Fatores de risco e manifestações clínicas da pré-eclâmpsia: uma revisão integrativa

This article aims to describe the risk factors and clinical manifestations of pre-eclampsia. This is an integrative review of the literature, which followed the review protocol that includes six stages, based on the following guiding question: What are the risk factors and clinical manifestations of pre-eclampsia? Data collection was carried out in the following databases: LILACS through VHL-MS, SciELO, PUBMED/MEDLINE, with the Health Sciences Descriptors (DeCS/MeSH): Pre-Eclampsia; Proteinuria; Hypertension; Treatment; Signs and symptoms in Portuguese and English. The descriptors were crossed using the Boolean operators AND and OR. The inclusion criteria were: works in complete and free versions in Portuguese, English or Spanish, published between 2019 and 2023, that addressed the study theme. The exclusion criteria were duplicates or articles that did not answer the guiding question. Risk factors include prior personal history of pre-eclampsia, family history of pre-eclampsia, pre-existing health conditions such as hypertension, DM and autoimmune diseases. As for clinical manifestations, pre-eclampsia often presents with high blood pressure, edema, especially in the hands, feet and face, severe headaches, visual changes, such as blurred vision or sensitivity to light, and upper abdominal pain, indicative of possible liver disease. complications. These clinical symptoms are crucial for early diagnosis and adequate management of pre-eclampsia, aiming to prevent serious complications for the mother and baby. It is concluded that the integration of effective prenatal care, ongoing education of pregnant women, and the implementation of robust public policies are crucial to improving maternal and perinatal outcomes related to preeclampsia. In short, continued investments in research, education and healthcare are needed to address the challenges associated with pre-eclampsia and ensure a healthy and safe pregnancy for all women.Este artículo tiene como objetivo describir los factores de riesgo y las manifestaciones clínicas de la preeclampsia. Esta es una revisión integrada de la literatura, que sigue el protocolo de revisión que incluye seis etapas, basado en la siguiente pregunta orientadora: ¿Cuáles son los factores de riesgo y las manifestaciones clínicas de la preeclampsia? La recolección de datos se realizó en las siguientes bases de datos: LILACS a través de la BVS-MS, SciELO, PUBMED/MEDLINE, con los Descriptores en Ciencias de la Salud (DeCS/MeSH): Preeclampsia; Proteinuria; Hipertensión; Tratamiento; Signos y síntomas en portugués e inglés. Los descriptores se cruzan mediante los operadores booleanos AND y OR. Los criterios de inclusión fueron: obras en versión completa y gratuita en portugués, inglés o español, publicadas entre 2019 y 2023, que aborden la temática del estudio. Los criterios de exclusión fueron duplicados o artículos que no respondieran a la pregunta orientadora. Los factores de riesgo incluyen antecedentes personales de preeclampsia, antecedentes familiares de preeclampsia, condiciones de salud preexistentes como hipertensión, diabetes mellitus y síntomas autoinmunes. En las manifestaciones clínicas, la preeclampsia suele presentarse con hipertensión, edemas, especialmente en manos, pies y cara, fuertes dolores de cabeza, cambios visuales como visión borrosa o sensibilidad a la luz y dolor en la parte superior del abdomen, indicativos de posible enfermedad del higado. complicaciones. Estos síntomas clínicos son cruciales para el diagnóstico precoz y el tratamiento adecuado de la preeclampsia, con el objetivo de prevenir complicaciones graves tanto para la madre como para el bebé. Si concluimos que la integración de una atención prenatal eficaz, la educación continua de las mujeres en relación con la preeclampsia y la implementación de políticas públicas sólidas son cruciales para mejorar los resultados maternos y perinatales relacionados con la preeclampsia. En resumen, se necesitan retrocesos continuos en la investigación, la educación y la atención médica para abordar los desafíos asociados con la preeclampsia y garantizar una preeclampsia saludable y segura para todas las mujeres.Este artigo tem por objetivo descrever os fatores de risco e as manifestações clínicas da pré-eclâmpsia. Trata-se de uma revisão integrativa da literatura, que seguiu o protocolo de revisão que contempla seis etapas, baseada na seguinte pergunta norteadora: Quais são os fatores de risco e as manifestações clínicas da pré-eclâmpsia? A coleta de dados foi realizada nas bases: LILACS através da BVS-MS, SciELO, PUBMED/MEDLINE, com os Descritores em Ciências da Saúde (DeCS/MeSH): Pré-Eclâmpsia; Proteinúria; Hipertensão; Tratamento; Sinais e sintomas em português e inglês. Os descritores foram cruzados utilizando os operadores booleanos AND e OR. Os critérios de inclusão foram: trabalhos nas versões completas e gratuitas nos idiomas português, inglês ou espanhol, publicados entre os anos de 2019 a 2023, que abordassem a temática do estudo. Os critérios de exclusão foram duplicatas ou artigos que não respondiam a pergunta norteadora. Entre os fatores de risco estão a história pessoal anterior de pré-eclâmpsia, o histórico familiar de pré-eclâmpsia, condições de saúde pré-existentes como HAS, DM e transtornos autoimunes. Quanto às manifestações clínicas, a pré-eclâmpsia frequentemente se apresenta com hipertensão arterial, edema, especialmente nas mãos, pés e rosto, dores de cabeça severas, alterações visuais, como visão embaçada ou sensibilidade à luz, e dor abdominal superior, indicativa de possíveis complicações hepáticas. Esses sintomas clínicos são cruciais para o diagnóstico precoce e o manejo adequado da pré-eclâmpsia, visando prevenir complicações graves tanto para a mãe quanto para o bebê. Conclui-se que a integração de cuidados pré-natais eficazes, educação contínua das gestantes e implementação de políticas públicas robustas são cruciais para melhorar os desfechos maternos e perinatais relacionados à pré-eclâmpsia. Em suma, investimentos contínuos em pesquisa, educação e cuidados de saúde são necessários para enfrentar os desafios associados à pré-eclâmpsia e garantir uma gravidez saudável e segura para todas as mulheres

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

Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions