Abordagem oncoplástica no tratamento conservador do câncer mamário: análise de custos

PURPOSE: To analyze the direct costs of conservative surgical treatment of breast cancer, performed in a university hospital, to the Brazilian National Health Care Public System (SUS), checking the impact of the oncoplastic approach on these costs. METHODS: One hundred thirty eight breast cancer patients who had undergone conservative treatment with oncoplastic approach (n=36) or not (control group, n=102), in the period from 2005 to 2010, were enrolled. Sociodemographic and clinical data were recorded. The direct costs of the surgical procedure were obtained and analyzed. RESULTS: Groups did not differ in regard to age (p=0.963), and patients in oncoplastic group had a longer time of hospital stay (p=0.000). The median direct cost for the oncoplastic group was R$461.00 and for the control group was R$229.00 (p=0.000). CONCLUSION: The oncoplastic approach has generated higher direct costs in conservative surgical treatment of breast cancer to SUS.OBJETIVO: Analisar os custos diretos do tratamento cirúrgico conservador do câncer mamário, realizado pelo Sistema Único de Saúde (SUS) em um hospital universitário, verificando o impacto da abordagem oncoplástica sobre estes custos. MÉTODOS: Foram incluídas 138 pacientes submetidas ao tratamento conservador do câncer mamário pelo SUS, com abordagem oncoplástica (n=36) ou não (grupo controle, n=102), no período de 2005 a 2010. Foram registrados dados sócio-demográficos e da operação. Os custos diretos do procedimento cirúrgico foram obtidos e analisados. RESULTADOS: Não houve diferença entre os grupos quanto à idade (p=0.963), e o tempo de internação hospitalar foi maior no grupo oncoplástica (p=0,000). A mediana dos custos diretos do grupo oncoplástica foi de R$461,00 e do grupo controle foi de R$229,00 (p=0,000). CONCLUSÃO: A abordagem oncoplástica gerou custos diretos maiores para o tratamento cirúrgico conservador do câncer mamário pelo SUS.UNIVÁS Plastic Surgery DivisionUNIVÁS Mastology DivisionUNIVÁS Hospital das Clínicas Samuel Libânio Plastic Surgery DivisionUNIVÁS School of AdministrationUNIVÁS Bioestatistics DivisionUNIFESP Plastic Surgery DivisionUNIFESP Head of Plastic Surgery DivisionUNIFESP, Plastic Surgery DivisionUNIFESP, Head of Plastic Surgery DivisionSciEL

AVALIAÇÃO DA ATIVIDADE ANTIFÚNGICA DO EXTRATO AQUOSO DAS FOLHAS DE Libidibia ferrea (MART. EX TUL.) L. P. QUEIROZ (PAU FERRO)

Os fungos são micro-organismos comuns no ambiente, sendo que alguns vivem de forma comensal, habitando a superfície da pele, mucosas, trato respiratório, gastrointestinal e urogenital de humanos e animais, como é o caso das espécies pertencentes ao gênero Candida. O fluconazol é um dos fármacos mais usados para combater as enfermidades causadas por esses micro-organismos, atuando em um alvo específico dos fungos, entretanto, muitas linhagens já lhe são resistentes. A resistência a medicamentos tem despertado a necessidade de procurar novas alternativas de cunho natural. Libidibia ferrea popularmente conhecida como jucá ou pau ferro é uma espécie vegetal da família Fabaceae, que possui em sua composição substâncias avaliadas quanto a seu efeito antimicrobiano. Este estudo tem como objetivo verificar o efeito antifúngico do extrato, sozinho e combinado com o Fluconazol na inibição de crescimento de Candida albicans, Candida tropicalis e Candida kruzei, bem como na virulência fúngica. Os ensaios para determinação da Concentração Inibitória de 50% dos micro-organismos (CI50), foram realizados por microdiluição (8.192 a 8 μg/mL) e na combinação extrato/fármaco, o extrato foi avaliado em concentração subinibitória (CFM/16). A Concentração Fungicida Mínima (CFM) foi verificada por subcultivo em meio sólido. O efeito inibidor sobre a morfologia fúngica foi verificado em câmaras úmidas. O extrato apresentou efeito inibidor sobre os micro-organismos em concentrações elevadas e sem relevância clínica, demonstrando um comportamento de resistência ao extrato em questão. A CI50 evidencia a potencialização do fármaco pelo extrato, onde a combinação dos dois reduziu a concentração de efeito do fluconazol frente a todas as linhagens. A CFM foi ≥ 16.384 µg/mL. Em relação a morfologia fúngica, o extrato inibiu a transição morfológica de C. albicans e C. tropicalis na concentração mais elevada. A espécie tem constituintes ativos para potencialização de efeito de fármaco comercial e para interferir na expressão de um importante fator de virulência fúngica

MENOPAUSA E SUAS CONSEQUÊNCIAS PSICOLÓGICAS.

Introduction: Menopause, a natural stage in women's lives, marks the end of the reproductive period and is often accompanied by hormonal and physical changes. Furthermore, menopause can have significant implications for women's mental health, influencing their emotional and psychological states. Objective: This study aims to investigate the psychological consequences of menopause in women, exploring the emotional and behavioral impacts associated with this transition phase. Methodology: This is an integrative literature review, with an approach that allows the synthesis of studies with different methodologies, including qualitative, quantitative and mixed studies. Searches were carried out in electronic databases, such as PubMed, PsycINFO and Scopus, using keywords related to menopause and mental health. Studies published in the last 10 years were selected. Results: The results highlighted a variety of psychological consequences related to menopause. Many participants reported symptoms of anxiety, depression and mood swings. In addition, self-esteem and body image were affected in some cases. Quality of life was also perceived as compromised due to these emotional challenges. Final Considerations: The study highlights the importance of understanding the psychological implications of menopause and recognizing that this phase can be accompanied by significant emotional difficulties for some women. The multidimensional approach, which considers both the biological and psychological aspects of menopause, is essential to provide adequate support to women in this transition.Introdução: A menopausa, um estágio natural na vida de mulheres, marca o fim do período reprodutivo e é frequentemente acompanhada por mudanças hormonais e físicas. Além disso, a menopausa pode ter implicações significativas para a saúde mental das mulheres, influenciando seus estados emocionais e psicológicos. Objetivo: Este estudo tem como objetivo investigar as consequências psicológicas da menopausa em mulheres, explorando os impactos emocionais e comportamentais associados a essa fase de transição. Metodologia: Trata-se de uma revisão integrativa da literatura, sendo uma abordagem que permite a síntese de estudos de diferentes metodologias, incluindo estudos qualitativos, quantitativos e mistos. Foram realizadas buscas em bases de dados eletrônicas, como PubMed, PsycINFO e Scopus, utilizando palavras-chave relacionadas à menopausa e saúde mental. Foram selecionados estudos publicados nos últimos 10 anos. Resultados: Os resultados destacaram uma variedade de consequências psicológicas relacionadas à menopausa. Muitas participantes relataram sintomas de ansiedade, depressão e oscilações de humor. Além disso, a autoestima e a imagem corporal foram afetadas em alguns casos. A qualidade de vida também foi percebida como comprometida devido a esses desafios emocionais. Considerações Finais: O estudo evidencia a importância de compreender as implicações psicológicas da menopausa e reconhecer que essa fase pode ser acompanhada por dificuldades emocionais significativas para algumas mulheres. A abordagem multidimensional, que considera tanto os aspectos biológicos quanto os psicológicos da menopausa, é essencial para fornecer um suporte adequado às mulheres nessa transição

High anti-SARS-CoV-2 antibody seroconversion rates before the second wave in Manaus, Brazil, and the protective effect of social behaviour measures: results from the prospective DETECTCoV-19 cohort

Background: The city of Manaus, Brazil, has seen two collapses of the health system due to the COVID-19 pandemic. We report anti-SARS-CoV-2 nucleocapsid IgG antibody seroconversion rates and associated risk factors in Manaus residents before the second wave of the epidemic in Brazil. Methods: A convenience sample of adult (aged ≥18 years) residents of Manaus was recruited through online and university website advertising into the DETECTCoV-19 study cohort. The current analysis of seroconversion included a subgroup of DETECTCoV-19 participants who had at least two serum sample collections separated by at least 4 weeks between Aug 19 and Oct 2, 2020 (visit 1), and Oct 19 and Nov 27, 2020 (visit 2). Those who reported (or had no data on) having a COVID-19 diagnosis before visit 1, and who were positive for anti-SARS-CoV-2 nucleocapsid IgG antibodies at visit 1 were excluded. Using an in-house ELISA, the reactivity index (RI; calculated as the optical density ratio of the sample to the negative control) for serum anti-SARS-CoV-2 nucleocapsid IgG antibodies was measured at both visits. We calculated the incidence of seroconversion (defined as RI values ≤1·5 at visit 1 and ≥1·5 at visit 2, and a ratio >2 between the visit 2 and visit 1 RI values) during the study period, as well as incidence rate ratios (IRRs) through cluster-corrected and adjusted Poisson regression models to analyse associations between seroconversion and variables related to sociodemographic characteristics, health access, comorbidities, COVID-19 exposure, protective behaviours, and symptoms. Findings: 2496 DETECTCoV-19 cohort participants returned for a follow-up visit between Oct 19 and Nov 27, 2020, of whom 204 reported having COVID-19 before the first visit and 24 had no data regarding previous disease status. 559 participants were seropositive for anti-SARS-CoV-2 nucleocapsid IgG antibodies at baseline. Of the remaining 1709 participants who were seronegative at baseline, 71 did not meet the criteria for seroconversion and were excluded from the analyses. Among the remaining 1638 participants who were seronegative at baseline, 214 showed seroconversion at visit 2. The seroconversion incidence was 13·06% (95% CI 11·52–14·79) overall and 6·78% (5·61–8·10) for symptomatic seroconversion, over a median follow-up period of 57 days (IQR 54–61). 48·1% of seroconversion events were estimated to be asymptomatic. The sample had higher proportions of affluent and higher-educated people than those reported for the Manaus city population. In the fully adjusted and corrected model, risk factors for seroconversion before visit 2 were having a COVID-19 case in the household (IRR 1·49 [95% CI 1·21–1·83]), not wearing a mask during contact with a person with COVID-19 (1·25 [1·09–1·45]), relaxation of physical distancing (1·31 [1·05–1·64]), and having flu-like symptoms (1·79 [1·23–2·59]) or a COVID-19 diagnosis (3·57 [2·27–5·63]) between the first and second visits, whereas working remotely was associated with lower incidence (0·74 [0·56–0·97]). Interpretation: An intense infection transmission period preceded the second wave of COVID-19 in Manaus. Several modifiable behaviours increased the risk of seroconversion, including non-compliance with non-pharmaceutical interventions measures such as not wearing a mask during contact, relaxation of protective measures, and non-remote working. Increased testing in high-transmission areas is needed to provide timely information about ongoing transmission and aid appropriate implementation of transmission mitigation measures. Funding: Ministry of Education, Brazil; Fundação de Amparo à Pesquisa do Estado do Amazonas; Pan American Health Organization (PAHO)/WHO.World Health OrganizationRevisión por pare

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