Evaluation of sound pressure levels in a pediatric intensive care unit

This study objectives were to measure the sound pressure levels found in the pediatric intensive care unit in a federal institution of Rio de Janeiro; to verify differences in noise levels during the morning and afternoon; to confront the sound pressure levels found against acceptable levels according to national and international noise organizations; to count the quantity of alarms triggered by each type of medical care equipment selected (multiparameter monitor, mechanical ventilator and infusion pump); to verify the relevance in the scientific world about pediatric intensive care unit noise through bibliometrics and to address the trinomial care technology - noise - implications on care. It’s an observational, exploratory, quantitative study, organized in three steps: Parameter collection and decibel meter calibration - data were based on the study by Salú, et al (2015) ; Data collection: 40 hours of discontinued observation (8am to 16pm) on different days for a period two months using two decibel meters; Data processing: An Excel spreadsheet was created for the database and data analysis was performed with the help of Microsoft Office Excel 2010 and Program R, organized into graphs and tables. 61% of the alarms corresponded to the mechanical ventilator; Bed E had the lowest standard deviation (SD = 2.945) and the highest median (69.5dBA). Even by removing the E bed from the analysis, there is a significant difference (p <0.001) between sound pressure levels. The median of the afternoon (28.2dBA); and morning (26.1dBA). Mechanical fan and monitor generated higher sounds; the pediatric intensive care unit has considerably exceeded that recommended by national and international noise organizations; afternoon generated higher sounds than morning. Keywords: Noise Meters; Noise; Intensive care; Pediatric

CARACTERIZAÇÃO SÓCIO DEMOGRÁFICA E CLÍNICA DE PACIENTES SUBMETIDOS À CIRURGIA BARIÁTRICA / SOCIO DEMOGRAPHIC CHARACTERISTICS AND CLINIC FOR SURGERY PATIENTS BARIATRIC

Introdução: A obesidade é uma doença multifatorial com consequências sociais, psicológicas e clínicas graves com diversostratamentos disponíveis tanto para a obesidade quanto para o sobrepeso, sendo a escolha baseada na gravidade do problema ena presença de complicações associadas. Em casos de obesidade grave a cirurgia bariátrica torna-se o recurso mais utilizado eeficaz. Objetivo: Caracterizar o perfil sócio demográfico e clínico de pacientes submetidos à Cirurgia Bariátrica. Método: Oestudo foi descritivo, retrospectivo, de abordagem quantitativa, com pacientes submetidos à cirurgia bariátrica assistidos emum Hospital Universitário. Resultados: A maioria dos pacientes foram do sexo feminino (93,1%) sendo 66,7% procedentes de2 São Luís - MA, com idade média de 38,6 ± 8,6 anos e Índice de Massa Corporal (IMC) de 44 ± 4,4 kg/m . A comorbidade maisfrequente foi hipertensão arterial sistêmica com 69,4%. A técnica mais utilizada foi por Gastroplastia em Y de Roux, 84,7% dospacientes, e no pós-operatório, 51,4%, tiveram a expansibilidade torácica diminuída. Em relação ao local de internação durantesua estadia no hospital, 93,1% ficaram na enfermaria. Conclusão: Os pacientes submetidos à cirurgia bariátrica foram mulheres,adultas, com obesidade grau III e com pelo menos uma comorbidade associada, sendo a hipertensão arterial sistêmica amais prevalente. A técnica mais utilizada foi a gastroplastia em Y de Roux, sendo a expansibilidade torácica a complicação maisfrequente no pós-operatório.Palavras-chave: Cirurgia Bariátrica. Obesidade. Perfil de Saúde.AbstractIntroduction: Obesity is a multifactorial disease with serious social, psychological and clinical consequences with several treatmentsavailable for both obesity and overweight, being the choice based on the severity of the problem and the presence of associatedcomplications. In cases of severe obesity bariatric surgery becomes the most used and effective resource. Objective: Tocharacterize the socio demographic and clinical profile of patients submitted to CB. Method: This was a descriptive, retrospective,quantitative study of patients undergoing bariatric surgery at the University Hospital. Results: The majority of the patientswere female (93,1%) and 66,7% were from São Luís - MA, with a mean age of 38,6 ± 8,6 years and a Body Mass Index (BMI) of44±4,4 kg/m². The most frequent comorbidity was systemic arterial hypertension with 69,4%. The most commonly used techniquewas Roux-en-Y gastroplasty, 84,7% of the patients, and in the postoperative period, 51,4%, had thoracic expandabilitydecreased. Regarding the place of hospitalization during his stay in the hospital, 93,1% were in the infirmary. Conclusion: Thepatients undergoing bariatric surgery were adult women with grade III obesity and with at least one associated comorbidity,with systemic arterial hypertension being the most prevalent. The most commonly used technique was Roux-en-Y gastroplasty,with thoracic expandability being the most frequent complication in the postoperative period.Keywords: Bariatric surgery. Obesity. Health Profile

Um estudo sobre a prevalência da dengue no Brasil: Análise da literatura / A study on the prevalence of dengue fever in Brazil: Analysis of the literature

Este estudo tem como propósito de pesquisa apresentar as principais características acerca da prevalência de dengue no Brasil através de uma revisão da literatura. Objetivo: Verificar a prevalência da dengue no Brasil, segundo a literatura. Metodologia: Trata-se de um estudo de natureza integrativa com abordagem qualitativa, com dados provenientes da literatura. Resultados e Discussão: Os casos de dengue vêm aumentando anualmente e esse aumento acentuado associa-se à introdução e/ou circulação de um ou mais sorotipos do vírus e crescente proporção da população acometida pela forma grave da doença, além da taxa de mortalidade considerável contribui para a perda de anos saudáveis de vida no Brasil. Considerações Finais: Os resultados possibilitam entender e ter uma visão geral acerca da prevalência de dengue no país além de mostrar claramente, que são necessários esforços e ações tendo por objetivo a redução nos casos de dengue, com foco principal nos estados com maior incidência

Pervasive gaps in Amazonian ecological research

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

Sensitivity of South American tropical forests to an extreme climate anomaly

The tropical forest carbon sink is known to be drought sensitive, but it is unclear which forests are the most vulnerable to extreme events. Forests with hotter and drier baseline conditions may be protected by prior adaptation, or more vulnerable because they operate closer to physiological limits. Here we report that forests in drier South American climates experienced the greatest impacts of the 2015–2016 El Niño, indicating greater vulnerability to extreme temperatures and drought. The long-term, ground-measured tree-by-tree responses of 123 forest plots across tropical South America show that the biomass carbon sink ceased during the event with carbon balance becoming indistinguishable from zero (−0.02 ± 0.37 Mg C ha −1 per year). However, intact tropical South American forests overall were no more sensitive to the extreme 2015–2016 El Niño than to previous less intense events, remaining a key defence against climate change as long as they are protected

Pervasive gaps in Amazonian ecological research

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

Pervasive gaps in Amazonian ecological research

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