21 research outputs found

    High levels of immunosuppression are related to unfavourable outcomes in hospitalised patients with rheumatic diseases and COVID-19 : first results of ReumaCoV Brasil registry

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    Objectives To evaluate risk factors associated with unfavourable outcomes: emergency care, hospitalisation, admission to intensive care unit (ICU), mechanical ventilation and death in patients with immune-mediated rheumatic disease (IMRD) and COVID-19. Methods Analysis of the first 8 weeks of observational multicentre prospective cohort study (ReumaCoV Brasil register). Patients with IMRD and COVID-19 according to the Ministry of Health criteria were classified as eligible for the study. Results 334 participants were enrolled, a majority of them women, with a median age of 45 years; systemic lupus erythematosus (32.9%) was the most frequent IMRD. Emergency care was required in 160 patients, 33.0% were hospitalised, 15.0% were admitted to the ICU and 10.5% underwent mechanical ventilation; 28 patients (8.4%) died. In the multivariate adjustment model for emergency care, diabetes (prevalence ratio, PR 1.38; 95% CI 1.11 to 1.73; p=0.004), kidney disease (PR 1.36; 95% CI 1.05 to 1.77; p=0.020), oral glucocorticoids (GC) (PR 1.49; 95% CI 1.21 to 1.85; p50 years (PR 1.89; 95% CI 1.26 to 2.85; p=0.002), no use of tumour necrosis factor inhibitor (TNFi) (PR 2.51;95% CI 1.16 to 5.45; p=0.004) and methylprednisolone pulse therapy (PR 2.50; 95% CI 1.59 to 3.92; p<0.001); for ICU admission, oral GC (PR 2.24; 95% CI 1.36 to 3.71; p<0.001) and pulse therapy with methylprednisolone (PR 1.65; 95% CI 1.00 to 2.68; p<0.043); the two variables associated with death were pulse therapy with methylprednisolone or cyclophosphamide (PR 2.86; 95% CI 1.59 to 5.14; p<0.018). Conclusions Age >50 years and immunosuppression with GC and cyclophosphamide were associated with unfavourable outcomes of COVID-19. Treatment with TNFi may have been protective, perhaps leading to the COVID-19 inflammatory process

    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

    Pervasive gaps in Amazonian ecological research

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    Pervasive gaps in Amazonian ecological research

    Get PDF
    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

    Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

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    Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure &lt;= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

    PROPRIEDADES FUNCIONAIS DAS PROTEÍNAS DE AMÊNDOAS DA MUNGUBA (Pachira aquatica Aubl.)

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    RESUMOA semente da munguba (Pachira aquatica Aubl.) contém amêndoas que exibem um conteúdo excelente de óleo e um percentualsignificativo em proteínas. Propositou-se determinar algumas propriedades funcionais das proteínas de amêndoas damunguba com o objetivo de instituir sua utilização na indústria de alimentos. O teor lipídico foi de 46,62%, o proteico de 13,75% e na forma de torta apresentou um índice de 28,27% de proteínas. Obtiveram-se doisisolados proteicos, o IP 2,0 e o IP 10,0, decorrentes de duas condições de pH (2,0 e 10,0). Na obtenção dos isolados proteicos, os índices em proteínas extraídas foram de 38,52% para o IP 2,0 e 82,06% para o IP 10,0. Os índices de proteínas recuperadas através da precipitação isoelétrica foram de 23,35% para o IP 2,0 e de 70,94%para o IP 10,0, em pH 5,0. As propriedades funcionais exibiram solubilidade mínima em pH 5,0, no pontoisoelétrico (pI), sendo mais elevada em pH ácido e alcalino do pI. As melhores capacidades de absorçãode água e de óleo exibidas foram para o IP 10,0. As propriedades emulsificantes foram dependentes do pH para os dois isolados, e o IP 10,0 indicou melhores resultados. As propriedades funcionais estudadas permitem o emprego dos isolados proteicos em produtos alimentícios que requerem alta solubilidade, tais como os produtos de panificação, massas em geral, sopas desidratadas e molhos, produtos que exigem desempenho na absorção do óleo, como as carnes simuladas, e em produtos que requerem poderes emulsificantes
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