-reactive protein, procalcitonin and interleukin-6 were determined. The joint aspirate was analyzed for total leukocyte count and IL-6. The definite diagnosis of PJI was determined on the basis of purulent synovial fluid, histopathology and microbiology. IL-6 in serum showed significantly higher values in the PJI group as compared to aseptic loosening and control, with specificity at 58.3% and a sensitivity of 79.5% at a cut-off value of 2.6 pg/ml. With a cut-off >6.6 pg/ml, the specificity increased to 88.3%. IL-6 in joint aspirate had, at a cut-off of >2100 pg/ml, a specificity of 85.7% and sensitivity of 59.4%. At levels >9000 pg/ml, specificity was almost at 100% with sensitivity just below 50%, so PJI could be considered proven with IL-6 levels above this threshold. Our data supports the published results on IL-6 as a biomarker in PJI. In our large prospective cohort of revision arthroplasty patients, the use of IL-6 in synovial fluid appears to be a more accurate marker than either the white blood cell count or the C-reactive protein level in serum for the detection of periprosthetic joint infection. On the basis of the results we recommend the use of the synovial fluid biomarker IL-6 for the diagnosis of periprosthetic joint infection following total hip and knee arthroplasty.

SUMMARYBackground: About 1% of adults suffer from painful osteoarthritis of the ankle. The current literature contains no information on the percentage of such patients who derive long-term relief of symptoms from conservative treatment. Advanced ankle osteoarthritis can be treated with non-joint-preserving measures, such as total ankle replacement and ankle fusion.

Our data suggest that polymicrobial PJI might be underrepresented in the current literature. Additionally, the presence of multiple infectious organisms is associated with a reduced rate after two years with 67.6 vs 87.5 % for monomicrobial infections. Special attention and extra care should be considered for these patients.

Despite reliable results of ankle fusion for advanced haemophilic arthropathy, total ankle replacement (TAR) may be functionally advantageous. There is only very limited literature data available on TAR in patients with haemophilia. The objective of this study is to evaluate the short- and mid-term results after TAR in patients with end-stage haemophilic ankle arthropathy and concomitant virus infections. In a retrospective study, results after eleven TAR in 10 patients with severe (n = 8) and moderate (n = 2) haemophilia (mean age: 49 ± 7 years, range, 37-59) were evaluated at a mean follow-up of 3.0 years (range, 1.2-5.4). Nine patients were positive for hepatitis C, five were HIV-positive. Range of motion (ROM), AOFAS-hindfoot-score, pain status (visual analogue scale, VAS) as well as patient satisfaction were evaluated. In two cases deep prosthesis infection occurred leading to the removal of the implant. In the remaining eight patients the mean AOFAS score improved significantly from 21.5 to 68.0 points (P < 0.0005), the VAS score decreased significantly from 7.6 to 1.9 points (P < 0.0005). ROM increased from 23.2 to 25.0 degrees (P = 0.51). At final follow-up all patients without any complications were satisfied with the postoperative results. Radiographic examination did not reveal any signs of prosthetic loosening. TAR is a viable surgical treatment option in patients with end-stage ankle osteoarthritis due to haemophilia. It provides significant pain relieve and high patient satisfaction. However, due to the increased risk of infection and lack of long-term results, TAR particularly in patients with severe haemophilia and virus infections should be indicated carefully.

Background and purpose —Due to the relative lack of reports on the medium- to long-term clinical and radiographic results of modular femoral cementless revision, we conducted this study to evaluate the medium- to long-term results of uncemented femoral stem revisions using the modular MRP-TITAN stem with distal diaphyseal fixation in a consecutive patient series.Patients and methods —We retrospectively analyzed 163 femoral stem revisions performed between 1993 and 2001 with a mean follow-up of 10 (5–16) years. Clinical assessment included the Harris hip score (HHS) with reference to comorbidities and femoral defect sizes classified by Charnley and Paprosky. Intraoperative and postoperative complications were analyzed and the failure rate of the MRP stem for any reason was examined.Results —Mean HHS improved up to the last follow-up (37 (SD 24) vs. 79 (SD 19); p < 0.001). 99 cases (61%) had extensive bone defects (Paprosky IIB–III). Radiographic evaluation showed stable stem anchorage in 151 cases (93%) at the last follow-up. 10 implants (6%) failed for various reasons. Neither a breakage of a stem nor loosening of the morse taper junction was recorded. Kaplan-Meier survival analysis revealed a 10-year survival probability of 97% (95% CI: 95–100).Interpretation —This is one of the largest medium- to long-term analyses of cementless modular revision stems with distal diaphyseal anchorage. The modular MRP-TITAN was reliable, with a Kaplan-Meier survival probability of 97% at 10 years.

Purpose Current concepts in the treatment of prosthetic joint infections include prosthetic retention and exchange strategies according to published recommendations. A useful algorithm should fit for each type of prosthetic joint infection, even the most complicated situations. We present the outcome of 147 patients with prosthetic joint infections of the hip or the knee joint in an unselected population in clinical routine. Methods Between November 2006 and November 2009, 147 consecutive patients with prosthetic joint infections of the hip or knee were treated according to an algorithm based on the concept published by Zimmerli et al. in 2004. Causative organism, duration of infection, patient comorbidities, surgical treatment, antibiotic treatment, and outcome of treatment were analysed retrospectively. According to the criteria duration of infection, stability of prosthesis, local and systemic risk factors, and susceptibility of the causative pathogen, patients were treated either with debridement and retention or a longinterval two-stage procedure. Results A pathogen could be detected in 82.8 % of the patients, gram-positive cocci being most common. Twentyseven patients were treated with debridement and retention and 120 were treated with a two-stage procedure. In 68 cases difficult-to-treat pathogens could be detected, a polymicrobial infection was found in 51 patients. Definitely free of infection were 71.6 % after a two-stage procedure, and 70.4 % after debridement and retention. Conclusions Our data indicates that the applied algorithm is suitable to be applied as a day-to-day routine, and we confirmed that published results from the literature can be reproduced in an inhomogeneous patient cohort.

Model-based techniques have proven to be successful in interpreting the large amount of information contained in images. Associated fitting algorithms search for the global optimum of an objective function, which should correspond to the best model fit in a given image. Although fitting algorithms have been the subject of intensive research and evaluation, the objective function is usually designed ad hoc, based on implicit and domain-dependent knowledge. In this article, we address the root of the problem by learning more robust objective functions. First, we formulate a set of desirable properties for objective functions and give a concrete example function that has these properties. Then, we propose a novel approach that learns an objective function from training data generated by manual image annotations and this ideal objective function. In this approach, critical decisions such as feature selection are automated, and the remaining manual steps hardly require domain-dependent knowledge. Furthermore, an extensive empirical evaluation demonstrates that the obtained objective functions yield more robustness. Learned objective functions enable fitting algorithms to determine the best model fit more accurately than with designed objective functions.