The Conundrum of Security in Modern Cloud Computing

In today’s economic climate organizations are seeking greater cost-saving measures, increased agility, and scalability that responds to the rapid changes in technology and business. Cloud computing, with its low cost pay-as-you-go business model, is helping organizations manage these changes while transforming information technology (IT) into an engine that drives business. Benefits from on-demand clouds provide users greater portability and the ability to access information from virtually anywhere: at home, a client location, when traveling, or at the office. The reduced costs and increased flexibility, however, associated with cloud computing also come with complex security issues and increased overall risk. When cloud services are moved beyond organizational boundaries, outside the border firewall, security is heightened for most organizations and navigating the complexity of these environments can be daunting. In this research paper we seek to help organizations make pragmatic decisions about where and when to use cloud solutions by outlining specific security issues that enterprises should address. We use external research sources and explore current security trends within cloud computing in order to provide background information, related research, and conclusions. We make use of colleagues, textbooks, peer reviewed journal articles, and Internet websites related to information technology and information security. Each section of our research is formatted similarly and presents pertinent security information, techniques, and tools that organizations would need in order to make relevant decisions when utilizing Software as a Service (SaaS), Platform as a Service (PaaS), or Infrastructure as a Service (IaaS)

Distress related to myocardial infarction and cardiovascular outcome: a retrospective observational study

Background During acute coronary syndromes patients perceive intense distress. We hypothesized that retrospective ratings of patients' MI-related fear of dying, helplessness, or pain, all assessed within the first year post-MI, are associated with poor cardiovascular outcome. Methods We studied 304 patients (61 ± 11 years, 85% men) who after a median of 52 days (range 12-365 days) after index MI retrospectively rated the level of distress in the form of fear of dying, helplessness, or pain they had perceived at the time of MI on a numeric scale ranging from 0 ("no distress") to 10 ("extreme distress"). Non-fatal hospital readmissions due to cardiovascular disease (CVD) related events (i.e., recurrent MI, elective and non-elective stent implantation, bypass surgery, pacemaker implantation, cerebrovascular incidents) were assessed at follow-up. The relative CVD event risk was computed for a (clinically meaningful) 2-point increase of distress using Cox proportional hazard models. Results During a median follow-up of 32 months (range 16-45), 45 patients (14.8%) experienced a CVD-related event requiring hospital readmission. Greater fear of dying (HR 1.21, 95% CI 1.03-1.43), helplessness (HR 1.22, 95% CI 1.04-1.44), or pain (HR 1.27, 95% CI 1.02-1.58) were significantly associated with an increased CVD risk without adjustment for covariates. A similarly increased relative risk emerged in patients with an unscheduled CVD-related hospital readmission, i.e., when excluding patients with elective stenting (fear of dying: HR 1.26, 95% CI 1.05-1.51; helplessness: 1.26, 95% CI 1.05-1.52; pain: HR 1.30, 95% CI 1.01-1.66). In the fully-adjusted models controlling for age, the number of diseased coronary vessels, hypertension, and smoking, HRs were 1.24 (95% CI 1.04-1.46) for fear of dying, 1.26 (95% CI 1.06-1.50) for helplessness, and 1.26 (95% CI 1.01-1.57) for pain. Conclusions Retrospectively perceived MI-related distress in the form of fear of dying, helplessness, or pain was associated with non-fatal cardiovascular outcome independent of other important prognostic factors

A population-based phenome-wide association study of cardiac and aortic structure and function

Differences in cardiac and aortic structure and function are associated with cardiovascular diseases and a wide range of other types of disease. Here we analyzed cardiovascular magnetic resonance images from a population-based study, the UK Biobank, using an automated machine-learning-based analysis pipeline. We report a comprehensive range of structural and functional phenotypes for the heart and aorta across 26,893 participants, and explore how these phenotypes vary according to sex, age and major cardiovascular risk factors. We extended this analysis with a phenome-wide association study, in which we tested for correlations of a wide range of non-imaging phenotypes of the participants with imaging phenotypes. We further explored the associations of imaging phenotypes with early-life factors, mental health and cognitive function using both observational analysis and Mendelian randomization. Our study illustrates how population-based cardiac and aortic imaging phenotypes can be used to better define cardiovascular disease risks as well as heart–brain health interactions, highlighting new opportunities for studying disease mechanisms and developing image-based biomarkers

2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS guideline for the diagnosis and management of patients with stable ischemic heart disease

The recommendations listed in this document are, whenever possible, evidence based. An extensive evidence review was conducted as the document was compiled through December 2008. Repeated literature searches were performed by the guideline development staff and writing committee members as new issues were considered. New clinical trials published in peer-reviewed journals and articles through December 2011 were also reviewed and incorporated when relevant. Furthermore, because of the extended development time period for this guideline, peer review comments indicated that the sections focused on imaging technologies required additional updating, which occurred during 2011. Therefore, the evidence review for the imaging sections includes published literature through December 2011

Treatment costs for depression with pain and cardiovascular comorbidities

Objective: As depressive disorders are highly heterogeneous, and as patients exhibit wide differences in clinical characteristics and comorbidities, we aim to examine whether and how demographic and clinical correlates affect healthcare costs for patients with depression in a real-world setting. Method: A national cohort of adult patients (n = 216,557) who received treatment for depression was identified from the National Health Insurance Research Database in Taiwan. Factors associated with service use and healthcare costs over a 12-month period were explored, with a particular focus on past treatment history, comorbid physical illnesses, painful physical symptoms, and choice of initial antidepressants. Results: Depression severity, past treatment history, comorbid mental/physical illnesses, painful physical symptoms, and choice of initial antidepressants were found to be associated with healthcare costs in the following year, although the nature of the associations differed across cost categories. The presence of comorbid cardiovascular disease or certain painful physical symptoms at baseline was associated not only with higher non-psychiatric but also with higher psychiatric costs; moreover, patients with these comorbidities were shown to have increased use of psychiatric emergency and inpatient services. Conclusion: Healthcare costs for depression are affected by a number of clinical characteristics and comorbidities of patients. The importance of comorbid pain and cardiovascular conditions warrants further research