Bmc Med
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Randomized Controlled Trial
A randomised controlled trial of dietary improvement for adults with major depression (the 'SMILES' trial).
The possible therapeutic impact of dietary changes on existing mental illness is largely unknown. Using a randomised controlled trial design, we aimed to investigate the efficacy of a dietary improvement program for the treatment of major depressive episodes. ⋯ These results indicate that dietary improvement may provide an efficacious and accessible treatment strategy for the management of this highly prevalent mental disorder, the benefits of which could extend to the management of common co-morbidities.
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Cardiovascular disease (CVD) is a common comorbidity in people with asthma. However, safety concerns have caused heterogeneity in clinical guideline recommendations over the use of cardioselective beta-blockers in people with asthma and CVD, partly because risk in the general population has been poorly quantified. The aim of this study was to measure the risk of asthma exacerbations with beta-blockers prescribed to a general population with asthma and CVD. ⋯ Cardioselective beta-blockers prescribed to people with asthma and CVD were not associated with a significantly increased risk of moderate or severe asthma exacerbations and potentially could be used more widely when strongly indicated.
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Disease models are useful for prospective studies of pathology, identification of molecular and cellular mechanisms, pre-clinical testing of interventions, and validation of clinical biomarkers. Here, we review animal models relevant to vascular cognitive impairment (VCI). A synopsis of each model was initially presented by expert practitioners. Synopses were refined by the authors, and subsequently by the scientific committee of a recent conference (International Conference on Vascular Dementia 2015). Only peer-reviewed sources were cited. ⋯ We concluded that (1) translational models may reflect a VCI-relevant pathological process, while not fully replicating a human disease spectrum; (2) rodent models of VCI are limited by paucity of white matter; and (3) further translational models, and improved cognitive testing instruments, are required.
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Several controlled clinical studies have evaluated the potential of the infection biomarker procalcitonin (PCT) to improve the diagnostic work-up of patients with bacterial infections and its influence on decisions regarding antibiotic therapy. Most research has focused on lower respiratory tract infections and critically ill sepsis patients. A clinical utility for PCT has also been found for patients with urinary tract infections, postoperative infections, meningitis, and patients with acute heart failure with possible superinfection (i.e., pneumonia). ⋯ PCT kinetics also proved to have prognostic value correlating with disease severity (i.e., pancreatitis, abdominal infection) and resolution of illness (i.e., sepsis). Although promising findings have been published in these different types of infections, there are a number of limitations regarding PCT, including suboptimal sensitivity and/or specificity, which makes a careful interpretation of PCT in the clinical context mandatory. This narrative review aims to update clinicians on the strengths and limitations of PCT for patient management, focusing on research conducted within the last 4 years.
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Rapid progress over the past decade has been made with the development of the 'Artificial Pancreas', also known as the closed-loop system, which emulates the feedback glucose-responsive functionality of the pancreatic beta cell. The recent FDA approval of the first hybrid closed-loop system makes the Artificial Pancreas a realistic therapeutic option for people with type 1 diabetes. In anticipation of its advent into clinical care, we provide a primer and appraisal of this novel therapeutic approach in type 1 diabetes for healthcare professionals and non-specialists in the field. ⋯ The introduction of the artificial pancreas into clinical practice represents a milestone towards the goal of improving the care of people with type 1 diabetes. There remains a need to understand the impact of user interaction with the technology, and its implication on current diabetes management and care.