Condutas iniciais na Síndrome Coronariana aguda e seu desfecho sobre os quadros de Taquiarritmias: uma revisão sistemática com metanálise: Initial conducts in acute Coronary Syndrome and its outcome on Tachyarrhythmia frames: a systematic review with meta-analysis

Este artigo tem por objetivo realizar uma revisão sistemática de literatura sobre condutas iniciais diante de um quadro síndrome coronariana aguda e seu impacto sobre quadros de taquiarritmias. Trata-se de uma revisão sistemática de literatura baseada em buscas nas bases de dados Biblioteca Virtual em Saúde – BVS, Google Acadêmico, Lilacs, Pubmed e Scientific Electronic Library Online – SciELO. A pesquisa utilizou-se dos seguintes descritores, segundo o DeCS, com seus correspondentes no idioma inglês e espanhol: Arritmias Cardíacas; Taquicardia; Síndrome Coronariana Aguda. Os principais resultados obtidos apontam que a síndrome coronariana aguda, um evento isquêmico do miocárdio, decorrente da hipoperfusão cardíaca, pode resultar em taquiarritmias supraventriculares (TSV) e ventriculares (TV), tendo seu desfecho clínico e prognóstico dependente do intervalo de tempo desde o início do evento e do tipo de taquiarritmia desencadeada. A partir disto, surge a questão sobre quais condutas iniciais tomadas diante de SCA minimizaria desfechos clínicos de taquiarritmias, a fim de garantir um manejo adequado e minimização da morbimortalidade

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

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

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

Embedding resilience in the design of the electricity supply for industrial clients.

This paper proposes an optimization model, using Mixed-Integer Linear Programming (MILP), to support decisions related to making investments in the design of power grids serving industrial clients that experience interruptions to their energy supply due to disruptive events. In this approach, by considering the probabilities of the occurrence of a set of such disruptive events, the model is used to minimize the overall expected cost by determining an optimal strategy involving pre- and post-event actions. The pre-event actions, which are considered during the design phase, evaluate the resilience capacity (absorption, adaptation and restoration) and are tailored to the context of industrial clients dependent on a power grid. Four cases are analysed to explore the results of different probabilities of the occurrence of disruptions. Moreover, two scenarios, in which the probability of occurrence is lowest but the consequences are most serious, are selected to illustrate the model's applicability. The results indicate that investments in pre-event actions, if implemented, can enhance the resilience of power grids serving industrial clients because the impacts of disruptions either are experienced only for a short time period or are completely avoided

Total expected costs of the 4 different cases.

<p>Total expected costs of the 4 different cases.</p

Total expected costs for case 4 for different constraints on financial resources.

<p>Total expected costs for case 4 for different constraints on financial resources.</p

Representation of the electrical connections for industrial clients (C1, …, Ci).

<p>Industrial customers, along with nodes and links, comprise the power grid portion considered in the proposed model and analyses.</p