Revision after shoulder replacement for acute fracture of the proximal humerus

Background and purpose — For more than half a century, stemmed hemiarthroplasty (SHA) has been used in the treatment of comminuted and displaced fractures of the proximal humerus. Reverse shoulder arthroplasty (RSA) has been increasingly popular in cases where it is difficult to obtain satisfactory fixation of the tuberosities. We report revision rates and reasons for revision after shoulder arthroplasty for acute fractures of the proximal humerus. Patients and methods — This study was based on a common dataset from the Nordic Arthroplasty Register Association (NARA), which includes data reported to the national shoulder arthroplasty registries in Denmark, Sweden, and Norway. We included 6,756 shoulder arthroplasties performed for acute fractures between 2004 and 2013. Results — There were 6,112 SHAs (90%) and 565 RSAs (8.4%). The cumulative arthroplasty survival rate after 5 years was 0.96 for both SHA and RSA. The relative risk of revision of RSA was 1.4 (95% CI: 0.9–2.2) with SHA as reference. For both types of arthroplasty, the most common reason for revision was infection (SHA 0.8%, RSA 2.1%). The relative risk of revision due to infection was 3.1 (95% CI: 1.6–5.9) for RSA with SHA as reference. The relative risk of revision for patients who were less than 75 years of age was 2.8 (95% CI: 2.0–3.8) compared to older patients. Interpretation — Revision after shoulder arthroplasty for acute fractures was rare. Survival rates were similar between SHA and RSA, but RSA had a statistically significant and clinically relevant higher risk of revision because of infection

Carriage of an ACME II variant may have contributed to methicillin-resistant staphylococcus aureus sequence type 239-like strain replacement in Liverpool hospital, Sydney, Australia

Approximately 39% of methicillin-resistant Staphylococcus aureus (MRSA) sequence type 239 (ST239)-like bloodstream isolates from Liverpool Hospital (obtained between 1997 and 2008) carry an arginine catabolic mobile element (ACME). Whole-genome sequencing revealed that an ACME II variant is located between orfX and SCCmec III, and based on pulsed-field gel electrophoresis patterns and temporal relationships of all ST239-like isolates (n = 360), ACME carriage may have contributed to subpulsotype strain replacement

Analytical variables influencing the performance of a miRNA based laboratory assay for prediction of relapse in stage I non-small cell lung cancer (NSCLC)

<p>Abstract</p> <p>Background</p> <p>Laboratory assays are needed for early stage non-small lung cancer (NSCLC) that can link molecular and clinical heterogeneity to predict relapse after surgical resection. We technically validated two miRNA assays for prediction of relapse in NSCLC. Total RNA from seventy-five formalin-fixed and paraffin-embedded (FFPE) specimens was extracted, labeled and hybridized to Affymetrix miRNA arrays using different RNA input amounts, ATP-mix dilutions, array lots and RNA extraction- and labeling methods in a total of 166 hybridizations. Two combinations of RNA extraction- and labeling methods (assays I and II) were applied to a cohort of 68 early stage NSCLC patients.</p> <p>Results</p> <p>RNA input amount and RNA extraction- and labeling methods affected signal intensity and the number of detected probes and probe sets, and caused large variation, whereas different ATP-mix dilutions and array lots did not. Leave-one-out accuracies for prediction of relapse were 63% and 73% for the two assays. Prognosticator calls ("no recurrence" or "recurrence") were consistent, independent on RNA amount, ATP-mix dilution, array lots and RNA extraction method. The calls were not robust to changes in labeling method.</p> <p>Conclusions</p> <p>In this study, we demonstrate that some analytical conditions such as RNA extraction- and labeling methods are important for the variation in assay performance whereas others are not. Thus, careful optimization that address all analytical steps and variables can improve the accuracy of prediction and facilitate the introduction of microRNA arrays in the clinic for prediction of relapse in stage I non-small cell lung cancer (NSCLC).</p