Current Cardiology Reports 

About: Current Cardiology Reports is an academic journal published by Springer Science+Business Media. The journal publishes majorly in the area(s): Medicine & Heart failure. It has an ISSN identifier of 1523-3782. Over the lifetime, 2554 publications have been published receiving 41666 citations.

Electronic Cigarettes for Smoking Cessation

Abstract: Electronic cigarettes (e-cigarettes) are novel vaporising devices that, similar to nicotine replacement treatments, deliver nicotine but in lower amounts and less swiftly than tobacco smoking. However, they enjoy far greater popularity than these medications due in part to their behaviour replacement characteristics. Evidence for their efficacy as cessation aids, based on several randomised trials of now obsolete e-cigarettes, suggests a modest effect equivalent to nicotine patch. E-cigarettes are almost certainly far less harmful than tobacco smoking, but the health effects of long-term use are as yet unknown. Dual use is common and almost as harmful as usual smoking unless it leads to quitting. Population effects, such as re-normalising smoking behaviour, are a concern. Clinicians should be knowledgeable about these products. If patients who smoke are unwilling to quit or cannot succeed using evidence-based approaches, e-cigarettes may be an option to be considered after discussing the limitations of current knowledge.

Epidemiology of Diabetes Mellitus and Cardiovascular Disease

Abstract: Diabetes mellitus (DM) has become a rising epidemic in the last century, more pressing in the last few decades with the exponential rise of obesity, and has become one of the leading causes of death worldwide. Genetic variants have also been a new field of epidemiology research to determine the underlying genetic component of those risk factors and the association of DM with CVD. In light of its significant prevalence, patients remain unaware of their disease progression that arises from genetic and metabolic risk factors. As compared to non-diabetics, those with type 2 DM carry a higher mortality risk from cardiovascular disease (CVD) across different ethnicity groups and sex. The most common cardiovascular manifestations in those with DM include heart failure, peripheral arterial disease, and coronary heart disease. Although DM does predispose patients to CVD, it in fact is not a risk equivalent, but carries significant heterogeneity in risk for CVD.

Work Stress as a Risk Factor for Cardiovascular Disease

Abstract: The role of psychosocial work stress as a risk factor for chronic disease has been the subject of considerable debate. Many researchers argue in support of a causal connection while others remain skeptical and have argued that the effect on specific health conditions is either negligible or confounded. This review of evidence from over 600,000 men and women from 27 cohort studies in Europe, the USA and Japan suggests that work stressors, such as job strain and long working hours, are associated with a moderately elevated risk of incident coronary heart disease and stroke. The excess risk for exposed individuals is 10–40 % compared with those free of such stressors. Differences between men and women, younger versus older employees and workers from different socioeconomic backgrounds appear to be small, indicating that the association is robust. Meta-analyses of a wider range of health outcomes show additionally an association between work stress and type 2 diabetes, though not with common cancers or chronic obstructive pulmonary disease, suggesting outcome specificity. Few studies have addressed whether mitigation of work stressors would reduce the risk of cardiovascular disease. In view of the limited interventional evidence on benefits, harms and cost-effectiveness, definitive recommendations have not been made (e.g. by the US Preventive Services Taskforce) for the primary prevention of cardiovascular disease via workplace stress reduction. Nevertheless, governments are already launching healthy workplace campaigns, and preventing excessive work stress is a legal obligation in several countries. Promoting awareness of the link between stress and health among both employers and workers is an important component of workplace health promotion.

Artificial Intelligence in Medicine and Cardiac Imaging: Harnessing Big Data and Advanced Computing to Provide Personalized Medical Diagnosis and Treatment

Abstract: Although advances in information technology in the past decade have come in quantum leaps in nearly every aspect of our lives, they seem to be coming at a slower pace in the field of medicine. However, the implementation of electronic health records (EHR) in hospitals is increasing rapidly, accelerated by the meaningful use initiatives associated with the Center for Medicare & Medicaid Services EHR Incentive Programs. The transition to electronic medical records and availability of patient data has been associated with increases in the volume and complexity of patient information, as well as an increase in medical alerts, with resulting “alert fatigue” and increased expectations for rapid and accurate diagnosis and treatment. Unfortunately, these increased demands on health care providers create greater risk for diagnostic and therapeutic errors. In the near future, artificial intelligence (AI)/machine learning will likely assist physicians with differential diagnosis of disease, treatment options suggestions, and recommendations, and, in the case of medical imaging, with cues in image interpretation. Mining and advanced analysis of “big data” in health care provide the potential not only to perform “in silico” research but also to provide “real time” diagnostic and (potentially) therapeutic recommendations based on empirical data. “On demand” access to high-performance computing and large health care databases will support and sustain our ability to achieve personalized medicine. The IBM Jeopardy! Challenge, which pitted the best all-time human players against the Watson computer, captured the imagination of millions of people across the world and demonstrated the potential to apply AI approaches to a wide variety of subject matter, including medicine. The combination of AI, big data, and massively parallel computing offers the potential to create a revolutionary way of practicing evidence-based, personalized medicine.