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Graphical abstract Fx1, Objetivo: Evaluar si el uso de corticoesteroides (Cs) se asocia con la mortalidad en la unidad de cuidados intensivos (UCI) en la población global y dentro de los fenotipos clínicos predeterminados Diseño: Análisis secundario de estudio multicéntrico observacional Ámbito: UCI Pacientes: Pacientes adultos con COVID-19 confirmado ingresados en 63 UCIs de España Intervención: Corticoides vs. no Corticoides Variables de interés principales: A partir del análisis no supervisado de grupos, 3 fenotipos clínicos fueron derivados y clasificados como: A: grave, B: critico and C: potencialmente mortal. Se efectuó un análisis multivariado después de un propensity optimal full matching (PS) y una regresión ponderada de Cox (HR) y análisis de Fine-Gray (sHR) para evaluar el impacto del tratamiento con Cs sobre la mortalidad en la población general y en cada fenotipo clínico. Resultados: Un total de 2.017 pacientes fueron analizados, 1.171(58%) con Cs. Después del PS, el uso de Cs no se relacionó significativamente con la mortalidad en UCI (OR:1.0,95%CI:0.98-1.15). Cs fueron administrados en 298/537(55.5%) pacientes del fenotipo “A” y no se observó asociación significativa con la mortalidad (HR=0.85[0.55-1.33]). Un total de 338/623(54.2%) pacientes del fenotipo “B” recibieron Cs sin efecto significativo sobre la mortalidad (HR=0.72[0.49-1.05]). Finalmente, 535/857(62.4%) pacientes del fenotipo “C” recibieron Cs. En este fenotipo, se evidenció un efecto protector de los Cs sobre la mortalidad HR (0.75[0.58-0.98]). Conclusión: Nuestros hallazgos alertan sobre el uso indiscriminado de Cs a dosis moderadas en todos los pacientes críticos con COVID-19. Solamente pacientes con elevado estado de inflamación podrían beneficiarse con el tratamiento con Cs.

Background More than 20% of hospitalized patients with COVID-19 demonstrate ARDS requiring ICU admission. The long-term respiratory sequelae in such patients remain unclear. Research Question What are the major long-term pulmonary sequelae in critical patients who survive COVID-19? Study Design and Methods Consecutive patients with COVID-19 requiring ICU admission were recruited and evaluated 3 months after hospitalization discharge. The follow-up comprised symptom and quality of life, anxiety and depression questionnaires, pulmonary function tests, exercise test (6-min walking test [6MWT]), and chest CT imaging. Results One hundred twenty-five patients admitted to the ICU with ARDS secondary to COVID-19 were recruited between March and June 2020. At the 3-month follow-up, 62 patients were available for pulmonary evaluation. The most frequent symptoms were dyspnea (46.7%) and cough (34.4%). Eighty-two percent of patients showed a lung diffusing capacity of less than 80%. The median distance in the 6MWT was 400 m (interquartile range, 362-440 m). CT scans showed abnormal results in 70.2% of patients, demonstrating reticular lesions in 49.1% and fibrotic patterns in 21.1%. Patients with more severe alterations on chest CT scan showed worse pulmonary function and presented more degrees of desaturation in the 6MWT. Factors associated with the severity of lung damage on chest CT scan were age and length of invasive mechanical ventilation during the ICU stay. Interpretation Three months after hospital discharge, pulmonary structural abnormalities and functional impairment are highly prevalent in patients with ARDS secondary to COVID-19 who required an ICU stay. Pulmonary evaluation should be considered for all critical COVID-19 survivors 3 months after discharge.

In this work we provide a perspective on Process Systems Engineering (PSE) in the context of sustainability, reviewing the main tools available and describing major applications in sustainability problems spanning multiple scales, from molecules, through chemical plants, and finally the enterprise and macroeconomic levels. After highlighting the potential role of PSE in meeting the UN Sustainable Development Goals, we discuss future research directions, focusing on major modelling and algorithmic challenges along with the trend to explore new application domains beyond chemical engineering while still revisiting problems within the core discipline.

Biomass resources offer a very promising alternative to fossil fuels for the sustainable production of electricity, fuels, and chemicals. Nevertheless, the problem of deciding on the best use of bi...

The authors would like to acknowledge funding from the Research Councils UK under grants EP/N024567/1 (CCS from Industrial clusters and their Supply chains), NE/P019900/1 (Comparative assessment and region-specific optimisation of GGR) and EP/T033940/1 (Multiphysics and multiscale modelling for safe and feasible CO2 capture and storage).

The newborn screening program in Ecuador has been operating since 2011 under the responsibility of the Ministry of Health. This program is centralized and diagnoses four diseases: congenital hypothyroidism, phenylketonuria, galactosemia, and congenital adrenal hyperplasia. This study aimed to assess the geographical distribution of newborn screening cases in Ecuador. Spatial analysis techniques were applied using the records of the National Newborn Screening Program with a congenital disease confirmed from January 2012 to December 2019. Morbidity rates per 100,000 were calculated by newborn screening disease detected and the province of birth, posteriorly, the map of its distribution was graphed and assessed using the QGIS 3.12 software. In total, 393 cases born confirmed between 2012 and 2019 were registered. The distribution of every disease tends to be different in all provinces in Ecuador; the spatial variation was significant and relative rates showed a higher incidence in some eastern provinces. In conclusion, we found a different distribution and rates of newborn screening disorders in Ecuador. The high incidence of congenital hypothyroidism, phenylketonuria, galactosemia, and congenital adrenal hyperplasia in some areas should be investigated, due could be related to ethnic, genetic, and cultural aspects of the population.

Meeting the sustainable development goals and carbon neutrality targets requires transitioning to cleaner products, which poses significant challenges to the future chemical industry. Identifying alternative pathways to cover the growing demand for chemicals and fuels in a more sustainable manner calls for close collaborative programs between experimental and computational groups as well as new tools to support these joint endeavours. In this broad context, we here review the role of process systems engineering tools in assessing and optimising alternative chemical production patterns based on renewable resources, including renewable carbon and energy. The focus is on the use of process modelling and optimisation combined with life cycle assessment methodologies and network analysis to underpin experiments and generate insight into how the chemical industry could optimally deliver chemicals and fuels with a lower environmental footprint. We identify the main gaps in the literature and provide directions for future work, highlighting the role of PSE concepts and tools in guiding the future transition and complementing experimental studies more effectively., Reaction Chemistry & Engineering, 6 (7), ISSN:2058-9883

The petrochemical sector will play a crucial role in developing low-carbon transition technologies, but the industry also contributes a significant proportion of greenhouse gas emissions. Momentum is building to help reduce the carbon footprint of this hard-to-abate sector, particularly through replacing fossil carbon feedstocks with carbon from biomass, captured CO2, and other recycled resources, but the broader implications of these so-called “solutions” remain unclear. Here, we assess the overall sustainability of such “renewable carbon pathways” by quantifying their life-cycle environmental footprints with respect to the previously defined nine planetary boundaries. We show that although a shift toward renewable carbon pathways could indeed reduce CO2 emissions by 25% to over 100%, the scenario with the lowest carbon footprint could exceed the biodiversity planetary boundary by at least 30%. Our work highlights the potential pitfalls of overlooking global environmental guardrails beyond greenhouse gas emissions reduction and identifies new avenues for quantifying the environmental footprint of decarbonization solutions for hard-to-abate sectors., One Earth, 4 (4), ISSN:2590-3322

© 2020 The Author(s)., [Purpose]: The DIANA study aimed to evaluate how often antimicrobial de-escalation (ADE) of empirical treatment is performed in the intensive care unit (ICU) and to estimate the effect of ADE on clinical cure on day 7 following treatment initiation., [Methods]: Adult ICU patients receiving empirical antimicrobial therapy for bacterial infection were studied in a prospective observational study from October 2016 until May 2018. ADE was defined as (1) discontinuation of an antimicrobial in case of empirical combination therapy or (2) replacement of an antimicrobial with the intention to narrow the antimicrobial spectrum, within the first 3 days of therapy. Inverse probability (IP) weighting was used to account for time-varying confounding when estimating the effect of ADE on clinical cure., [Results]: Overall, 1495 patients from 152 ICUs in 28 countries were studied. Combination therapy was prescribed in 50%, and carbapenems were prescribed in 26% of patients. Empirical therapy underwent ADE, no change and change other than ADE within the first 3 days in 16%, 63% and 22%, respectively. Unadjusted mortality at day 28 was 15.8% in the ADE cohort and 19.4% in patients with no change [p = 0.27; RR 0.83 (95% CI 0.60–1.14)]. The IP-weighted relative risk estimate for clinical cure comparing ADE with no-ADE patients (no change or change other than ADE) was 1.37 (95% CI 1.14–1.64)., [Conclusion]: ADE was infrequently applied in critically ill-infected patients. The observational effect estimate on clinical cure suggested no deleterious impact of ADE compared to no-ADE. However, residual confounding is likely.

The global food system inextricably connects human health and environmental integrity. It holds the transformative capability to significantly reduce levels of environmental degradation, caused by current food production practices, and alleviate the ‘triple burden’ of malnutrition, existing due to food consumption patterns. System-wide transitions are therefore paramount to tackling environmental and nutritional challenges that are exacerbated by a rapidly growing population. This work presents a novel application of Data Envelopment Analysis (DEA) to study the sustainability of food supply patterns around the world and appraise the potential to lower environmental pressure without compromising the supply of calories and nutritional quality. By relating environmental impacts to caloric availability and nutritional adequacy, DEA computes a relative performance score for 139 countries and identifies only 18 countries with per capita food supplies that are ‘efficient’ in transforming five environmental inputs (land use, greenhouse gas emissions, acidification potential, eutrophication potential and freshwater withdrawals) into calories and nutrition. The widespread extent of ‘inefficiency’ stresses that the significant opportunity and need to reduce environmental impacts from food is truly global and extensive. Results of this analysis also provide quantitative information on the varying degrees of potential to improve the ways in which each nation's population is fed and therefore offers country-specific insight for decision-makers into the integration of environmental and nutritional outcomes for sustainable development., Science of The Total Environment, 755 (Part 1), ISSN:0048-9697, ISSN:1879-1026

Assessing the footprint of anthropogenic activities has become particularly challenging in today's globalized markets, where a large number of economic transactions taking place across the globe need to be disentangled before the most critical sectors are identified. In this work, we present an approach to quantify the eco-efficiency of economic activities that combines multi-regional environmentally-extended input-output tables and data envelopment analysis. We employ this method to assess the European Union manufacturing sectors in terms of three inputs -global warming potential, potential acidifying equivalent and tropospheric ozone forming potential- and one output (economic wealth), following both production and consumption-based accounting approaches. Our approach classifies economic sectors as efficient and inefficient, and for the latter it provides improvement targets that if attained would make them efficient. We find that there is a significant mismatch at the sectorial level between both accounting schemes, each providing complementary information for policy-making. In the production-based case, targets allow identifying sectors and pollutants requiring more stringent regulations and/or higher investments in cleaner technologies. Conversely, the consumption-based accounting allows identifying the ultimate sources of impact, an insight that can assist in the selection of alternative “cleaner” suppliers via eco-labelling of products/services and proper taxation schemes.

The difficulties in climate change negotiations together with the recent withdrawal of the U.S. from the Paris Agreement call for new cooperative mechanisms to enable a resilient international response. In this study we propose an approach to aid such negotiations based on quantifying the benefits of interregional cooperation and distributing them among the participants in a fair manner. Our approach is underpinned by advanced optimisation techniques that automate the screening of millions of alternatives for differing levels of cooperation, ultimately identifying the most cost-effective solutions for meeting emission targets. We apply this approach to the Clean Power Plan, a related act in the U.S. aiming at curbing carbon emissions from electricity generation, but also being withdrawn. We find that, with only half of the states cooperating, the cost of electricity generation could be reduced by US$41 billion per year, while simultaneously cutting carbon emissions by 68% below 2012 levels. These win–win scenarios are attained by sharing the emission targets and trading electricity among the states, which allows exploiting regional advantages. Fair sharing of dividends may be used as a key driver to spur cooperation since the global action to mitigate climate change becomes beneficial for all participants. Even if global cooperation remains elusive, it is worth trying since the mere cooperation of a few states leads to significant benefits for both the U.S. economy and the climate. These findings call on the U.S. to reconsider its withdrawal but also boost individual states to take initiative even in the absence of federal action., Energy & Environmental Science, 11 (3), ISSN:1754-5692, ISSN:1754-5706

Although various Heat Exchanger Network (HEN) synthesis methods have been proposed in the literature, fundamental study for addressing uncertainties arisen from market fluctuations using stochastic variables and parameters is scarce. Such feature certainly adds difficulties to a problem already not straightforward to solve. In that manner, this work adapts a meta-heuristic approach to be able to efficiently perform such task. Uncertainties are assumed from variations in costs of commodities related to production of utilities. Several forecast scenarios are generated via Monte Carlo Simulation in order to obtain discretized distributions for the uncertain variables. Five financial risk metrics are applied for risks management. Each metric is formulated as secondary function to expected total annual costs (ETAC) in a multi-objective optimization (MOO) model with two objective functions. A benchmark case study is adapted in order to demonstrate the method reliability. The approach is able to achieve results that fit for different types of investors ( e.g. , risk-averse, risk-taker), handling uncertainty by efficiently performing trade-offs in heat exchange areas and utilities requirement.

The combined use of data envelopment analysis (DEA) and life cycle assessment (LCA) has recently emerged as a suitable technique for assessing the environmental efficiency of products. The standard approach DEA + LCA requires the input/output data to be perfectly known in advance. In practice, however, the environmental impact calculations are typically affected by a high degree of uncertainty stemming from lack of data and/or inaccurate measurements. This contribution introduces a methodology that combines DEA, LCA and stochastic modelling to evaluate the environmental efficiency of products under uncertainty. The capabilities of this approach are illustrated through its application to the assessment of eleven technologies for electricity generation. We show that the efficiency scores in the nominal and the stochastic cases can differ significantly, to the point that a technology can be deemed efficient or inefficient depending on the values of the uncertain parameters. These results support the need to incorporate uncertainty modeling into the DEA + LCA framework in order to further assess the validity of the deterministic calculations.

Cryogenic air separation to produce nitrogen, oxygen and argon with high quality requirements is an energy-intensive industrial process that requires large quantities of electricity. The complexity in operating these networks stems from the volatile conditions, namely electricity prices and products demands, which vary every hour, creating a clear need for computer-aided tools to attain economic and energy savings. In this article, we present a multiperiod mixed-integer linear programming (MILP) model to determine the optimal production schedule of an industrial cryogenic air separation process so as to maximize the net profit by minimizing energy consumption (which is the main contributor to the operating costs). The capabilities of the model are demonstrated by means of its application to an existing industrial process, where significant improvements are attained through the implementation of the MILP.

The concept of circular economy has gained wide interest in industry as a powerful strategy to reduce impacts while remaining economically competitive. Here, we explore the benefits of this approach in the chemical industry, quantifying explicitly the economic and environmental benefits of ethylene recovery from polyethylene plastics using process modeling coupled with Life Cycle Assessment (LCA). Our results show that the recovered ethylene represents a win-win alternative, offering a highly competitive cost of 0.386 €/kg vs 0.835 €/ kg with the standard naphtha-based route. Furthermore, substantial reductions of as much as 87%, 89%, and 164% could also be attained (compared to the naphtha-based ethylene) in impacts on human health, ecosystem quality, and resources scarcity, respectively. Overall, this work aims to promote the adoption of circular economy strategies in the chemical sector, while highlighting the role of process modeling, LCA, and systems thinking in quantifying the associated benefits to build strong cases for policymaking.

The development of sustainable products and processes has recently gained wide interest in the chemical industry. Here, we review the application of the life cycle optimization framework to chemical systems, where the key idea is to combine life cycle assessment (LCA) with multiobjective optimization (MOO) so as to identify solutions attaining simultaneously economic and environmental benefits. We introduce the fundamentals of this method and highlight its capabilities in three examples at various spatial and temporal scales, i.e., the sustainable design of hydrogen supply chains and process flowsheets and the environmental assessment of chemicals. We argue that the combined use of MOO and LCA will play a key role in the transition to a more sustainable chemical industry, yet we identify methodological and practical issues that still need to be resolved for its widespread use in industry.

Thermal insulation based on biomaterials with low energy embodied is a promising alternative to reduce the energy demand of the actual building stock and help meeting the climatic 2050 EU goals. Despite their appealing properties, these materials are not widely available in the insulation market for a variety of reasons such as a more laborious implementation compared to commercial alternatives. To overcome this limitation and change this trend, this work introduces a systematic method to generate efficient combinations of biomaterials with reduced cost and environmental impacts that could be manufactured as commercial sandwich or solid panels and fiber mats.

University rankings have become an important tool to compare academic institutions within and across countries. Yet, they rely on aggregated scores based on subjective weights which render them sensitive to experts’ preferences and not fully transparent to final users. To overcome this limitation, we apply Data Envelopment Analysis (DEA) to evaluate UK universities in the field of chemical engineering as a case study, using data retrieved from two national rankings. DEA is a non-parametric approach developed for the multi-criteria assessment of entities that avoids the use of subjective weightings and aggregated scores; this is accomplished by calculating an efficiency index, on the basis of which universities can be classified as either ‘efficient’ or ‘inefficient’. Our analysis shows that the Higher Education Institutions (HEI) occupying the highest positions in the chemical engineering rankings might not be the most efficient ones, and vice versa, which highlights the need to complement the use of rankings with other analytical tools. Overall, DEA provides further insight into the assessment of HEIs, allowing institutions to better understand their weaknesses and strengths, while pinpointing sources of inefficiencies where improvement efforts must be directed.

Time to clearance of pathogens is probably critical to outcome in septic shock. Current guidelines recommend intervention for source control within 12 hours after diagnosis. We aimed to determine the epidemiology of source control in the management of sepsis and to analyze the impact of timing to source control on mortality.Prospective observational analysis of the Antibiotic Intervention in Severe Sepsis study, a Spanish national multicenter educational intervention to improve antibiotherapy in sepsis.Ninety-nine medical-surgical ICUs in Spain.We enrolled 3,663 patients with severe sepsis or septic shock during three 4-month periods between 2011 and 2013.Source control and hospital mortality.A total of 1,173 patients (32%) underwent source control, predominantly for abdominal, urinary, and soft-tissue infections. Compared with patients who did not require source control, patients who underwent source control were older, with a greater prevalence of shock, major organ dysfunction, bacteremia, inflammatory markers, and lactic acidemia. In addition, compliance with the resuscitation bundle was worse in those undergoing source control. In patients who underwent source control, crude ICU mortality was lower (21.2% vs 25.1%; p = 0.010); after adjustment for confounding factors, hospital mortality was also lower (odds ratio, 0.809 [95% CI, 0.658-0.994]; p = 0.044). In this observational database analysis, source control after 12 hours was not associated with higher mortality (27.6% vs 26.8%; p = 0.789).Despite greater severity and worse compliance with resuscitation bundles, mortality was lower in septic patients who underwent source control than in those who did not. The time to source control could not be linked to survival in this observational database.

Methanol from captured CO2 provides a more sustainable alternative to gasoline due to its low carbon footprint, yet it requires a large amount of renewable energy that could be used instead to decarbonise the electricity mix. A techno-economic and environmental analysis of methanol produced from captured CO2 and renewable energy is conducted to shed light on the transportation-power nexus. The investigated scenarios differ in how the carbon-free energy source – electricity from wind – is used to either decarbonise the electricity mix or produce green methanol to displace conventional fossil fuels. The assessment is carried out for six countries that differ in the composition of their electricity mix and gasoline consumption. The results of this holistic assessment show that, at present, decarbonising the electricity grid using renewable energy sources and carbon capture and storage would offer greater environmental benefits, without incurring large changes in direct economic costs, compared to producing methanol from the hydrogenation of captured CO2. Though this insight might change in the future if the carbon intensity of the mix is reduced and green methanol becomes cheaper, it highlights the need to consider the transportation-power nexus in assessing alternative fuels and thereby prevent shifting of emissions from one sector to another over their life cycle.

Correction for ‘Powering sustainable development within planetary boundaries’ by Ibrahim M. Algunaibet et al., Energy Environ. Sci., 2019, 12, 1890–1900., Energy & Environmental Science, 12 (12), ISSN:1754-5692, ISSN:1754-5706

Life cycle assessment (LCA) has become the prevalent approach for quantifying the environmental impact of products over their entire life cycle. Unfortunately, LCA studies require large amounts of data that are difficult to collect in practice, which makes them expensive and time consuming. This work introduces a method that simplifies standard LCA studies by using proxy metrics that are identified following a systematic approach. Our method, which combines multi-linear regression and mixed-integer linear programming, builds in an automatic manner simplified multi-linear regression models of impact that predict (with high accuracy) the damage in different environmental categories from a reduced number of proxy metrics. Our approach was applied to data retrieved from ecoinvent. Numerical results show that few indicators suffice to describe the environmental performance of a process with high accuracy. Our findings will help develop general guidelines for simplified LCA studies that will focus on quantifying a reduced number of key indicators.

The new European Union’s Common Agricultural Policy will cover the period from 2015 to 2020. Significant novelties in the payment scheme have been introduced which may potentially encourage farmers to implement changes at the farm level by meeting certain environmental requirements in return for support payments. The mandatory requirements, commonly known as ‘greening rules’, consist of crop diversification, maintenance of permanent grassland and establishment of an ecological focus area. This paper presents a decision-support tool based on a multi-stage linear programming model that identifies optimal cropping plan decisions under the new Common Agricultural Policy. The capabilities of our tool are illustrated through its application to the Spanish agricultural regions. Our method identifies the optimal cropping plan (i.e., crops to be grown and their acreage each year during the reform horizon) that maximizes the farmer’s net return in each region. Furthermore, the model can also be used to calculate the minimum subsidy value that would make the implementation of greening rules economically appealing, thereby promoting the widespread adoption of more sustainable agricultural practises.

Mucormycosis is usually an acute angioinvasive infections, which leads to non-suppurative necrosis and significant tissue damage. It represents 1.6% of all the invasive fungal infections and predominates in immunosuppressed patients with risk factors. Incidence has been significantly increased even in immunocompetent patients. Due to finding a case of disseminated mucormycosis caused by Rhizomucor pusillus in a young immunocompetent patient, a systematic review was carried out of reported cases in PubMed of mucormycosis in immunocompetent adults according to the main anatomic locations, and especially in disseminated cases. A review of the main risk factors and pathogenicity, clinical manifestations, techniques of early diagnosis, current treatment options, and prognosis is presented. Taxonomy and classification of the genus Mucor has also been reviewed.

Policies are encouraging to reduce emissions in all sectors, due to the high energy demand during the life cycle of the processes. Constructions are not an exception and policies are encouraging to reduce energy demand in buildings. Although new constructions are reducing their energy demand according to new directives, without interventions in the actual building stock, the European goals proposed for 2050 cannot be achieved. Insulation is known to achieve an important reduction in the energy demand in the operation phase of the buildings. Despite that, this implementation carries out an initial investment in both, cost and impact, which suggest that using low embodied materials, such us bio-based materials, could improve this solution. Despite their good thermal properties, these new materials are not arriving at the actual market for insulators. In order to improve this scalability, an evaluation of the efficiency of different materials is carried out, with a following combination of the efficient materials in order to generate new hybrid solutions. These hybrid materials cope to simplify the applicability of bio-based materials, generating sandwich panels or combined mats to generate materials similar to the commercialized ones which have an increasing market nowadays. The methodology presented combines Data Envelopment Analysis (DEA) and Building modelling simulation. Using thermal simulations of EnergyPlus and the evaluation of efficiency and further projections of DEA. Seven bio-based materials and polyurethane for comparison have been studied, with a thickness that varies from 1 cm and 26 cm in increments of 5 cm. DEA analysis is used to quantify the efficiency score of the different thicknesses of the materials. The non-efficient materials are projected to this frontier, achieving a combination of materials. Those combinations have been analysed in order to model only the feasible solutions, which have proved to achieve efficiency in all the combinations proposed.

Resumen Antecedentes Las mucormicosis son infecciones poco frecuentes en pacientes inmunocompetentes, y se han descrito muy pocos casos de mucormicosis asociadas a aspergilosis en pacientes no hematologicos. Caso clinico Un varon de 17 anos, inmunocompetente y sin factores de riesgo previamente conocidos, ingreso en el hospital tras presentar crisis convulsivas 11 dias despues de sufrir un accidente de moto. Presento un curso clinico torpido por infeccion fungica invasiva mixta, con afectacion pulmonar por Aspergillus niger y mucormicosis diseminada por Rhizomucor pusillus (diagnostico histopatologico y microbiologico en varios lugares no contiguos). Fue tratado con anfotericina B liposomal durante 7 semanas (dosis total acumulada > 10 g) y preciso multiples reintervenciones quirurgicas. El paciente sobrevivio y fue dado de alta de UCI tras 5 meses de evolucion y multiples complicaciones. Conclusiones El tratamiento con anfotericina B liposomal y el manejo quirurgico agresivo consiguio la erradicacion de la infeccion fungica invasiva mixta, pero alertamos de la necesidad de mantener un mayor grado de sospecha clinica y de realizar tecnicas de diagnostico precoz de infecciones fungicas invasivas en pacientes no inmunodeprimidos para evitar la diseminacion de la enfermedad y el mal pronostico asociado.

Assessing the sustainability level of the power sector can aid the transition towards a sustainable energy system. In this contribution, we propose a novel approach to compare and optimize electricity mixes according to sustainability criteria and apply it to the 28 EU members. Our method combines life cycle assessment, data envelopment analysis (DEA) and rigorous mathematical programming tools in three main steps. Firstly, DEA is applied to assess the efficiency level of electricity mixes of EU member countries considering the three dimensions of sustainability. Then, electricity portfolios of inefficient countries are optimized by solving a model that seeks to attain the targets provided by DEA while simultaneously considering the technical aspects governing electricity generation. This model, which constitutes the cornerstone of our approach, complements standard DEA by ensuring realistic and meaningful targets. In the third step, we evaluate the electricity portfolios optimized previously by running DEA again. Our results suggest that energy policies in the EU should favor the deployment of hydropower, wind and solar, while simultaneously displacing non-renewable sources and bioenergy. The deployment of carbon capture and storage is also a potential alternative that could be incentivized via policies worded in terms of carbon intensity targets.

Cryogenic air separation technology is used to produce large amounts of technical gases with high purity levels. It is an industrial energy-intensive technology consuming high volumes of electricity. The complexity in operating air separation processes increases since the volatile conditions (i.e., electricity prices and product demand) can hourly change. Thus, the use of computer-aided tools to obtain energy and economic savings becomes crucial. In this paper, we state a multiperiod and multiproduct mixed-integer linear programming (MILP) model to determine the optimal production schedule of an industrial cryogenic air separation process. The MILP model contributes to minimize the energy consumption in the network whereas the net profit is maximized. The model capabilities are developed and validated using an existing air separation plant.

Multi-objective optimization (MOO) has recently attracted an increasing interest in environmental engineering. One major limitation of the existing solution methods for MOO is that their computational burden tends to grow rapidly in size with the number of environmental objectives. In this paper, we study the use of Principal Component Analysis (PCA) to identify redundant environmental metrics in MOO that can be omitted without disturbing the main features of the problem, thereby reducing the associated complexity. We show that, besides its numerical usefulness, the use of PCA coupled with MOO provides valuable insights on the relationships between environmental indicators of concern for decision-makers. The capabilities of the proposed approach are illustrated through its application to the design of environmentally conscious chemical supply chains (SCs).

Antecedentes: En las ultimas 3 decadas se ha observado un incremento significativo de la enfermedad fungica invasora producida por Candida en pacientes criticos no neutropenicos. El fluconazol y la anfotericina B se han considerado tratamientos de primera linea de la enfermedad (probada y probable) producida por Candida, aunque la mortalidad sigue siendo muy elevada. Objetivo: Revisar el uso de la micafungina en el tratamiento de la enfermedad fungica invasora producida por Candida en pacientes criticos no neutropenicos. Metodo: Valorar el uso clinico y la eficacia de la micafungina en estos pacientes, a partir de sus propiedades farmacologicas, micologicas y de los resultados clinicos de los estudios publicados. Resultados y conclusiones: Actualmente es necesario reducir la mortalidad utilizando antifungicos mas eficaces e instaurando tratamientos mas precoces. Las candinas parecen obtener resultados mejores en el tratamiento de enfermedad invasora por Candida en pacientes criticos. La micafungina es eficaz y tiene un perfil de seguridad semejante al fluconazol, es una opcion de primera linea para el tratamiento de la candidemia y/o de las candidiasis invasoras, y puede utilizarse en el tratamiento anticipado seguido de una estrategia de desescalada con azoles.

With the recent trend of moving towards a more sustainable economy, the interest on designing buildings with lower cost and environmental impact has grown significantly. In this context, multi-objective optimization has attracted much attention in building design as a tool to study trade-off solutions (“cost” vs “environmental impact”) resulting from the optimization of conflicting objectives. One major limitation of this approach (as applied to building design) is that it is computationally demanding due to the need to optimize several objectives using complex models based on differential equations (which are used to estimate the energy consumed by a building). In this work, we propose a systematic framework for the design of buildings that combines a rigorous objective reduction method (which removes redundant objectives from the analysis) with a surrogate model (which simplifies the calculation of the energy requirements of the building), both of which expedite the identification of alternative designs leading to environmental improvements. The capabilities of our methodology are illustrated through a case study based on a thermal modelling of a house-like cubicle, in which we optimize the insulation thicknesses of the building envelope. Results show that significant economic and environmental improvements can be achieved compared to the base case (cubicle without insulation). Furthermore, it is clearly illustrated how the minimization of an aggregated environmental metric, like the Eco-Indicator 99, as unique environmental objective may overlook some Pareto solutions that may be appealing for decision-makers. The authors would like to acknowledge financial support from the Spanish Government (ENE2015-64117-C5-3-R (MINECO/FEDER, UE)). Joan Carreras would also like to acknowledge financial support from the Pump-Priming Research Programs of The University of Manchester.

This work addresses the optimization of supply and distribution chains considering the effect that equipment aging can cause over the performance of the facilities involved in the process. The decaying performance of the facilities is modeled as an exponential equation, thus giving rise to a novel MINLP formulation. The capabilities of the proposed approach have been tested through its application to a case study considering a simplification of the Spanish natural gas network. Results demonstrate that overlooking the effect of equipment aging can lead to infeasible solutions in practice and show how the proposed model allows overcoming such limitations thus becoming a practical tool to support the decision-making process in the distribution sector.

Many energy strategies can be applied to a building to improve its energy efficiency without compromising comfort. The analysis becomes more complex when considering not only the energetic improvement but also the corresponding economic cost and especially when considering its multiple environmental impacts. This study presents a methodology for determining the optimal insulation thickness for external building surfaces. As a case study, we model a cubicle like building. It is representative for a conventional Mediterranean construction system and is situated in Lleida, representing a moderate climate in Spain. Our approach is based on a multi-objective optimization model that minimizes simultaneously the cost and eleven environmental impact indicators associated with both the energy consumption over the operational phase and the construction materials used (including the waste produced during the disposal phase). To simplify the problem we reduce the dimensionality of the multi-objective optimization problem identifying and removing in a systematic manner redundant criteria from the mathematical model. To accelerate the optimization analysis we apply a surrogate model which provides the global prediction of the objective functions, and an evaluation of uncertainty of the prediction of this model. Results show that this approach represents a practical tool for performing the dimensionality reduction of criteria and the acceleration of building design optimization through the use of a surrogate model.

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works Although design is a problem that has been addressed in the literature, maintaining, upgrading and expanding energy distribution networks along the entire life-cycle is a topic that has received scarce attention. The problem includes considering the long-term dependence of the efficiency of the investments along their life span. This work presents a novel model for the optimization of energy distribution networks considering the decaying performance caused by equipment aging. Increasing maintenance costs have been included to model the decaying performance, thus giving rise to an MINLP formulation. A simplified case study based on a real electricity distribution network has been used as a test bed for the proposed approach. Results show that unrealistic sizing and planning solutions are obtained when the decaying performance is not considered and demonstrate that the proposed MINLP overcomes such limitations.

This study assessed the risk of haematological, renal and hepatic toxicity associated with amphotericin B lipid complex (ABLC; Abelcet) in a multicentre, open-label, non-comparative study of 93 patients from 17 different hospitals who received ABLC because of proven or suspected systemic fungal infection or leishmaniasis. Most (66%) patients had onco-haematological diseases. Optimum treatment with ABLC comprised a slow (2-h) infusion dose of 5 mg/kg/day for a minimum period of 14 days. Biochemical and haematological parameters were measured pre-, during and post-treatment. In the overall patient group, the mean serum creatinine concentration was similar pre- and post-study (1.00 ± 1.14 mg/dL vs. 1.20 ± 1.19 mg/dL; p > 0.05). There were no significant changes pre- and post-treatment in concentrations of haemoglobin, potassium, transaminases and bilirubin. There was no significant correlation between the dose administered and the concentrations of serum creatinine (Spearmann 0.22). There was no greater nephrotoxicity in the patients with previous renal failure, or in those who had received amphotericin B previously. There were serious adverse events in five patients, but other alternative causes that could explain these events were present in three of these patients. Fevers or chills were experienced by 23% of the patients during the ABLC infusion, but only in one case did this necessitate the suspension of treatment. It was concluded that ABLC is a drug with low nephrotoxicity, even when administered to patients with pre-existing renal insufficiency. Adverse events were generally slight or moderate, and were managed easily with appropriate pre-medication.

Background Although there has been an improved management of invasive candidiasis in the last decade, still controversial issues remain, especially in different therapeutic critical care scenarios. Aims We sought to identify the core clinical knowledge and to achieve high agreement recommendations required to care for critically ill adult patients with invasive candidiasis for antifungal treatment in special situations and different scenarios. Methods Second prospective Spanish survey reaching consensus by the DELPHI technique, conducted anonymously by electronic e-mail in the first phase to 23 national multidisciplinary experts in invasive fungal infections from five national scientific societies including intensivists, anesthesiologists, microbiologists, pharmacologists and infectious disease specialists, answering 30 questions prepared by a coordination group after a strict review of literature in the last five years. The educational objectives spanned four categories, including peritoneal candidiasis, immunocompromised patients, special situations, and organ failures. The agreement among panelists in each item should be higher than 75% to be selected. In a second phase, after extracting recommendations from the selected items, a meeting was held with more than 60 specialists in a second round invited to validate the preselected recommendations. Measurements and main results In the first phase, 15 recommendations were preselected (peritoneal candidiasis (3), immunocompromised patients (6), special situations (3), and organ failures (3)). After the second round the following 13 were validated: Peritoneal candidiasis (3): Source control and early adequate antifungal treatment is mandatory; empirical antifungal treatment is recommended in secondary nosocomial peritonitis with Candida spp. colonization risk factors and in tertiary peritonitis. Immunocompromised patients (5): consider hepatotoxicity and interactions before starting antifungal treatment with azoles in transplanted patients; treat candidemia in neutropenic adult patients with antifungal drugs at least 14 days after the first blood culture negative and until normalization of neutrophils is achieved. Caspofungin, if needed, is the echinocandin with most scientific evidence to treat candidemia in neutropenic adult patients; caspofungin is also the first choice drug to treat febrile candidemia; in neutropenic patients with candidemia remove catheter. Special situations (2): in moderate hepatocellular failure, patients with invasive candidiasis use echinocandins (preferably low doses of anidulafungin and caspofungin) and try to avoid azoles; in case of possible interactions review all the drugs involved and preferably use anidulafungin. Organ failures (3): echinocandins are the safest antifungal drugs; reconsider the use of azoles in patients under renal replacement therapy; all of the echinocandins to treat patients under continuous renal replacement therapy are accepted and do not require dosage adjustment. Conclusions Treatment of invasive candidiasis in ICU patients requires a broad range of knowledge and skills as summarized in our recommendations. These recommendations may help to optimize the therapeutic management of these patients in special situations and different scenarios and improve their outcome based on the DELPHI methodology.

The combined use of multiobjective optimization and life-cycle assessment (LCA) has recently emerged as a useful tool for minimizing the environmental impact of industrial processes. The main limitation of this approach is that it requires large amounts of data that are typically affected by several uncertainty sources. We propose herein a systematic framework to handle these uncertainties that takes advantage of recent advances made in modeling of uncertain LCA data and in optimization under uncertainty. Our strategy is based on a stochastic, multiobjective, and multiscenario mixed-integer nonlinear programming approach in which the uncertain parameters are described via scenarios. We investigate the use of two stochastic metrics: (1) the environmental impact in the worst case and (2) the environmental downside risk. We demonstrate the capabilities of our approach through its application to a generic complex industrial network in which we consider the uncertainty of some key life-cycle inventory parameters. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2098–2121, 2014

Summary Background Candidaemia and invasive Candida infections can cause patient death and are expensive. Anidulafungin, a newly-licensed candin, has proven effective in treating candidaemia. Our study evaluates the cost-effectiveness of anidulafungin compared with fluconazole, the current standard of care, for treating invasive candidiasis and candidaemia in Spain. Methods A decision tree model from the hospital perspective was constructed to examine the cost-effectiveness of anidulafungin compared with fluconazole in treating confirmed candidaemia. Treatment success, patient treatment patterns, and patient survival were based on the results from a randomised, double-blind multicentre trial (Reboli et al., 2007 [41] ). Only in-hospital (2011 €) direct costs per-patient obtained from a Spanish national database were considered. Renal toxicity probabilities and costs were extracted from the published literature. The incremental cost per successfully treated patient was calculated. One-way sensitivity analyses were performed to test model robustness. Results The percentage of successfully treated patients was higher with anidulafungin than with fluconazole (74% versus 57%). Treatment with anidulafungin resulted in higher antifungal drug costs (5991 € versus 3149 €) but lower overall costs (40 047 € versus 41 350 €) due to reductions in other medical costs. Univariate sensitivity analyses showed that anidulafungin was the most cost-effective. Conclusions Anidulafungin demonstrated improved clinical efficacy versus fluconazole in treating confirmed candidaemia. Despite increased drug costs, treating confirmed candidaemia with anidulafungin is a cost-effective strategy.

Current medical knowledge lacks specific information regarding creatine kinase (CK) elevation in influenza A pH1N1 (2009) infection. Primary endpoints were correlation between CK at intensive care unit (ICU) admission and ICU mortality. Secondary endpoints were ICU length of stay (LOS), mechanical ventilation (MV), and requirement of renal replacement techniques (RRT). A prospective multicenter register included all adults admitted for severe acute respiratory insufficiency (SARI) with confirmed pH1N1 in 148 ICUs. Clinical data including demographics, comorbidities, laboratory information, organ involvement, and prognostic data were registered. Post hoc classification of subjects was determined according to CK level. Data are expressed as median (interquartile range). Five hundred and five (505) patients were evaluable. Global ICU mortality was 17.8 % without documented differences between breakpoints. CK ≥500 UI/L was documented in 23.8 % of ICU admissions, being associated with greater renal dysfunction: acute kidney injury (AKI) was more frequent (26.1 versus 17.1 %, p

Background Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task., BMC Systems Biology, 5 (1), ISSN:1752-0509

After five years of treating diabetics by continuous ambulatory peritoneal dialysis (CAPD), we analyzed the factors involved in prognosis. Forty-one patients were included in the study, with a cumulative experience of 784 months. Good control of blood glucose was obtained with intraperitoneal (i.p.) insulin and the blood pressure was controlled in 87% of patients without medication, which probably favored the stabilization of visual acuity in 60% of 15 patients evaluated after two years. The follow-up of patients was longer in those who began CAPD with a higher residual creatinine clearance. In spite of the large number of patients who were blind or had very poor vision, 83% of all patients were self-sufficient and well-trained for CAPD, and 39% were able to work full time. The incidence of peritonitis declined to 1 episode per 17.5 patient months associated with the introduction of new preventive measures. Patients over 50 years old had the highest mortality rate and myocardial infarction was the main cause of death. Patient survival at 6, 12, 24, 36, and 42 months was 100, 90, 80, 62, and 62%, respectively. Age and cardiac problems are important factors in survival. Self-sufficiency, rehabilitation, and low incidence of peritonitis are also important factors in the life quality of diabetic patients on CAPD.

Objectives: To define which variables upon ICU admission could be related to the presence of coinfection using CHAID (Chi-squared Automatic Interaction Detection) analysis. Methods: A secondary analysis from a prospective, multicentre, observational study (2009 -2014) in ICU patients with confirmed A(H1N1)pdm09 infection. We assessed the potential of biomarkers and clinical variables upon admission to the ICU for coinfection diagnosis using CHAID analysis. Performance of cut-off points obtained was determined on the basis of the bi-nominal distributions of the true (+) and true (-) results. Results: Of the 972 patients included, 196 (20.3%) had coinfection. Procalcitonin (PCT; ng/mL 2.4 vs. 0.5, p < 0.001), but not C-reactive protein (CRP; mg/dL 25 vs. 38.5; p = 0.62) was higher in patients with coinfection. In CHAID analyses, PCT was the most important variable for coinfection. PCT < 0.29 ng/mL showed high sensitivity (Se = 88.2%), low Sp (33.2%) and high negative predictive value (NPV = 91.9%). The absence of shock improved classification capacity. Thus, for PCT < 0.29 ng/mL, the Se was 84%, the Sp 43% and an NPV of 94% with a post-test probability of coinfection of only 6%. Conclusion: PCT has a high negative predictive value (94%) and lower PCT levels seems to be a good tool for excluding coinfection, particularly for patients without shock. (C) 2015 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

Multi-objective optimization (MOO) has emerged recently as a useful technique in the design andplanning of engineering systems because it allows identifying alternatives leading to significant envi-ronmental savings. MOO models typically contain an infinite number of Pareto solutions, from whichdecision-makers should choose the best one according to their preferences. An approach is here pre-sented that identifies and retains for further inspection a reduced set of Pareto solutions showing betteroverall performance. The capabilities of our approach are illustrated through its application to the designof reverse osmosis desalination plants considering simultaneously the unitary production cost and a setof environmental impacts in several damage categories. Our method reduces significantly the number ofPareto points, thereby facilitating the decision-making process in MOO. The authors would like to acknowledge financial support from the Spanish Government(ENE2011-28269-C03-03, ENE2011-22722, DPI2012-37154-C02-02, CTQ2012-37039-C02) and the Catalan Government for the quality accreditation given to their research groups SUSCAPE and GREA (2009 SGR 545, 2009 SGR 534)

Ceftazidime-avibactam (CAZ-AVI) is a recently approved β-lactam–β-lactamase inhibitor combination with the potential to treat serious infections caused by carbapenem-resistant organisms. Few patients with such infections were included in the CAZ-AVI clinical trials, and clinical experience is lacking. We present a case series of patients with infections caused by carbapenem-resistant Enterobacteriaceae (CRE) or Pseudomonas aeruginosa (CRPa) who were treated with CAZ-AVI salvage therapy on a compassionate-use basis. Physicians who had prescribed CAZ-AVI completed a case report form. We used descriptive statistics to summarize patient characteristics and treatment outcomes. We used the Wilcoxon rank sum test and Fisher's exact test to compare patients by treatment outcome. The sample included 36 patients infected with CRE and two with CRPa. The most common infections were intra-abdominal. Physicians categorized 60.5% of patients as having life-threatening infections. All but two patients received other antibiotics before CAZ-AVI, for a median of 13 days. The median duration of CAZ-AVI treatment was 16 days. Twenty-five patients (65.8%) concurrently received other antibiotics to which their pathogen was nonresistant in vitro . Twenty-eight patients (73.7%, 95% confidence interval [CI], 56.9 to 86.6%) experienced clinical and/or microbiological cure. Five patients (20.8%) with documented microbiological cure died, whereas 10 patients (71.4%) with no documented microbiological cure died ( P = 0.01). In three-quarters of cases, CAZ-AVI (alone or combined with other antibiotics) cured infections caused by carbapenem-resistant organisms, 95% of which had failed previous therapy. Microbiological cure was associated with improved survival. CAZ-AVI shows promising clinical results for infections for which treatment options are limited.