•Studies varied considerably in estimating costs involved in diabetic amputation.•Inpatient care costs associated with diabetic amputation were £43.8 million.•Post-amputation care annual expenditure ...was £20.8 million.•Diabetes-related amputations create considerable public health and economic burden.
The main aim of this study was to assess the cost of diabetic amputation (both direct and indirect) to the National Health Service from the point of amputation onwards.
This systematic review involved searches of published literature between January 2007 and March 2017 mainly using the bibliographic databases, the Cochrane Library, EMBASE via Ovid®, MEDLINE via Ovid®, as well as grey literature, both in print and in electronic formats published through non-commercial publications, which reported the cost of amputation due to diabetic foot ulcers.
The studies included in this review varied considerably in estimating the cost including cost elements and how those costs were categorised. The cost estimates for inpatient care associated with amputation involving admissions or procedures on amputation stumps in people with diabetes was £43.8 million. The annual expenditure for post-amputation care involving prosthetic care, physiotherapy, transport and wheelchair use was £20.8 million.
There is a considerable public health and economic burden caused by diabetes-related amputations in England. More focussed research is needed with improved methods of estimating costs that would account for direct and indirect costs associated with diabetic amputation.
The increasing availability of high-throughput sequencing (frequently termed next-generation sequencing (NGS)) data has created opportunities to gain deeper insights into the mechanisms of a number ...of diseases and is already impacting many areas of medicine and public health. The area of infectious diseases stands somewhat apart from other human diseases insofar as the relevant genomic data comes from the microbes rather than their human hosts. A particular concern about the threat of antimicrobial resistance (AMR) has driven the collection and reporting of large-scale datasets containing information from microbial genomes together with antimicrobial susceptibility test (AST) results. Unfortunately, the lack of clear standards or guiding principles for the reporting of such data is hampering the field's advancement. We therefore present our recommendations for the publication and sharing of genotype and phenotype data on AMR, in the form of 10 simple rules. The adoption of these recommendations will enhance AMR data interoperability and help enable its large-scale analyses using computational biology tools, including mathematical modelling and machine learning. We hope that these rules can shed light on often overlooked but nonetheless very necessary aspects of AMR data sharing and enhance the field's ability to address the problems of understanding AMR mechanisms, tracking their emergence and spread in populations, and predicting microbial susceptibility to antimicrobials for diagnostic purposes.
The increasing availability of high-throughput sequencing (frequently termed next-generation sequencing (NGS)) data has created opportunities to gain deeper insights into the mechanisms of a number ...of diseases and is already impacting many areas of medicine and public health. The area of infectious diseases stands somewhat apart from other human diseases insofar as the relevant genomic data comes from the microbes rather than their human hosts. A particular concern about the threat of antimicrobial resistance (AMR) has driven the collection and reporting of large-scale datasets containing information from microbial genomes together with antimicrobial susceptibility test (AST) results. Unfortunately, the lack of clear standards or guiding principles for the reporting of such data is hampering the field's advancement. We therefore present our recommendations for the publication and sharing of genotype and phenotype data on AMR, in the form of 10 simple rules. The adoption of these recommendations will enhance AMR data interoperability and help enable its large-scale analyses using computational biology tools, including mathematical modelling and machine learning. We hope that these rules can shed light on often overlooked but nonetheless very necessary aspects of AMR data sharing and enhance the field's ability to address the problems of understanding AMR mechanisms, tracking their emergence and spread in populations, and predicting microbial susceptibility to antimicrobials for diagnostic purposes.
An ever-increasing demand for novel antimicrobials to treat life-threatening infections caused by the global spread of multidrug-resistant bacterial pathogens stands in stark contrast to the current ...level of investment in their development, particularly in the fields of natural-product-derived and synthetic small molecules. New agents displaying innovative chemistry and modes of action are desperately needed worldwide to tackle the public health menace posed by antimicrobial resistance. Here, our consortium presents a strategic blueprint to substantially improve our ability to discover and develop new antibiotics. We propose both short-term and long-term solutions to overcome the most urgent limitations in the various sectors of research and funding, aiming to bridge the gap between academic, industrial and political stakeholders, and to unite interdisciplinary expertise in order to efficiently fuel the translational pipeline for the benefit of future generations.
Antimicrobial resistance (AMR) is a growing public health threat, estimated to cause over 10 million deaths per year and cost the global economy 100 trillion USD by 2050 under status quo projections. ...These losses would mainly result from an increase in the morbidity and mortality from treatment failure, AMR infections during medical procedures, and a loss of quality of life attributed to AMR. Numerous interventions have been proposed to control the development of AMR and mitigate the risks posed by its spread. This paper reviews key aspects of bacterial AMR management and control which make essential use of data technologies such as artificial intelligence, machine learning, and mathematical and statistical modelling, fields that have seen rapid developments in this century. Although data technologies have become an integral part of biomedical research, their impact on AMR management has remained modest. We outline the use of data technologies to combat AMR, detailing recent advancements in four complementary categories: surveillance, prevention, diagnosis, and treatment. We provide an overview on current AMR control approaches using data technologies within biomedical research, clinical practice, and in the "One Health" context. We discuss the potential impact and challenges wider implementation of data technologies is facing in high-income as well as in low- and middle-income countries, and recommend concrete actions needed to allow these technologies to be more readily integrated within the healthcare and public health sectors.
The relationship between the energy source used by HT-29 cells and their state of differentiation was determined. Short chain fatty acids and acetoacetate were applied to the cells for 9 d, after ...which the medium was replaced with conventional culture medium for a further 9 d so that the permanence of the changes could be assessed (18 d). Glucose utilization and lactic acid, acetoacetate, and β-hydroxybutyrate production by the cells were determined. Differentiation was assessed by the presence of the enzymes sucrase-isomaltase and carbonic anhydrase 1, as well as morphological changes of the cells. By tracing carbon from acetate, propionate, and butyrate through the cells, it was found that the carbon from the short-chain fatty acids was fluxed into acetoacetate. Significant amounts of acetoacetate were released by the propionate-treated culture after 9 d and the acetate-, propionate-, valerate-, and caproate-treated cultures after 18 d. A significant positive correlation was found between acetoacetate synthesis and differentiation. Acetoacetate applied to HT-29 cells also induced their differentiation. The acetate-, butyrate-, valerate-, isovalerate-, and caproate-treated cells underwent terminal differentiation, while the propionate- and isocaproate-treated cultures underwent programming events. We, therefore, conclude that HT-29 cells utilize short chain fatty acids in preference to glucose, metabolize these to ketones, thereby raising the energy state and effecting the observed morphological and functional changes in the cells.
