The effect of antimicrobial resistance on patient outcomes: importance of proper evaluation of appropriate therapy

The impact of antimicrobial resistance on patient outcomes can be effectively measured only if the appropriateness of the antimicrobial therapy received is properly measured. Definition of appropriate therapy should include not only in vitro susceptibility but also the clinical adequacy of the antibiotic used, taking into account the pathogen isolated, the site of infection, known pharmacokinetic and pharmacodynamic properties of the drug, and dosing. In the absence of these data, the effect of delay or absence of appropriate therapy in patients infected with resistant bacterial pathogens is subject to confounding, and the true effect of resistance on outcomes may be obscured

Transfer of Carbapenem-Resistant Plasmid from Klebsiella pneumoniae ST258 to Escherichia coli in Patient

Klebsiella pneumoniae carbapenemase (KPC) 3–producing Escherichia coli was isolated from a carrier of KPC-3–producing K. pneumoniae. The KPC-3 plasmid was identical in isolates of both species. The patient's gut flora contained a carbapenem-susceptible E. coli strain isogenic with the KPC-3–producing isolate, which suggests horizontal interspecies plasmid transfer

Input-Sensitive Performance Testing

One goal of performance testing is to find specific test input data for exposing performance bottlenecks and identify the methods responsible for these performance bottlenecks. A big and important challenges of performance testing is how to deeply understand the performance behaviors of a non-trivial software system in terms of test input data to properly select the specific test input values for finding the problematic methods. Thus, we propose this research program to automatically analyze performance behaviors in software and link these behaviors with test input data for selecting the specific ones that can expose performance bottlenecks. In addition, this research further examines the corresponding execution traces of selected inputs for targeting the problematic methods

Automatic generation of software interfaces for supporting decision-making processes. An application of domain engineering and machine learning

Information dashboards are sophisticated tools. Although they enable users to reach useful insights and support their decisionmaking challenges, a good design process is essential to obtain powerful tools. Users need to be part of these design processes, as they will be the consumers of the information displayed. But users are very diverse and can have different goals, beliefs, preferences, etc., and creating a new dashboard for each potential user is not viable. There exist several tools that allow users to configure their displays without requiring programming skills. However, users might not exactly know what they want to visualize or explore, also becoming the configuration process a tedious task. This research project aims to explore the automatic generation of user interfaces for supporting these decisionmaking processes. To tackle these challenges, a domain engineering, and machine learning approach is taken. The main goal is to automatize the design process of dashboards by learning from the context, including the end-users and the target data to be displayed

Historical roots of Agile methods: where did “Agile thinking” come from?

The appearance of Agile methods has been the most noticeable change to software process thinking in the last fifteen years [16], but in fact many of the “Agile ideas” have been around since 70’s or even before. Many studies and reviews have been conducted about Agile methods which ascribe their emergence as a reaction against traditional methods. In this paper, we argue that although Agile methods are new as a whole, they have strong roots in the history of software engineering. In addition to the iterative and incremental approaches that have been in use since 1957 [21], people who criticised the traditional methods suggested alternative approaches which were actually Agile ideas such as the response to change, customer involvement, and working software over documentation. The authors of this paper believe that education about the history of Agile thinking will help to develop better understanding as well as promoting the use of Agile methods. We therefore present and discuss the reasons behind the development and introduction of Agile methods, as a reaction to traditional methods, as a result of people's experience, and in particular focusing on reusing ideas from histor

A study of the Scrum Master’s role

Scrum is an increasingly common approach to software development adopted by organizations around the world. However, as organizations transition from traditional plan-driven development to agile development with Scrum, the question arises as to which Scrum role (Product Owner, Scrum Master, or Scrum Team Member) corresponds to a Project Manager, or conversely which Scrum role should the Project Managers adopt? In an attempt to answer this question, we adopted a mixed-method research approach comprising a systematic literature review and embedded case study of a commercial software development team. Our research has identified activities that comprise the Scrum Master role, and which additional roles are actually performed by Scrum Masters in practice. We found nine activities that are performed by Scrum Masters. In addition, we found that Scrum Masters also perform other roles, most importantly as Project Managers. This latter situation results in tension and conflict of interest that could have a negative impact on the performance of the team as a whole. These results point to the need to re-assess the role of Project Managers in organizations that adopt Scrum as a development approach. We hypothesize that it might be better for Project Managers to become Product Owners, as aspects of this latter role are more consistent with the traditional responsibilities of a Project Manager

Gram-Negative Bacteremia upon Hospital Admission: When Should Pseudomonas aeruginosa Be Suspected?

Background. Pseudomonas aeruginosa is an uncommon cause of community-acquired bacteremia among patients without severe immunodeficiency. Because tension exists between the need to limit unnecessary use of anti-pseudomonal agents and the need to avoid a delay in appropriate therapy, clinicians require better guidance regarding when to cover empirically for P. aeruginosa. We sought to determine the occurrence of and construct a model to predict P. aeruginosa bacteremia upon hospital admission. Methods. A retrospective study was conducted in 4 tertiary care hospitals. Microbiology databases were searched to find all episodes of bacteremia caused by gram-negative rods (GNRs) ⩽48 h after hospital admission. Patient data were extracted from the medical records of 151 patients with P. aeruginosa bacteremia and of 152 randomly selected patients with bacteremia due to Enterobacteriaceae. Discriminative parameters were identified using logistic regression, and the probabilities of having P. aeruginosa bacteremia were calculated. Results. P. aeruginosa caused 6.8% of 4114 unique patient episodes of GNR bacteremia upon hospital admission (incidence ratio, 5 cases per 10,000 hospital admissions). Independent predictors of P. aeruginosa bacteremia were severe immunodeficiency, age >90 years, receipt of antimicrobial therapy within past 30 days, and presence of a central venous catheter or a urinary device. Among 250 patients without severe immunodeficiency, if no predictor variables existed, the likelihood of having P. aeruginosa bacteremia was 1:42. If ⩾2 predictors existed, the risk increased to nearly 1:3. Conclusions. P. aeruginosa bacteremia upon hospital admission in patients without severe immunodeficiency is rare. Among immunocompetent patients with suspected GNR bacteremia who have ⩾2 predictors, empirical anti-pseudomonal treatment is warrante

Single-Cell Glia and Neuron Gene Expression in the Central Amygdala in Opioid Withdrawal Suggests Inflammation With Correlated Gut Dysbiosis.

Drug-seeking in opioid dependence is due in part to the severe negative emotion associated with the withdrawal syndrome. It is well-established that negative emotional states emerge from activity in the amygdala. More recently, gut microflora have been shown to contribute substantially to such emotions. We measured gene expression in single glia and neurons gathered from the amygdala using laser capture microdissection and simultaneously measured gut microflora in morphine-dependent and withdrawn rats to investigate drivers of negative emotion in opioid withdrawal. We found that neuroinflammatory genes, notabl