Songalbrektsen6505

OBJECTIVE To determine preference-based (utility) assessments of health-related quality of life (HRQoL) in kidney stone patients, and evaluate the association between these and disease specific, psychometric health status-based HRQoL scores (obtained via the Wisconsin Stone Quality of Life [WISQOL]). METHODS One hundred four adults with urolithiasis, as well as 78 young healthy adults without history of urolithiasis (controls) were consecutively enrolled, meeting the predetermined recruitment goal. Each participant completed the SF-36 v2 (from which SF-6D utility is calculated) and EQ-5D questionnaires, while urolithiasis patients additionally completed the WISQOL. Relationship between health utility and WISQOL scores was evaluated using Pearson's test and multivariable linear regression analysis (MVA). Construct validity of the utilities for urolithiasis was assessed by comparing utilities for patients vs controls, and for symptomatic vs asymptomatic patients. RESULTS Mean (SD) WISQOL standard score, SF-6D, and EQ-5D utilities in stone patients respectively were 63 (29.1), 0.68 (0.16), and 0.83 (0.17). SF-6D and EQ-5D utilities significantly correlated with WISQOL standard score (Pearson's r = 0.87 and 0.58, respectively; each P less then .0001). On MVA, WISQOL standard score was a significant predictor of SF-6D and EQ-5D utilities, explaining 72.1% and 33.9% of the respective variances in the utilities. Median SF-6D and EQ-5D utility were significantly lower in patients vs controls (each P ≤.0009), and in symptomatic vs asymptomatic patients (each P ≤ .0002). CONCLUSION SF-6D, more so than EQ-5D utilities in urolithiasis patients are strongly associated with disease-specific WISQOL scores, suggesting they are optimal for preference-based HRQoL assessment in this population. Construct validity of the utilities in stone disease was demonstrated. OBJECTIVE To identify how demographic factors, stone-associated medical co-morbidities, and treatment predict compliance with 24-hour urine collection. MATERIALS AND METHODS A retrospective medical record review of patients treated for urolithiasis between August 2014 and March 2017 was performed. Patient demographics, medical characteristics, stone factors, type of treatment, and compliance data were included for patients requested to submit a collection. Variables that were statistically significant on bivariate analysis were then used to formulate a model predicting submission of a 24-hour urine sample. Procaspase activation RESULTS Of the 303 patients who met inclusion criteria, 183 (60.4%) submitted an initial 24-hour urine collection. On bivariate analysis, patients older than 50 were more likely to submit a 24-hour urine collection (71.4% vs 51.5%; p less then 0.001), patients with a metabolic predisposition for stones were more likely to submit a 24-hour urine collection (70.6% vs 53.1%; p less then 0.003), and patients who did not have surgery were more likely to submit a 24-hour urine collection (97.9% vs 53.5%; p less then 0.001). Our three-variable prediction model found that not undergoing surgery was a strong predictor of 24-hour urine collection. CONCLUSIONS We suspect that patients perceive surgery as a more definitive treatment for kidney stones than conservative management. Patient education on the natural history and role of metabolic management in the prevention of nephrolithiasis is essential in improving compliance with 24-hour urine collection. The Suppression of Tumorigenicity 2 protein (ST2) is a member of the interleukin (IL) 1 receptor family with transmembrane (ST2L) and soluble (sST2) isoforms that are (over)expressed in several cells in different conditions and following various triggers (e.g. inflammation, stress). The ligand of ST2 is IL-33, which on binding to ST2L results in nuclear signalling and immunomodulatory action in various cells (tumour, immune, heart). sST2, that is released in the circulation, functions as a »decoy« receptor of IL-33 and inhibits IL-33/ST2L signalling and beneficial effects. The importance and role of the ST2/IL-33 axis and sST2 have been evaluated and confirmed in several inflammatory, cancer and cardiac diseases. sST2 is involved in homeostasis/pathogenesis of these diseases, as the counterbalance/response on IL-33/ST2L axis activation, which is triggered and expressed during developing fibrosis, tissue damage/inflammation and remodelling. In clinical studies, sST2 has been recognised as an important prognostic marker in patients with cardiac disease, including patients with chronic kidney disease where specific characteristics of sST2 enable better assessment of the risk of End-Stage Renal Disease patients on dialysis. sST2 is also recognised as an important marker for monitoring treatment in heart failure patients. However, accurate measurement and interpretation of ST2 concentration in serum/plasma samples for routine and research applications require the use of appropriate methods and recognition of essential characteristics of both the methods and the analyte that may influence the result. sST2, as one of the most promising disease biomarkers, is deserving of further study and wider application in clinical practice. V.Discovery of new protein biomarker candidates has become a major research goal in the areas of clinical chemistry, analytical chemistry, and biomedicine. These important species constitute the molecular target when it comes to diagnosis, prognosis, and further monitoring of disease. However, their analysis requires powerful, selective and high-throughput sample preparation and product (analyte) characterisation approaches. In general, manual sample processing is tedious, complex and time-consuming, especially when large numbers of samples have to be processed (e.g., in clinical studies). Automation via microtiter-plate platforms involving robotics has brought improvements in high-throughput performance while comparable or even better precisions and repeatability (intra-day, inter-day) were achieved. At the same time, waste production and exposure of laboratory personnel to hazards were reduced. In comprehensive protein analysis workflows (e.g., liquid chromatography-tandem mass spectrometry analysis), sample preparation is an unavoidable step.