University of Alberta

About: University of Alberta is a education organization based out in Edmonton, Alberta, Canada. It is known for research contribution in the topics: Population & Health care. The organization has 65403 authors who have published 154847 publications receiving 5358338 citations. The organization is also known as: Ualberta & UAlberta.

Improvement in outcomes of clinical islet transplantation: 1999-2010.

Abstract: OBJECTIVE To describe trends of primary efficacy and safety outcomes of islet transplantation in type 1 diabetes recipients with severe hypoglycemia from the Collaborative Islet Transplant Registry (CITR) from 1999 to 2010. RESEARCH DESIGN AND METHODS A total of 677 islet transplant-alone or islet-after-kidney recipients with type 1 diabetes in the CITR were analyzed for five primary efficacy outcomes and overall safety to identify any differences by early (1999–2002), mid (2003–2006), or recent (2007–2010) transplant era based on annual follow-up to 5 years. RESULTS Insulin independence at 3 years after transplant improved from 27% in the early era (1999–2002, n = 214) to 37% in the mid (2003–2006, n = 255) and to 44% in the most recent era (2007–2010, n = 208; P = 0.006 for years-by-era; P = 0.01 for era alone). C-peptide ≥0.3 ng/mL, indicative of islet graft function, was retained longer in the most recent era ( P 1c and resolution of severe hypoglycemia exhibited enduring long-term effects. Fasting blood glucose stabilization also showed improvements in the most recent era. There were also modest reductions in the occurrence of adverse events. The islet reinfusion rate was lower: 48% by 1 year in 2007–2010 vs. 60–65% in 1999–2006 ( P P CONCLUSIONS The CITR shows improvement in primary efficacy and safety outcomes of islet transplantation in recipients who received transplants in 2007–2010 compared with those in 1999–2006, with fewer islet infusions and adverse events per recipient.

Current status of machine prognostics in condition-based maintenance: a review

Abstract: Condition-based maintenance (CBM) is a decision-making strategy based on real-time diagnosis of impending failures and prognosis of future equipment health. It is a proactive process that requires the development of a predictive model that can trigger the alarm for corresponding maintenance. Prognostic methodologies for CBM have only recently been introduced into the technical literature and become such a focus in the field of maintenance research and development. There are many research and development on a variety of technologies and algorithms that can be regarded as the steps toward prognostic maintenance. They are needed in order to support decision making and manage operational reliability. In this paper, recent literature that focuses on the machine prognostics has been reviewed. Generally, prognostic models can be classified into four categories: physical model, knowledge-based model, data-driven model, and combination model. Various techniques and algorithms have been developed depending on what models they usually adopt. Based on the review of some typical approaches and new introduced methods, advantages and disadvantages of these methodologies are discussed. From the literature review, some increasing trends appeared in the research field of machine prognostics are summarized. Furthermore, the future research directions have been explored.