PERFIL EPIDEMIOLÓGICO DA INSUFICIÊNCIA CARDÍACA EM EMERGÊNCIA DE UM HOSPITAL GERAL

A Insuficiência Cardíaca (IC) é uma síndrome clínica complexaque cursa com um comprometimento estrutural oufuncional do enchimento ventricular ou da ejeção sanguínea.São observados um conjunto de sinais como crepitaçõespulmonares, elevação da pressão venosa jugular edeslocamento de batida de ápice de pulmão associados aossintomas típicos como falta de ar, edema e fadiga. Estetrabalho trata-se de um estudo retrospectivo, descritivo eobservacional de pacientes com IC atendidos no período dejaneiro a dezembro de 2015 no serviço de urgência e emergênciado Hospital Municipal de Contagem José LucasFilho. Podemos inferir dos resultados apresentados que aHAS é a comorbidade mais encontrada em pacientes comIC. Considerando que HAS seja uma comorbidade comumem idosos, podemos inferir que se trata de um problemaem ascensão visto o envelhecimento da população de umamaneira geral. Este dado nos leva a acreditar que o controledos níveis pressóricos ainda na atenção primária seria amelhor maneira de prevenir uma futura IC

Perfil dos casos notificados de Tuberculose no município de Teresina-PI nos anos de 2012-2021

A tuberculose é uma doença que acompanha a humanidade há milênios, relacionada a estratos sociais ligados à pobreza e à má distribuição de renda. Ainda, acomete pessoas, principalmente, em idade produtiva, promovendo dependência do poder público, constituindo-se assim, em um grave problema de Saúde Coletiva. O estudo tem como objetivo analisar o perfil clínico epidemiológico de pacientes notificados com tuberculose em unidades básicas de saúde no município de Teresina-PI nos anos de 2012 a 2021. Trata-se de um estudo epidemiológico, quantitativo, do tipo descritivo e retrospectivo que analisou o perfil epidemiológico de pacientes com tuberculose residentes do município de Teresina-PI nos anos de 2012 a 2021. Entre os anos de 2012-2021 houve variação no número de casos de tuberculose notificados, apresentando um total de 3930 casos, média de 393 ao ano em que 57% o diagnóstico foi confirmado laboratorialmente. O presente estudo visa contribuir para o aprimoramento das políticas públicas de saúde com foco na prevenção, orientação e adoção de medidas que minimizem este quadro, com atenção especial para público masculino, na faixa etária entre 30-59 anos que são os principais responsáveis pelas notificações de tuberculose

The main diseases in the culture of pineapple: a review

Pineapple is a crop of great importance, having vitamins, minerals and capable of preventing diseases. Therefore, several researchers are interested in studying this crop, in addition to its use for other purposes, such as the production of juice pulp, jellies, sweets and other products, with its in natura form being the most sought after among countries. However, the attack of pathogens reduces pineapple production to worrying levels, and when not controlled, it even eradicates the entire plantation. Based on this, this review aimed to show the recent discoveries about the pineapple culture, emphasizing, mainly, the main diseases of this production chain. After gathering the main information on the most frequent diseases in pineapple production fields, we observed that fusariosis is considered the main disease of pineapple, followed by black spot, eye rot and root rot, being in short knowledge of these by producers is important in order to avoid irreversible damage. It is understood that more research is needed, since in the literature there are few field studies on this crop, especially with regard to seeking alternative means of controlling these diseases, so that the dissemination of this knowledge provides better information on agronomic interests

COVID-19 outcomes in people living with HIV: Peering through the waves

Objective: To evaluate clinical characteristics and outcomes of COVID-19 patients infected with HIV, and to compare with a paired sample without HIV infection. Methods: This is a substudy of a Brazilian multicentric cohort that comprised two periods (2020 and 2021). Data was obtained through the retrospective review of medical records. Primary outcomes were admission to the intensive care unit, invasive mechanical ventilation, and death. Patients with HIV and controls were matched for age, sex, number of comorbidities, and hospital of origin using the technique of propensity score matching (up to 4:1). They were compared using the Chi-Square or Fisher's Exact tests for categorical variables and the Wilcoxon for numerical variables. Results: Throughout the study, 17,101 COVID-19 patients were hospitalized, and 130 (0.76%) of those were infected with HIV. The median age was 54 (IQR: 43.0;64.0) years in 2020 and 53 (IQR: 46.0;63.5) years in 2021, with a predominance of females in both periods. People Living with HIV (PLHIV) and their controls showed similar prevalence for admission to the ICU and invasive mechanical ventilation requirement in the two periods, with no significant differences. In 2020, in-hospital mortality was higher in the PLHIV compared to the controls (27.9% vs. 17.7%; p = 0.049), but there was no difference in mortality between groups in 2021 (25.0% vs. 25.1%; p > 0.999). Conclusions: Our results reiterate that PLHIV were at higher risk of COVID-19 mortality in the early stages of the pandemic, however, this finding did not sustain in 2021, when the mortality rate is similar to the control group

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

ABC₂-SPH risk score for in-hospital mortality in COVID-19 patients:development, external validation and comparison with other available scores

Objectives: The majority of available scores to assess mortality risk of coronavirus disease 2019 (COVID-19) patients in the emergency department have high risk of bias. Therefore, this cohort aimed to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients and to compare this score with other existing ones. Methods: Consecutive patients (≥ 18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March–July, 2020. The model was validated in the 1054 patients admitted during August–September, as well as in an external cohort of 474 Spanish patients. Results: Median (25–75th percentile) age of the model-derivation cohort was 60 (48–72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count, and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829–0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833–0.885]) and Spanish (0.894 [95% CI 0.870–0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions: An easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation was designed and validated for early stratification of in-hospital mortality risk of patients with COVID-19.</p

Diagnóstico diferencial da Síndrome de Takotsubo e infarto agudo do miocárdio: uma revisão sistemática: Differential diagnosis of Takotsubo Syndrome and acute myocardial infarction: a systematic review

A cardiomiopatia de Takotsubo e o infarto agudo do miocárdio compartilham apresentação clínica e risco de morte semelhantes, embora uma das diferenças mais importantes seja a ausência de doença coronariana obstrutiva na cardiomiopatia de Takotsubo. Neste estudo, tem-se como objetivo analisar a literatura disponível avaliando o diagnóstico diferencial entre pacientes com CTT em comparação com pacientes com infarto agudo do miocárdio. Para isso, foi realizada uma revisão sistemática, utilizando-se a Pubmed e a Medline como base de dados. A partir da análise dos estudos e interpretação de suas principais descobertas, concluiu-se que para pacientes com CTT, outras condições e comorbidades, em vez de apenas dislipidemia e/ou outros fatores de risco estabelecidos, sejam responsáveis por um risco de morte comparável ao de IAM. No entanto, as conclusões desse estudo têm várias limitaçõe

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