Failure to rescue in the era of the lung allocation score: The impact of center volume.

BACKGROUND: Failure to Rescue (FTR) is a valuable surgical quality improvement metric. The aim of this study is to assess the relationship between center volume and FTR following lung transplantation. METHODS: Using the database of the United Network for Organ Sharing (UNOS) all adult, primary, isolated lung recipients in the United States between May 2005 and March 2016 were identified. FTR was defined as operative mortality after any of five specific complications. FTR was compared across terciles of transplantation centers stratified based on operative volume. RESULTS: 17,185 lung recipients met study criteria. The composite FTR rate (Death following at least one complication) was 20.7%. Following stratification by volume, FTR rates increased from high to middle tercile centers (19.3% vs. 23.0%). Multivariate logistic regression models suggested an independent relationship between higher center volume and lower FTR rates (p < 0.001). CONCLUSION: Higher volume lung transplantation centers have lower rates of failure to rescue.

Digital direct detection of microRNAs using single molecule arrays.

MicroRNAs (miRNAs) are involved in many biological pathways, and detecting miRNAs accurately is critical for diagnosing a variety of diseases including cancer. However, most current methods for miRNA detection require lengthy sample preparation and amplification steps that can bias the results. In addition, lack of specificity and reproducibility give rise to various challenges in detection of circulating miRNAs in biological samples. In this work, we applied the Single Molecule Array (Simoa) technique to develop an ultra-sensitive sandwich assay for direct detection of multiple miRNAs without pre-amplification. We successfully detected miRNAs at femtomolar concentrations (with limits of detection [LODs] ranging from 1 to 30 fM) and high specificity (distinguishing miRNAs with a single nucleotide mismatch). This method was effective against a range of diverse target sequences, suggesting a general approach for miRNA detection. To demonstrate the practical application of this technique, we detected miRNAs in a variety of sample types including human serum and total RNA. The high sensitivity and simple workflow of the Simoa method represent excellent advantages for miRNA-based diagnostics of human diseases.