10 research outputs found

    Fortalecimiento institucional de la asociación de mujeres cabeza de familia indígena “AMCAFAMI” en el Municipio de Mitú

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    El presente documento pretende plasmar una propuesta de aporte al fortalecimiento y desarrollo organizacional para la Asociación AMCAFAMI, con base en los lineamientos, conceptos y metodologías asimiladas durante el proceso formativo en la especialización sobre Gerencia Social de la Corporación Universitaria Minuto de Dios. En este sentido en el documento se presentaran planteamientos teóricos prácticos desde la óptica general de la planificación estratégica, el mercadeo social, fundraising, consolidación de redes y alianzas, balance social, resolución de conflictos, impactos ambientales; entre otros elementos claves que componen una propuesta novedosa para la asociación, la cual permite asertivamente la posibilidad de aportar a su causa social y por ende a sus asociadas. AMCAFAMI, asociación de mujeres cabeza de familia indígenas del municipio del Mitú, es una asociación no gubernamental, sin ánimo de lucro e independiente. Es una asociación que persigue la promoción, mejora y defensa del medio de vida, tanto económico como social y cultural de las mujeres y de las familias que dependen de ellas, al mismo tiempo que reivindica el protagonismo de la mujer en el desarrollo socio cultural, propiciando su formación y facilitando la generación de ingresos y mejoramiento de la calidad de vida a través de distintas iniciativas. AMCAFAMI es la primera organización de mujeres del departamento del Vaupés. Su fundación data de 2009, fecha en la cual ha iniciado su labor de impulsar y fomentar la integración de la mujer cabeza de familia indígena y su desarrollo autónomo

    Overview of recent TJ-II stellarator results

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    The main results obtained in the TJ-II stellarator in the last two years are reported. The most important topics investigated have been modelling and validation of impurity transport, validation of gyrokinetic simulations, turbulence characterisation, effect of magnetic configuration on transport, fuelling with pellet injection, fast particles and liquid metal plasma facing components. As regards impurity transport research, a number of working lines exploring several recently discovered effects have been developed: the effect of tangential drifts on stellarator neoclassical transport, the impurity flux driven by electric fields tangent to magnetic surfaces and attempts of experimental validation with Doppler reflectometry of the variation of the radial electric field on the flux surface. Concerning gyrokinetic simulations, two validation activities have been performed, the comparison with measurements of zonal flow relaxation in pellet-induced fast transients and the comparison with experimental poloidal variation of fluctuations amplitude. The impact of radial electric fields on turbulence spreading in the edge and scrape-off layer has been also experimentally characterized using a 2D Langmuir probe array. Another remarkable piece of work has been the investigation of the radial propagation of small temperature perturbations using transfer entropy. Research on the physics and modelling of plasma core fuelling with pellet and tracer-encapsulated solid-pellet injection has produced also relevant results. Neutral beam injection driven Alfvénic activity and its possible control by electron cyclotron current drive has been examined as well in TJ-II. Finally, recent results on alternative plasma facing components based on liquid metals are also presentedThis work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014–2018 under Grant Agreement No. 633053. It has been partially funded by the Ministerio de Ciencia, Inovación y Universidades of Spain under projects ENE2013-48109-P, ENE2015-70142-P and FIS2017-88892-P. It has also received funds from the Spanish Government via mobility grant PRX17/00425. The authors thankfully acknowledge the computer resources at MareNostrum and the technical support provided by the Barcelona S.C. It has been supported as well by The Science and Technology Center in Ukraine (STCU), Project P-507F

    The Spin-Off as an Instrument of Sustainable Development: Incentives for Creating an Academic USO

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    In recent years, universities and public authorities have increasingly focused on creating USOs (university spin-offs) as a method of transferring research results to society and of achieving the sustainable development sought by European institutions. However, the success of these policies depends on the appeal of creating a USO for academics. The aim of this research was to examine the relative importance of certain factors that may boost academic entrepreneurship and, therefore, to guide public policies. To do this, a qualitative study was carried out among 42 researchers from Spanish universities and research centres to understand their motivations for creating a USO. A quantitative study was then carried out, based on Conjoint Analysis and with a sample of 1726 academics, to identify the relative importance of six conditions that influence their predisposition to become entrepreneurs. This technique is seldom used in the field of entrepreneurship and, to the best of our knowledge, has never been used before to analyse academic entrepreneurship. The results of the study show that personal economic benefit is clearly the factor that heightens the intention to create a USO the most. Research benefit, CV benefit, support programmes, teaching reduction and personal cost are of lesser importance. The study also concludes that there are few differences according to the academic’s profile

    At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

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    By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients

    Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

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    Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death

    Implementation of Recommendations on the Use of Corticosteroids in Severe COVID-19

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    Importance: Research diversity and representativeness are paramount in building trust, generating valid biomedical knowledge, and possibly in implementing clinical guidelines. Objectives: To compare variations over time and across World Health Organization (WHO) geographic regions of corticosteroid use for treatment of severe COVID-19; secondary objectives were to evaluate the association between the timing of publication of the RECOVERY (Randomised Evaluation of COVID-19 Therapy) trial (June 2020) and the WHO guidelines for corticosteroids (September 2020) and the temporal trends observed in corticosteroid use by region and to describe the geographic distribution of the recruitment in clinical trials that informed the WHO recommendation. Design, setting, and participants: This prospective cohort study of 434 851 patients was conducted between January 31, 2020, and September 2, 2022, in 63 countries worldwide. The data were collected under the auspices of the International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC)-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Analyses were restricted to patients hospitalized for severe COVID-19 (a subset of the ISARIC data set). Exposure: Corticosteroid use as reported to the ISARIC-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Main outcomes and measures: Number and percentage of patients hospitalized with severe COVID-19 who received corticosteroids by time period and by WHO geographic region. Results: Among 434 851 patients with confirmed severe or critical COVID-19 for whom receipt of corticosteroids could be ascertained (median [IQR] age, 61.0 [48.0-74.0] years; 53.0% male), 174 307 (40.1%) received corticosteroids during the study period. Of the participants in clinical trials that informed the guideline, 91.6% were recruited from the United Kingdom. In all regions, corticosteroid use for severe COVID-19 increased, but this increase corresponded to the timing of the RECOVERY trial (time-interruption coefficient 1.0 [95% CI, 0.9-1.2]) and WHO guideline (time-interruption coefficient 1.9 [95% CI, 1.7-2.0]) publications only in Europe. At the end of the study period, corticosteroid use for treatment of severe COVID-19 was highest in the Americas (5421 of 6095 [88.9%]; 95% CI, 87.7-90.2) and lowest in Africa (31 588 of 185 191 [17.1%]; 95% CI, 16.8-17.3). Conclusions and relevance: The results of this cohort study showed that implementation of the guidelines for use of corticosteroids in the treatment of severe COVID-19 varied geographically. Uptake of corticosteroid treatment was lower in regions with limited clinical trial involvement. Improving research diversity and representativeness may facilitate timely knowledge uptake and guideline implementation

    The value of open-source clinical science in pandemic response: lessons from ISARIC

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    The value of open-source clinical science in pandemic response: lessons from ISARIC

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    Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms

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    Background: COVID-19 is primarily known as a respiratory illness; however, many patients present to hospital without respiratory symptoms. The association between non-respiratory presentations of COVID-19 and outcomes remains unclear. We investigated risk factors and clinical outcomes in patients with no respiratory symptoms (NRS) and respiratory symptoms (RS) at hospital admission. Methods: This study describes clinical features, physiological parameters, and outcomes of hospitalised COVID-19 patients, stratified by the presence or absence of respiratory symptoms at hospital admission. RS patients had one or more of: cough, shortness of breath, sore throat, runny nose or wheezing; while NRS patients did not. Results: Of 178,640 patients in the study, 86.4 % presented with RS, while 13.6 % had NRS. NRS patients were older (median age: NRS: 74 vs RS: 65) and less likely to be admitted to the ICU (NRS: 36.7 % vs RS: 37.5 %). NRS patients had a higher crude in-hospital case-fatality ratio (NRS 41.1 % vs. RS 32.0 %), but a lower risk of death after adjusting for confounders (HR 0.88 [0.83-0.93]). Conclusion: Approximately one in seven COVID-19 patients presented at hospital admission without respiratory symptoms. These patients were older, had lower ICU admission rates, and had a lower risk of in-hospital mortality after adjusting for confounders

    ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

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    The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use
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