Barriers to Applying Guidelines for Treatment of Type 2 Diabetes Mellitus in the Rio Grande Valley

Background: Type 2 Diabetes Mellitus affects 29.6% of adults in the Rio Grande Valley and 54% are estimated to be uncontrolled. Established and new pharmacotherapy agents are available, and guidelines exist in individualization of glycemic targets and agent selection. We present a case facing various barriers in applying these guidelines. Case Presentation: A 54-year-old uninsured woman with past medical history of uncontrolled type 2 diabetes mellitus, hypertension, chronic kidney disease stage 3, peripheral artery disease and bilateral below knee amputations presents for follow-up. She denies polyuria, polydipsia and weight changes. She reports compliance with medications and a fasting glucose range of 180-195. Current diabetes medications are insulin glargine, lispro, and dapagliflozin-metformin. Prior intolerance to dulaglutide with gastrointestinal upset. On exam, she had had a recent amputation with signs of infection. Data showed A1C this month at 9.4% from 13.7% 3 months ago and 14.8% 1 year ago. GFR stable at 58 and electrolytes normal. Urine protein creatinine ratio elevated at 1,865. Determined A1C goal to be below 8.0% based on multiple factors and reviewed benefits and risks of pharmacotherapy options. We increased the glargine and dapagliflozin-metformin. Conclusion: Though patient has a relatively young age, multiple factors suggest we have a less stringent target such as 8% including established vascular complications, limited resources as patient is uninsured, and patient self-care capabilities including health literacy. We will review the benefits, risks, and challenges in using sodium-glucose-cotransporter inhibitors and glucagon-like-peptide agonists and how the evidence applies to our patient

Meta-validation of bipartite network projections

Monopartite projections of bipartite networks are useful tools for modeling indirect interactions in complex systems. The standard approach to identify significant links is statistical validation using a suitable null network model, such as the popular configuration model (CM) that constrains node degrees and randomizes everything else. However different CM formulations exist, depending on how the constraints are imposed and for which sets of nodes. Here we systematically investigate the application of these formulations in validating the same network, showing that they lead to different results even when the same significance threshold is used. Instead a much better agreement is obtained for the same density of validated links. We thus propose a meta-validation approach that allows to identify model-specific significance thresholds for which the signal is strongest, and at the same time to obtain results independent of the way in which the null hypothesis is formulated. We illustrate this procedure using data on scientific production of world countries.The configuration model, in its various formulations, is a widely used null model for statistical validation of bipartite network projections. Here, the authors show that different formulations might bring to very different results, and propose a meta-validation approach that allows to identify model-specific significance thresholds while remaining null-model independent

Measuring Safety Performance in the extra-urban Road Network of Lombardy Region (Italy)

Road Network Screening (RNS) is a process to evaluate the safety performance of the whole road network and identify worst performing roads. Currently, literature provides many models and methods for RNS. Moreover, several frameworks of RNS were issued at the European National Level over time. However, even if sophisticated models and methods could be preferable for their computational accuracy, they may be far from the capabilities of practitioners. In addition, other issues such as availability of operative attributes and data quality and processing persist. For instance, accurate crash location, which is crucial for detailed analyses of high crash rates at some locations, is still an issue: many road administrations pointed out that coordinates miss or are inaccurate in many cases. Within this context, this paper proposes a straightforward operational framework to evaluate safety performance for RNS, using a flexible rationale that integrates crash, traffic, and road data, respectively. More precisely, this framework: (a) handles crash location data without using spatial coordinates; (b) computes the crash rate index at different administrative levels; (c) shows results by Geographic Information System (GIS) maps. This framework is applied to the whole extra-urban road network of the Lombardy Region (Northern Italy) using 30.000+ crash data provided by the Regional Institute for Lombardy Policy Support (PoliS). Road authorities could adopt this framework to perform an accurate safety screening on the road network aimed at rational planning of safety interventions

What makes spatial data big? A discussion on how to partition spatial data

The amount of available spatial data has significantly increased in the last years so that traditional analysis tools have become inappropriate to effectively manage them. Therefore, many attempts have been made in order to define extensions of existing MapReduce tools, such as Hadoop or Spark, with spatial capabilities in terms of data types and algorithms. Such extensions are mainly based on the partitioning techniques implemented for textual data where the dimension is given in terms of the number of occupied bytes. However, spatial data are characterized by other features which describe their dimension, such as the number of vertices or the MBR size of geometries, which greatly affect the performance of operations, like the spatial join, during data analysis. The result is that the use of traditional partitioning techniques prevents to completely exploit the benefit of the parallel execution provided by a MapReduce environment. This paper extensively analyses the problem considering the spatial join operation as use case, performing both a theoretical and an experimental analysis for it. Moreover, it provides a solution based on a different partitioning technique, which splits complex or extensive geometries. Finally, we validate the proposed solution by means of some experiments on synthetic and real datasets

Antimicrobial Challenge in Acute Care Surgery

The burden of infections in acute care surgery (ACS) is huge. Surgical emergencies alone account for three million admissions per year in the United States (US) with estimated financial costs of USD 28 billion per year. Acute care facilities and ACS patients represent boost sanctuaries for the emergence, development and transmission of infections and multi-resistant organisms. According to the World Health Organization, healthcare-associated infections affected around 4 million cases in Europe and 1.7 million in the US alone in 2011 with 39,000 and 99,000 directly attributable deaths, respectively. In this scenario, antimicrobial resistance arose as a public-health emergency that worsens patients’ morbidity and mortality and increases healthcare costs. The optimal patient care requires the application of comprehensive evidence-based policies and strategies aiming at minimizing the impact of healthcare associated infections and antimicrobial resistance, while optimizing the treatment of intra-abdominal infections. The present review provides a snapshot of two hot topics, such as antimicrobial resistance and systemic inflammatory response, and three milestones of infection management, such as source control, infection prevention, and control and antimicrobial stewardship

Tumor suppressors in chronic lymphocytic leukemia: From lost partners to active targets

Tumor suppressors play an important role in cancer pathogenesis and in the modulation of resistance to treatments. Loss of function of the proteins encoded by tumor suppressors, through genomic inactivation of the gene, disable all the controls that balance growth, survival, and apoptosis, promoting cancer transformation. Parallel to genetic impairments, tumor suppressor products may also be functionally inactivated in the absence of mutations/deletions upon post-transcriptional and post-translational modifications. Because restoring tumor suppressor functions remains the most effective and selective approach to induce apoptosis in cancer, the dissection of mechanisms of tumor suppressor inactivation is advisable in order to further augment targeted strategies. This review will summarize the role of tumor suppressors in chronic lymphocytic leukemia and attempt to describe how tumor suppressors can represent new hopes in our arsenal against chronic lymphocytic leukemia (CLL)

Comment on ``Spin Polarization and Magnetic Circular Dichroism in Photoemission from the 2p Core Level of Ferromagnetic Ni''

Although the Ni_4 cluster includes more information regarding the Ni band structure with respect to the Anderson impurity model, it also favors very peculiar ground states which are incompatible with a coherent picture of all dichroism experiments.Comment: 1 page, RevTeX, 1 epsf figur

A comparative cycling path selection for sustainable tourism in Franciacorta. An integrated AHP-ELECTRE method

Cycle tourism is a form of sustainable itinerant tourism expanding in Italy and the rest of the world, with prospects for growth in coming years. Europe and North America have already developed a wide range of cycling infrastructures tied to tourism experiences. Benefits induced are generally recognised: first, it is a sustainable solution that increases local economics while conserving the environment; second, it guarantees advantages on social connections, amusement, and physical and mental health. However, it requires an adequate network to enjoy destinations as historical and landscape peculiarities. Currently, literature provides some methods for planning itineraries dedicated to cycle tourism. Despite that, there is less attention on how evaluating existing or already planned tourist itineraries. This study covers this gap, by applying an integrated method to assess bicycle connections for tourism experiences within municipalities. Since this evaluation may contain many conflicting criteria (e.g., preferences of public administrator, technical and economic viability) and possible alternatives, this study frames the method as a multi-criteria decision-making problem (MCDM). Specifically, at first, the Analytical Hierarchy Process (AHP) is adopted to calculate weights for each criterium; next, the ELimination Et Choix Traduisant la REalitè (ELECTRE) method is applied to provide a (possible) priority ranking of cycling tourist paths among alternatives, by computing indices of discordance and concordance between pairs of alternatives. The framework is applied to the Franciacorta area (North-East Italy), a national and international tourist relevance territory encompassing 22 municipalities. This study may be useful for public administrators to rationalise and prioritise cycling routes

Development Of Innovating Na Leak Detector On Pipes

International audienceWithin the ASTRID reactor project, CEA, EDF and AREVA NP, have launched a RetD program focused on the low leak rates detection of sodium on pipes. This program is focused on the development of innovating detectors, multilayer-type and Optic Fiber, involving tests in the FUTUNa sodium loop. This loop is designed to produce very accurate sodium leak rates within a range around 1cm$^3$/min, the tests being performed at different temperature (up to 550DC) on large-diameter pipe mock-ups (D 800 mm) at ambient atmosphere. This paper presents the first series of tests carried out with various materials of the first and second layer of the detector. The results are compared and discussed as well as the observations made after removing the mock-ups. The most interesting result of the overall tests is a detection time less than 2 hours for the two types of detectors