BULIMIA NERVOSA: DO DIAGNÓSTICO AO TRATAMENTO

An integrative literature review is presented on bulimia nervosa, its clinical and epidemiological aspects, as well as the impact of this condition on the individual's life. This condition is characterized by an eating disorder in which the individual exhibits periodic binge eating behaviors, in which the individual ingests an exceptional amount of calories in a short period of time. These episodes are sequenced by compensatory behaviors, which the patient perceives as uncontrolled and humiliating. Diagnostic criteria are used to define the condition, which can coexist with other comorbidities. There is a need for a multidisciplinary team to intervene to improve patients' quality of life, as well as treatment aimed at the various aspects of this disorder.    Apresenta-se uma revisão integrativa de literatura acerca da bulimia nervosa, seus aspectos clínicos, epidemiológicos, bem como o impacto dessa condição na vida do indivíduo. Essa condição caracteriza-se por um transtorno alimentar em que o indivíduo apresenta comportamentos periódicos de compulsão alimentar, nos quais o indivíduo ingere uma quantidade excepcional de calorias em um curto período. Tais episódios são sequenciados por comportamentos compensatórios, sentidos pela paciente como manifestações descontroladas e humilhantes. Utilizam-se critérios diagnósticos para definir o quadro, que pode coexistir com outras comorbidades. Há necessidade de uma equipe multidisciplinar para intervir na melhoria e na qualidade de vida dos pacientes, assim como um tratamento voltado para os vários aspectos que esse transtorno apresenta

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

Perfil epidemiológico dos pacientes com gastrosquise operados em uma maternidade de referência do estado do Piauí de 2019 a 2021

Introdução: esta pesquisa parte da necessidade de discutir sobre o perfil epidemiológico da Gastrosquise, na cidade de Teresina-PI, por se tratar de um debate extremamente importante, uma vez que impacta as esferas sociais, biológicas e psíquicas, que torna-se relevante para a saúde pública da população. Objetivo: analisar o perfil epidemiológico dos pacientes com Gastrosquise operados em uma Maternidade Pública de Referência do Estado do Piauí de 2019 a 2021. Métodos: trata-se de um estudo observacional, descritivo, quantitativo, de natureza documental. Foram coletados 30 prontuários físicos de uma Maternidade Pública do Estado, situada em Teresina-PI, com o intuito de analisar os dados através de questões norteadoras, a fim de explorar as informações presentes nos prontuários, o que levou a interpretação e discussão dos achados. Resultados: identificou-se 30 pacientes portadores de gastrosquise, no período de janeiro de 2019 a dezembro de 2021, em que 73,3% das mães realizaram o pré-natal, idade materna com média de 21 anos, 63,3% realizaram parto cesárea. Os fatores de risco relacionados ao óbito do recém-nascido incluem, o Apgar baixo, a prematuridade e o diagnóstico tardio. Conclusão: o presente estudo permitiu esclarecer sobre o perfil clínico-epidemiológico dos recém-nascidos admitidos na Maternidade Pública do Estado, situada em Teresina, Piauí, no período de janeiro de 2019 a dezembro de 2021, que reflete a necessidade de um diagnóstico no pré-natal e melhores cuidados na conduta do paciente, a fim de reduzir a mortalidade