Can the five repetition sit-to-stand test discriminate inpatients and outpatients with acute exacerbations of COPD?

The five repetition sit-to-stand test (5STS) is a simple and validated functional test, suitable to be performed in different settings, that has been related with mortality in chronic obstructive pulmonary disease (COPD). Yet, its relationship with the need for hospitalisation is unknown. This study explored the 5STS ability to discriminate between hospitalised and non-hospitalised patients at the onset of an acute exacerbation of COPD (AECOPD). Patients with AECOPD visiting the urgency ward of 2 hospitals were recruited. Clinicians defined the need for hospitalisation based on their best judgment. The 5STS was completed within 48h of the AECOPD onset. Receiver operating characteristic analysis was performed and the area under the curve (AUC) was calculated. 47 patients (92% male, 69±7yrs, FEV150±20%predicted) participated. Age, gender, FEV1, body mass index and quadriceps muscle strength were not different between inpatients and outpatients. 5STS showed good ability to discriminate between inpatients and outpatients (AUC=0.73; 95%CI 0.59-0.88), with a sensitivity of 75% and specificity of 53% for a cut-off of 13.7s (Fig. 1). 5STS can accurately discriminate between inpatients and outpatients with AECOPD. A cut-off of 13.7s may be used to differentiate these patients. Results also emphasise the need to improve patients’ functionality during hospitalisation. Studies with larger samples are needed.publishe

A causalidade do abortamento espontâneo: uma revisão integrativa/ The causality of spontaneous abortion: an integrative review

O aborto espontâneo (AE) condiz com à interrupção involuntária da gravidez até a 20ª semana de gestação. Levando em consideração as causas isoladas, pode se dizer que anomalias genéticas, como erro nos cromossomos e gametas, alguns apontam também doenças bacterianas no colo uterino, útero com diferentes formas, aspectos autoimunes e inflamação no endométrio. O índice de abortamento pode chegar em até 75% das gestações. O presente estudo representa um importante instrumento científico à medida que se propõe a descrever os fatores associados a ocorrência de abortamento espontâneo. O presente estudo trata-se de uma revisão integrativa. Como objetivo principal nos propomos a aprofundar nas causalidades do AE. Tal predomínio mostra que essa temática ainda é pouco explorada pela enfermagem e por todos da ciência e saúde

Padrão de consumo de bebida alcóolica em pessoas com hipertensão arterial / Pattern of alcohol consumption in people with high blood pressure

O presente estudo teve como objetivo investigar o padrão de consumo de álcool em pessoas hipertensas, em um Multicentro de Saúde no município de Salvador. Foi realizado estudo de corte transversal e natureza quantitativa, com uma amostra composta por 220 participantes. Para coleta de dados utilizaram-se formulário para entrevista estruturada onde foram coletado dados relativos a caracaterização socioeconômica e o instrumento Alcohol use disorders identification para identificar problemas relacionados ao consumo de bebidas alcoólicas no cuidado primário à saúde. Foram realizadas análises descritivas e exploratórias para caracterizar a população sendo utilizado o programa estatístico SPSS (Statistical Package of Social Science). Nos resultados, observou-se predominância do sexo feminino, sendo a média de idade de 59,4 anos com um desvio padrão de 11,3, variando entre 24 a 85 anos, raça/cor autodeclarada negra, nível de escolaridade a partir do ensino médio, renda familiar mensal inferior a 1 salário mínimo e viviam com companheiro. Quanto às zonas de risco do álcool, a maioria dos participantes da pesquisa encontrava-se na zona I da classificação do AUDIT

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

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