456 research outputs found

    Real Options Theory and EU Member States Energy Investment Strategies

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    According to the European Commission’s latest energy and climate proposals (“Europe 2030”), Member States will be obliged to draft National Action Plans for competitive, secure and sustainable energy. In particular, these plans need to simultaneously address issues of achieving domestic objectives regarding renewable energy, energy savings, energy security, research and innovation, greenhouse gas emissions, nuclear energy, shale gas, carbon capture and storage, European Union level climate and energy objectives etc. Furthermore, coordination with neighboring Member States as well as regional effects will also have to be taken into consideration. Drafting these medium and long-term plans may be a challenging task for the Member States, especially given the uncertainties that the energy sector faces. In this paper, we examine how real options theory can be utilized to formulate these national plans, especially the underlying Member State energy investment strategies, through illustrative examples

    Outcomes of non-invasive diagnostic modalities for the detection of coronary artery disease: network meta-analysis of diagnostic randomised controlled trials

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    Objective: To evaluate differences in downstream testing, coronary revascularisation, and clinical outcomes following non-invasive diagnostic modalities used to detect coronary artery disease. Design: Systematic review and network meta-analysis. Data sources: Medline, Medline in process, Embase, Cochrane Library for clinical trials, PubMed, Web of Science, SCOPUS, WHO International Clinical Trials Registry Platform, and Clinicaltrials.gov. Eligibility criteria for selecting studies: Diagnostic randomised controlled trials comparing non-invasive diagnostic modalities in patients presenting with symptoms suggestive of low risk acute coronary syndrome or stable coronary artery disease. Data synthesis: A random effects network meta-analysis synthesised available evidence from trials evaluating the effect of non-invasive diagnostic modalities on downstream testing and patient oriented outcomes in patients with suspected coronary artery disease. Modalities included exercise electrocardiograms, stress echocardiography, single photon emission computed tomography-myocardial perfusion imaging, real time myocardial contrast echocardiography, coronary computed tomographic angiography, and cardiovascular magnetic resonance. Unpublished outcome data were obtained from 11 trials. Results: 18 trials of patients with low risk acute coronary syndrome (n=11 329) and 12 trials of those with suspected stable coronary artery disease (n=22 062) were included. Among patients with low risk acute coronary syndrome, stress echocardiography, cardiovascular magnetic resonance, and exercise electrocardiograms resulted in fewer invasive referrals for coronary angiography than coronary computed tomographic angiography (odds ratio 0.28 (95% confidence interval 0.14 to 0.57), 0.32 (0.15 to 0.71), and 0.53 (0.28 to 1.00), respectively). There was no effect on the subsequent risk of myocardial infarction, but estimates were imprecise. Heterogeneity and inconsistency were low. In patients with suspected stable coronary artery disease, an initial diagnostic strategy of stress echocardiography or single photon emission computed tomography-myocardial perfusion imaging resulted in fewer downstream tests than coronary computed tomographic angiography (0.24 (0.08 to 0.74) and 0.57 (0.37 to 0.87), respectively). However, exercise electrocardiograms yielded the highest downstream testing rate. Estimates for death and myocardial infarction were imprecise without clear discrimination between strategies. Conclusions: For patients with low risk acute coronary syndrome, an initial diagnostic strategy of stress echocardiography or cardiovascular magnetic resonance is associated with fewer referrals for invasive coronary angiography and revascularisation procedures than non-invasive anatomical testing, without apparent impact on the future risk of myocardial infarction. For suspected stable coronary artery disease, there was no clear discrimination between diagnostic strategies regarding the subsequent need for invasive coronary angiography, and differences in the risk of myocardial infarction cannot be ruled out. Systematic review registration: PROSPERO registry no CRD42016049442

    Prevalence of evidence of inconsistency and its association with network structural characteristics in 201 published networks of interventions

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    BACKGROUND: Network meta-analysis (NMA) has attracted growing interest in evidence-based medicine. Consistency between different sources of evidence is fundamental to the reliability of the NMA results. The purpose of the present study was to estimate the prevalence of evidence of inconsistency and describe its association with different NMA characteristics. METHODS: We updated our collection of NMAs with articles published up to July 2018. We included networks with randomised clinical trials, at least four treatment nodes, at least one closed loop, a dichotomous primary outcome, and available arm-level data. We assessed consistency using the design-by-treatment interaction (DBT) model and testing all the inconsistency parameters globally through the Wald-type chi-squared test statistic. We estimated the prevalence of evidence of inconsistency and its association with different network characteristics (e.g., number of studies, interventions, intervention comparisons, loops). We evaluated the influence of the network characteristics on the DBT p-value via a multivariable regression analysis and the estimated Pearson correlation coefficients. We also evaluated heterogeneity in NMA (consistency) and DBT (inconsistency) random-effects models. RESULTS: We included 201 published NMAs. The p-value of the design-by-treatment interaction (DBT) model was lower than 0.05 in 14% of the networks and lower than 0.10 in 20% of the networks. Networks including many studies and comparing few interventions were more likely to have small DBT p-values (less than 0.10), which is probably because they yielded more precise estimates and power to detect differences between designs was higher. In the presence of inconsistency (DBT p-value lower than 0.10), the consistency model displayed higher heterogeneity than the DBT model. CONCLUSIONS: Our findings show that inconsistency was more frequent than what would be expected by chance, suggesting that researchers should devote more resources to exploring how to mitigate inconsistency. The results of this study highlight the need to develop strategies to detect inconsistency (because of the relatively high prevalence of evidence of inconsistency in published networks), and particularly in cases where the existing tests have low power

    Molecular recognition of N-acetyltryptophan enantiomers by β-cyclodextrin

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    The enantioselectivity of β-cyclodextrin (β-CD) towards L- and D-N-acetyltryptophan (NAcTrp) has been studied in aqueous solution and the crystalline state. NMR studies in solution show that β-CD forms complexes of very similar but not identical geometry with both L- and D-NAcTrp and exhibits stronger binding with L-NAcTrp. In the crystalline state, only β-CD-L-NAcTrp crystallizes readily from aqueous solutions as a dimeric complex (two hosts enclosing two guest molecules). In contrast, crystals of the complex β-CD-D-NAcTrp were never obtained, although numerous conditions were tried. In aqueous solution, the orientation of the guest in both complexes is different than in the β-CD-L-NAcTrp complex in the crystal. Overall, the study shows that subtle differences observed between the β-CD-L,D-NAcTrp complexes in aqueous solution are magnified at the onset of crystallization, as a consequence of accumulation of many soft host-guest interactions and of the imposed crystallographic order, thus resulting in very dissimilar propensity of each enantiomer to produce crystals with β-CD

    Incorporating dose effects in network meta-analysis

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    Systematic reviews with network meta-analysis that ignore potential dose effects could limit the applicability and validity of review findings. This article aims to help content experts (eg, clinicians), methodologists, and statisticians better understand how to incorporate dose effects in network meta-analysis. Three models are described that make different clinical and statistical assumptions about how to model dose effects. This article also illustrates the importance of dose effects in understanding the potential risk of harm in people with dementia from cerebrovascular events associated with atypical antipsychotic drug use (quetiapine, olanzapine, and risperidone) and the potential risk of harm in people with nausea and headache associated with cholinesterase inhibitor use (donepezil, galantamine, and rivastigmine). Finally, important considerations when choosing between different network meta-analysis models incorporating dose effects are discussed

    Contrôle et lutte contre la fraude du patient européen

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    Il est des chiffres qui donnent le vertige. Incontestablement, ceux concernant les pertes dues à la fraude et la corruption en matière de soins en font partie. Certaines estimations font en effet état de 56 milliards d'euros perdus annuellement en Europe, ce qui représente près de 80 millions de perte chaque jour et plus de 5% de l'ensemble des budgets nationaux consacrés à la santé (Gee et alii, 2010)

    The Patterns of High-Level Magnetic Activity Occurring on the Surface of V1285 Aql: The OPEA Model of Flares and DFT Models of Stellar Spots

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    Statistically analyzing Johnson UBVR observations of V1285 Aql during the three observing seasons, both activity level and behavior of the star are discussed in respect to obtained results. We also discuss the out-of-flare variation due to rotational modulation. Eighty-three flares were detected in the U-band observations of season 2006 . First, depending on statistical analyses using the independent samples t-test, the flares were divided into two classes as the fast and the slow flares. According to the results of the test, there is a difference of about 73 s between the flare-equivalent durations of slow and fast flares. The difference should be the difference mentioned in the theoretical models. Second, using the one-phase exponential association function, the distribution of the flare-equivalent durations versus the flare total durations was modeled. Analyzing the model, some parameters such as plateau, half-life values, mean average of the flare-equivalent durations, maximum flare rise, and total duration times are derived. The plateau value, which is an indicator of the saturation level of white-light flares, was derived as 2.421{\pm}0.058 s in this model, while half-life is computed as 201 s. Analyses showed that observed maximum value of flare total duration is 4641 s, while observed maximum flare rise time is 1817 s. According to these results, although computed energies of the flares occurring on the surface of V1285 Aql are generally lower than those of other stars, the length of its flaring loop can be higher than those of more active stars.Comment: 44 pages, 10 figures, 5 tables, 2011PASP..123..659

    Therapeutic Management: When and What

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    Migraine is a widespread brain disease that is classified as the second most disabling condition and has the third highest prevalence of all medical conditions. Despite its non-emergent or life-threatening nature, migraine can progress to chronic type, a subform associated with significant morbidity and drug overuse. In the management of migraine, it is important therefore to introduce early prophylactic treatment in order to limit migraine chronification. In this chapter, we will go through all the treatment options, both acute and preventive, pharmaceutical and non-pharmaceutical following this flowchart: 1. Introduction; 2. General principles; 2.1 Symptomatic therapy; 2.2 Prophylactic management; 3. Pharmaceutical therapies; 3.1 Symptomatic; 3.1.1 Disease-specific; 3.1.2 No disease-specific; 3.2 Prophylactic; 3.2.1 Disease-specific; 3.2.2 No disease-specific; 3.3 Non-Pharmaceutical therapies; 3.4 Neuromodulation; 3.4.1 Invasive; 3.4.5 Non-invasive; 3.5 Nutrient (nutraceuticals); 3.6 Dietary interventions; 3.7 Acupuncture; 3.8 Physical therapy; 4. Cognitive behavioral therapies; 5. Patient centricity and patient education
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