Measures to eradicate multidrug-resistant organism outbreaks: How much does it cost?

This study aimed to assess the economic burden of infection control measures that succeeded in eradicating multidrug-resistant organisms (MDROs) in emerging epidemic contexts in hospital settings. The MEDLINE, EMBASE and Ovid databases were systematically interrogated for original English-language articles detailing costs associated with strict measures to eradicate MDROs published between 1 January 1974 and 2 November 2014. This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Overall, 13 original articles were retrieved reporting data on several MDROs, including glycopeptide-resistant enterococci (n = 5), carbapenemase-producing Enterobacteriacae (n = 1), methicillin-resistant Staphylococcus aureus (n = 5), and carbapenem-resistant Acinetobacter baumannii (n = 2). Overall, the cost of strict measures to eradicate MDROs ranged from €285 to €57 532 per positive patient. The major component of these overall costs was related to interruption of new admissions, representing €2466 to €47 093 per positive patient (69% of the overall mean cost; range, 13-100%), followed by mean laboratory costs of €628 to €5849 (24%; range, 3.3-56.7%), staff reinforcement costs of €6204 to €148 381 (22%; range, 3.3-52%), and contact precautions costs of €166 to €10 438 per positive patient (18%; range, 0.7-43.3%). Published data on the economic burden of strict measures to eradicate MDROs are limited, heterogeneous, and weakened by several methodological flaws. Novel economic studies should be performed to assess the financial impact of current policies, and to identify the most cost-effective strategies to eradicate emerging MDROs in healthcare facilities

Prediction of microbial communities for urban metagenomics using neural network approach.

BACKGROUND:Microbes are greatly associated with human health and disease, especially in densely populated cities. It is essential to understand the microbial ecosystem in an urban environment for cities to monitor the transmission of infectious diseases and detect potentially urgent threats. To achieve this goal, the DNA sample collection and analysis have been conducted at subway stations in major cities. However, city-scale sampling with the fine-grained geo-spatial resolution is expensive and laborious. In this paper, we introduce MetaMLAnn, a neural network based approach to infer microbial communities at unsampled locations given information reflecting different factors, including subway line networks, sampling material types, and microbial composition patterns. RESULTS:We evaluate the effectiveness of MetaMLAnn based on the public metagenomics dataset collected from multiple locations in the New York and Boston subway systems. The experimental results suggest that MetaMLAnn consistently performs better than other five conventional classifiers under different taxonomic ranks. At genus level, MetaMLAnn can achieve F1 scores of 0.63 and 0.72 on the New York and the Boston datasets, respectively. CONCLUSIONS:By exploiting heterogeneous features, MetaMLAnn captures the hidden interactions between microbial compositions and the urban environment, which enables precise predictions of microbial communities at unmeasured locations

A systematic review of the role of bisphosphonates in metastatic disease

Objectives: To identify evidence for the role of bisphosphonates in malignancy for the treatment of hypercalcaemia, prevention of skeletal morbidity and use in the adjuvant setting. To perform an economic review of current literature and model the cost effectiveness of bisphosphonates in the treatment of hypercalcaemia and prevention of skeletal morbidity Data sources: Electronic databases (1966-June 2001). Cochrane register. Pharmaceutical companies. Experts in the field. Handsearching of abstracts and leading oncology journals (1999-2001). Review methods: Two independent reviewers assessed studies for inclusion, according to predetermined criteria, and extracted relevant data. Overall event rates were pooled in a meta-analysis, odds ratios ( OR) were given with 95% confidence intervals (CI). Where data could not be combined, studies were reported individually and proportions compared using chi- squared analysis. Cost and cost-effectiveness were assessed by a decision analytic model comparing different bisphosphonate regimens for the treatment of hypercalcaemia; Markov models were employed to evaluate the use of bisphosphonates to prevent skeletal-related events (SRE) in patients with breast cancer and multiple myeloma. Results: For acute hypercalcaemia of malignancy, bisphosphonates normalised serum calcium in >70% of patients within 2-6 days. Pamidronate was more effective than control, etidronate, mithramycin and low-dose clodronate, but equal to high dose clodronate, in achieving normocalcaemia. Pamidronate prolongs ( doubles) the median time to relapse compared with clodronate or etidronate. For prevention of skeletal morbidity, bisphosphonates compared with placebo, significantly reduced the OR for fractures (OR [95% CI], vertebral, 0.69 [0.57-0.84], non-vertebral, 0.65 [0.54-0.79], combined, 0.65 [0.55-0.78]) radiotherapy 0.67 [0.57-0.79] and hypercalcaemia 0.54 [0.36-0.81] but not orthopaedic surgery 0.70 [0.46-1.05] or spinal cord compression 0.71 [0.47-1.08]. However, reduction in orthopaedic surgery was significant in studies that lasted over a year 0.59 [0.39-0.88]. Bisphosphonates significantly increased the time to first SRE but did not affect survival. Subanalyses were performed for disease groups, drugs and route of administration. Most evidence supports the use of intravenous aminobisphosphonates. For adjuvant use of bisphosphonates, Clodronate, given to patients with primary operable breast cancer and no metastatic disease, significantly reduced the number of patients developing bone metastases. This benefit was not maintained once regular administration had been discontinued. Two trials reported significant survival advantages in the treated groups. Bisphosphonates reduce the number of bone metastases in patients with both early and advanced breast cancer. Bisphosphonates are well tolerated with a low incidence of side-effects. Economic modelling showed that for acute hypercalcaemia, drugs with the longest cumulative duration of normocalcaemia were most cost-effective. Zoledronate 4 mg was the most costly, but most cost-effective treatment. For skeletal morbidity, Markov models estimated that the overall cost of bisphosphonate therapy to prevent an SRE was pound250 and pound1500 per event for patients with breast cancer and multiple myeloma, respectively. Bisphosphonate treatment is sometimes cost-saving in breast cancer patients where fractures are prevented. Conclusions: High dose aminobisphosphonates are most effective for the treatment of acute hypercalcaemia and delay time to relapse. Bisphosphonates significantly reduce SREs and delay the time to first SRE in patients with bony metastatic disease but do not affect survival. Benefit is demonstrated after administration for at least 6-12 months. The greatest body of evidence supports the use of intravenous aminobisphosphonates. Further evidence is required to support use in the adjuvant setting

The Child is Father of the Man: Foresee the Success at the Early Stage

Understanding the dynamic mechanisms that drive the high-impact scientific work (e.g., research papers, patents) is a long-debated research topic and has many important implications, ranging from personal career development and recruitment search, to the jurisdiction of research resources. Recent advances in characterizing and modeling scientific success have made it possible to forecast the long-term impact of scientific work, where data mining techniques, supervised learning in particular, play an essential role. Despite much progress, several key algorithmic challenges in relation to predicting long-term scientific impact have largely remained open. In this paper, we propose a joint predictive model to forecast the long-term scientific impact at the early stage, which simultaneously addresses a number of these open challenges, including the scholarly feature design, the non-linearity, the domain-heterogeneity and dynamics. In particular, we formulate it as a regularized optimization problem and propose effective and scalable algorithms to solve it. We perform extensive empirical evaluations on large, real scholarly data sets to validate the effectiveness and the efficiency of our method.Comment: Correct some typos in our KDD pape

Public health training in Europe. Development of European masters degrees in public health.

BACKGROUND: Changing political and economic relations in Europe mean that there are new challenges for public health and public health training. There have been several attempts to develop training at the master's level in public health which is focused on meeting the new needs. These have failed due to being too inflexible to allow participation by schools of public health. METHODS: A project funded by the European Union involving public health trainers has developed a new approach which allows participating schools to retain their national differences and work within local rules and traditions, but which aims to introduce the European dimension into public health training. This paper reports the conclusions of this project. CONCLUSIONS: A network of schools wishing to develop European Master's degrees is being established and other schools offering good quality programmes will be able to join