Fortalecimento da musculatura respiratória em pacientes submetidos a ventilação mecânica invasiva: revisão integrativa da literatura

Introdução: a atrofia muscular e consequente fraqueza dos músculos respiratórios inspiratórios pode ocorrer em pacientes dependentes de ventilação mecânica, dificultando seu desmame ventilatório. A avaliação e treinamento desta musculatura podem ser realizados em unidade de terapia intensiva como modo de fortalecimento muscular respiratório para permitir a retirada do suporte ventilatório. Objetivo: realizar uma revisão integrativa da literatura científica e analisar as melhores técnicas de fortalecimento da musculatura respiratória. Método: trata-se de uma revisão integrativa da literatura científica com levantamento de dados através das bases de dados Google Acadêmico, Scielo, Medline, Pubmed, Lilacs, em português, sobre o treinamento da musculatura respiratória de pacientes em ventilação mecânica, no período de janeiro de 2016 a dezembro de 2020. Resultados: foram selecionados 40 estudos, porém apenas 11 destes estavam relacionados ao tema e foram incluídos neste trabalho, sendo 3 estudos clínicos e 8 revisões de literatura, que mostram que o fortalecimento da musculatura respiratória pode ser benéfico para pacientes dependentes de ventilação mecânica. Conclusão: o treinamento muscular respiratório é muito importante para facilitar o processo de desmame de pacientes em ventilação mecânica, com benefícios variáveis de acordo com a técnica utilizada

Insuficiência cardíaca grave e rapidamente progressiva em paciente adulto jovem com cardiomiopatia chagásica crônica: desafio diagnóstico e terapêutico

Chagas disease is responsible for 12 thousand deaths annually in the Americas, mainly due to Chronic Chagas Cardiomyopathy (CCC) that occurs in 20 to 30% of those infected people, after 60 years old, 30 to 40 years after the first infection, leading to biventricular heart failure (HF), arrhythmias, blocks and embolisms. The diagnosis is based on epidemiology, clinical condition, electrocardiographic changes and imaging tests associated with serology. The present study reports the case of a patient with atypical evolution for her age due to rapid progression to advanced and refractory HF, associated with high morbidity and mortality, a typically late manifestation of CCC. Clinical case: 37 years old female patient admitted to the Intensive Care Unit of a tertiary hospital in a city of São Paulo State for decompensated congestive heart failure, associated with pleural effusion. The echocardiogram and serology for Trypanosoma Cruzi confirmed the diagnosis of CCC and risk of mortality estimated in 84%. Treatment started with beta-blocker, spironolactone, diuretic, enalapril and patient was discharged from hospital. After 20 months, she was readmitted with cardiogenic shock, cardio-renal syndrome and atrial fibrillation treated with diuretics, inotropic and amiodarone, and progressing to death after three days. It was not possible to refer for resynchronization therapy or heart transplantation, due to psychiatric comorbidity, poor medication adherence and unavailability at the service. The precocious presentation of advanced and refractory HF, in this case, revels the importance of adherence to medication treatment, reduction of readmissions and the quick referral to a transplant center and ventricular support, in an attempt to reduce the morbidity and mortality of these patients.A Doença de Chagas é responsável por 12 mil mortes anualmente nas Américas em decorrência da Cardiomiopatia Chagásica crônica (CCC) que ocorre em 20 a 30% dos infectados, após os 60 anos, 30 a 40 anos após a primo-infecção, levando à Insuficiência Cardíaca (IC) biventricular, arritmias, bloqueios e embolias. O diagnóstico é baseado na epidemiologia, quadro clínico, alterações eletrocardiográficas e de exames de imagem associados à sorologia. O presente estudo relata o caso de paciente com evolução atípica para a idade devido à rápida progressão para IC avançada e refratária, associada à alta morbimortalidade, manifestação tipicamente tardia da CCC. Caso clínico: paciente de 37 anos, sexo feminino, internada na Unidade de Terapia Intensiva de um hospital terciário no interior do Estado de São Paulo por IC congestiva descompensada, associada a derrame pleural. O ecocardiograma e sorologia para Trypanossoma Cruzi confirmaram o diagnóstico de CCC e risco de mortalidade estimado em 84%. Foi iniciado tratamento com betabloqueador, espironolactona, diurético, enalapril e paciente recebeu alta. Após 20 meses, reinternou com choque cardiogênico, síndrome cardiorrenal e fibrilação atrial tratados com diuréticos, inotrópicos e amiodarona, evoluindo para óbito após três dias. Não foi possível encaminhamento para terapia de ressincronização ou transplante cardíaco, devido à comorbidade psiquiátrica, má adesão medicamentosa e indisponibilidade no serviço. A precocidade da apresentação da IC avançada e refratária, neste caso, revela a importância da adesão ao tratamento medicamentoso, redução de reinternações e o rápido referenciamento a centro de transplante e suporte ventricular, como tentativa de diminuir a morbimortalidade desses pacientes

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

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

Resumos concluídos - Ciências Biomédicas

Resumos concluídos - Ciências Biomédica

Núcleos de Ensino da Unesp: artigos 2008

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq