Medication Reconciliation at Discharge from Hospital: A Systematic Review of the Quantitative Literature

Medicines reconciliation is a way to identify and act on discrepancies in patients’ medical histories and it is found to play a key role in patient safety. This review focuses on discrepancies and medical errors that occurred at point of discharge from hospital. Studies were identified through the following electronic databases: PubMed, Sciences Direct, EMBASE, Google Scholar, Cochrane Reviews and CINAHL. Each of the six databases was screened from inception to end of January 2014. To determine eligibility of the studies; the title, abstract and full manuscript were screened to find 15 articles that meet the inclusion criteria. The median number of discrepancies across the articles was found to be 60%. In average patient had between 1.2–5.3 discrepancies when leaving the hospital. More studies also found a relation between the numbers of drugs a patient was on and the number of discrepancies. The variation in the number of discrepancies found in the 15 studies could be due to the fact that some studies excluded patient taking more than 5 drugs at admission. Medication reconciliation would be a way to avoid the high number of discrepancies that was found in this literature review and thereby increase patient safety.

Ubiquitous Translation

In this book, Piotr Blumczynski explores the central role of translation as a key epistemological concept as well as a hermeneutic, ethical, linguistic and interpersonal practice. His argument is three-fold: (1) that translation provides a basis for genuine, exciting, serious, innovative and meaningful exchange between various areas of the humanities through both a concept (the WHAT) and a method (the HOW); (2) that, in doing so, it questions and challenges many of the traditional boundaries and offers a transdisciplinary epistemological paradigm, leading to a new understanding of quality, and thus also meaning, truth, and knowledge; and (3) that translational phenomena are studied by a broad range of disciplines in the humanities (including philosophy, theology, linguistics, and anthropology) using various, often seemingly unrelated concepts which nevertheless display a considerable degree of qualitative proximity. The common thread running through all these convictions and binding them together is the insistence that translational phenomena are ubiquitous. Because of its unconventional and innovative approach, this book will be of interest to translation studies scholars looking to situate their research within a broader transdisciplinary model, as well as to students of translation programs and practicing translators who seek a fuller understanding of why and how translation matters.

A HuGE Review and Meta-Analyses of Genetic Associations in New Onset Diabetes after Kidney Transplantation

PURPOSE: New onset diabetes after transplantation (NODAT) is a serious complication following solid organ transplantation. There is a genetic contribution to NODAT and we have conducted comprehensive meta-analysis of available genetic data in kidney transplant populations.

METHODS: Relevant articles investigating the association between genetic markers and NODAT were identified by searching PubMed, Web of Science and Google Scholar. SNPs described in a minimum of three studies were included for analysis using a random effects model. The association between identified variants and NODAT was calculated at the per-study level to generate overall significance values and effect sizes.

RESULTS: Searching the literature returned 4,147 citations. Within the 36 eligible articles identified, 18 genetic variants from 12 genes were considered for analysis. Of these, three were significantly associated with NODAT by meta-analysis at the 5% level of significance; CDKAL1 rs10946398 p = 0.006 OR = 1.43, 95% CI = 1.11-1.85 (n = 696 individuals), KCNQ1 rs2237892 p = 0.007 OR = 1.43, 95% CI = 1.10-1.86 (n = 1,270 individuals), and TCF7L2 rs7903146 p = 0.01 OR = 1.41, 95% CI = 1.07-1.85 (n = 2,967 individuals).

CONCLUSION: Evaluating cumulative evidence for SNPs associated with NODAT in kidney transplant recipients has revealed three SNPs associated with NODAT. An adequately powered, dense genome-wide association study will provide more information using a carefully defined NODAT phenotype.

Smartphone and GPS technology for freeroaming dog population surveillance -a methodological study (Studio metodologico sull’applicazione di smartphone e tecnologia GPS alla sorveglianza delle popolazioni di cani vaganti)

Free-roaming dogs (FRD) represent a potential threat to the quality of life in cities from an ecological, social and public health point of view. One of the most urgent concerns is the role of uncontrolled dogs as reservoirs of infectious diseases transmittable to humans and, above all, rabies. An estimate of the FRD population size and characteristics in a given area is the first step for any relevant intervention programme. Direct count methods are still prominent because of their non-invasive approach, information technologies can support such methods facilitating data collection and allowing for a more efficient data handling. This paper presents a new framework for data collection using a topological algorithm implemented as ArcScript in ESRI® ArcGIS software, which allows for a random selection of the sampling areas. It also supplies a mobile phone application for Android® operating system devices which integrates Global Positioning System (GPS) and Google Maps™. The potential of such a framework was tested in 2 Italian regions. Coupling technological and innovative solutions associated with common counting methods facilitate data collection and transcription. It also paves the way to future applications, which could support dog population management systems.

School-based approaches to the correction of refractive error in children.

The World Health Organization estimates that 13 million children aged 5-15 years worldwide are visually impaired from uncorrected refractive error. School vision screening programs can identify and treat or refer children with refractive error. We concentrate on the findings of various screening studies and attempt to identify key factors in the success and sustainability of such programs in the developing world. We reviewed original and review articles describing children's vision and refractive error screening programs published in English and listed in PubMed, Medline OVID, Google Scholar, and Oxford University Electronic Resources databases. Data were abstracted on study objective, design, setting, participants, and outcomes, including accuracy of screening, quality of refractive services, barriers to uptake, impact on quality of life, and cost-effectiveness of programs. Inadequately corrected refractive error is an important global cause of visual impairment in childhood. School-based vision screening carried out by teachers and other ancillary personnel may be an effective means of detecting affected children and improving their visual function with spectacles. The need for services and potential impact of school-based programs varies widely between areas, depending on prevalence of refractive error and competing conditions and rates of school attendance. Barriers to acceptance of services include the cost and quality of available refractive care and mistaken beliefs that glasses will harm children's eyes. Further research is needed in areas such as the cost-effectiveness of different screening approaches and impact of education to promote acceptance of spectacle-wear. School vision programs should be integrated into comprehensive efforts to promote healthy children and their families.

PageRank in Malware Categorization

In this paper, we propose a malware categorization method that models malware behavior in terms of instructions using PageRank. PageRank computes ranks of web pages based on structural information and can also compute ranks of instructions that represent the structural information of the instructions in malware analysis methods. Our malware categorization method uses the computed ranks as features in machine learning algorithms. In the evaluation, we compare the effectiveness of different PageRank algorithms and also investigate bagging and boosting algorithms to improve the categorization accuracy.