PERFIL HEMATO-LABORATORIAL DE PACIENTES COVID-19 NO EXTREMO SUL CATARINENSE/BRASIL

To assess the clinical and laboratory profile of patients hospitalized for COVID-19. Descriptive retrospective observational study, collecting secondary data from medical records of patients hospitalized for COVID-19 between January and June 2021 at a high-complexity hospital in Criciúma, Santa Catarina, Brazil. The study population consisted of a total of 497 patients, with a mean age of 59.2 years and a standard deviation of 15.44, with a predominance of male patients (55.3%). The most prevalent comorbidities were diabetes mellitus (23.54%) and arterial hypertension (35.01%). The main clinical outcome was discharge (62.8%). Regarding laboratory tests, patients initially showed elevated inflammatory markers and leukocytosis. During hospitalization, they developed anemia, thrombocytopenia, improvement in inflammatory markers, and maintained leukocytosis. In this context, patients may present laboratory abnormalities, particularly a pro-inflammatory state and chenges in hematimetric parameters, anemia, thrombocytopenia, and leukocytosis. Therefore, the data presented in this study can contribute to a better understanding and confirmation of the multiple effects of the virus on the human body, especially concerning the hematopoietic system.Verificar o perfil clínico e laboratorial de pacientes internados por COVID-19. Estudo observacional descritivo retrospectivo, com coleta de dados secundários de prontuários de pacientes internados por COVID-19 no período de janeiro a junho de 2021 em um hospital de alta complexidade no município de Criciúma/SC. A população estudada constituiu um total de 497 pacientes, sendo a média de idade de 59,2 anos com desvio padrão de 15,44 e predomínio do sexo masculino (55,3%). Em relação às comorbidades, as mais prevalentes foram diabetes mellitus (23,54%) e hipertensão arterial (35,01%). O principal desfecho clínico foi a alta (62,8%). Quanto aos exames laboratoriais, os pacientes inicialmente apresentaram elevação das provas inflamatórias e leucocitose. E no decorrer da internação, desenvolveram anemia, plaquetopenia e melhora das provas inflamatórias, além de manter a leucocitose. Nesse âmbito, pode-se encontrar alterações laboratoriais nos pacientes, com destaque para o estado pró-inflamatório para os parâmetros hematimétricos. Portanto, os dados apresentados no presente estudo podem contribuir para a melhoria do entendimento e confirmação acerca dos múltiplos efeitos do vírus sobre o corpo humano, especialmente no que tange o sistema hematopoiético

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