46 research outputs found

    Poor adherence to antibiotic prescribing guidelines in acute otitis media—obstacles, implications, and possible solutions

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    Many countries now have guidelines on the clinical management of acute otitis media. In almost all, the public health goal of containing acquired resistance in bacteria through reduced antibiotic prescribing is the main aim and basis for recommendations. Despite some partial short-term successes, clinical activity databases and opinion surveys suggest that such restrictive guidelines are not followed closely, so this aim is not achieved. Radical new solutions are needed to tackle irrationalities in healthcare systems which set the short-term physician–patient relationship against long-term public health. Resolving this opposition will require comprehensive policy appraisal and co-ordinated actions at many levels, not just dissemination of evidence and promotion of guidelines. The inappropriate clinical rationales that underpin non-compliance with guidelines can be questioned by evidence, but also need specific developments promoting alternative solutions, within a framework of whole-system thinking. Promising developments would be (a) physician training modules on age-appropriate analgesia and on detection plus referral of rare complications like mastoiditis, and (b) vaccination against the most common and serious bacterial pathogens

    Treatment of relapsed and refractory multiple myeloma: recommendations from the International Myeloma Working Group

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    This Policy Review presents the International Myeloma Working Group's clinical practice recommendations for the treatment of relapsed and refractory multiple myeloma. Based on the results of phase 2 and phase 3 trials, these recommendations are proposed for the treatment of patients with relapsed and refractory disease who have received one previous line of therapy, and for patients with relapsed and refractory multiple myeloma who have received two or more previous lines of therapy. These recommendations integrate the issue of drug access in both low-income and middle-income countries and in high-income countries to help guide real-world practice and thus improve patient outcomes

    A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

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    Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

    A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

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    Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

    The Lipoxygenases: Their Regulation and Implication in Alzheimer’s Disease

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    Step by step: Early detection of diseases using an intelligent floor

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    The development of sensor technologies in smart homes helps to increase user comfort or to create safety through the recognition of emergency situations. For example, lighting in the home can be controlled or an emergency call can be triggered if sensors hidden in the floor detect a fall of a person. It makes sense to also use these technologies regarding prevention and early detection of diseases. By detecting deviations and behavioral changes through long-term monitoring of daily life activities it is possible to identify physical or cognitive diseases. In this work, we first examine in detail the existing possibilities to recognize the activities of daily life and the capability of such a system to conclude from the given data on illnesses. Then we propose a model for the use of floor-based sensor technology to help diagnose diseases and behavioral changes by analyzing the time spent in bed as well as the walking speed of users. Finally, we show that the system can be used in a real environment
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