RELAÇÃO DA INFORMAÇÃO SOBRE DOENÇAS INFECCIOSAS OFERTADA PELA MÍDIA E ASSIMILADA PELA POPULAÇÃO DE ANÁPOLIS

Frequentemente os meios de comunicação em massa são utilizados de maneira a confundir o ouvinte ou selecionar informações pontuais, sendo então pouco efetivos àqueles que desejariam extrair dos mesmos um conhecimento verdadeiro e íntegro. Isso não tem sido diferente em relação à educação em saúde, comprometendo assim a qualidade de vida da população. O objetivo deste pré-projeto é analisar o impacto da mídia na construção do conhecimento em saúde levado à população. O estudo pretende analisar se as informações passadas pela mídia são duradouras, tem qualidade, geram crédito ou descrédito na população, criam satisfação ou não; refletem a realidade, são impositivas ou não, e por fim, se mostram qual o papel da mídia no controle das epidemias. A metodologia será a pesquisa observacional-descritiva, com informações coletadas através de questionário quali-quantitativo, feito à população em forma de entrevista, em ambientes públicos. Essas informações midiáticas, que influenciam as pessoas, suas atitudes e formas de enxergarem a realidade, são também responsáveis pela educação em saúde e são capazes de construir o comportamento da população diante das doenças e das epidemias que assolam a sociedade.  Diante disso, espera-se que a informação em saúde sobre as doenças infecciosas passada pela mídia não tenha caráter duradouro e seja de baixa qualidade. Espera-se que a população confie na maioria das informações passadas, mas que, entretanto, não modifique seus hábitos diante da informação passada, visando prevenir doenças infecciosas. Presume-se que o modelo da informação seja impositivo e que a mídia tenha um importante papel no controle das epidemias

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

Human herpesvirus 8 (HHV-8) detected by nested polymerase chain reaction (PCR) in HIV patients with or without Kaposi's sarcoma. An analytic cross-sectional study

CONTEXT AND OBJECTIVE: Kaposi's sarcoma (KS) is a common neoplastic disease in AIDS patients. The aim of this study was to evaluate the frequency of human herpesvirus 8 (HHV-8) infection in human immunodeficiency virus (HIV)-infected patients, with or without KS manifestations and correlate HHV-8 detection with KS staging. DESIGN AND SETTING: Analytic cross-sectional study conducted in a public tertiary-level university hospital in Ribeirão Preto, São Paulo, Brazil. METHODS: Antibodies against HHV-8 lytic-phase antigens were detected by means of the immunofluorescence assay. HHV-8 DNA was detected in the patient samples through a nested polymerase chain reaction (nested PCR) that amplified a region of open reading frame (ORF)-26 of HHV-8. RESULTS: Anti-HHV-8 antibodies were detected in 30% of non-KS patients and 100% of patients with KS. Furthermore, the HHV-8 DNA detection rates observed in HIV-positive patients with KS were 42.8% in serum, 95.4% in blood samples and 100% in skin biopsies; and in patients without KS, the detection rate was 4% in serum. Out of the 16 serum samples from patients with KS-AIDS who were classified as stage II, two were positive (12.5%); and out of the 33 samples from patients in stage IV, 19 (57.6%) were positive. CONCLUSION: We observed an association between HHV-8 detection and disease staging, which was higher in the serum of patients in stage IV. This suggests that detection of HHV-8 DNA in serum could be very useful for clinical assessment of patients with KS and for monitoring disease progression

PP08 / PP09 / PP11

Três Trabalho

Mechanical ventilation and death in pregnant patients admitted for COVID-19: a prognostic analysis from the Brazilian COVID-19 registry score

Abstract Background The assessment of clinical prognosis of pregnant COVID-19 patients at hospital presentation is challenging, due to physiological adaptations during pregnancy. Our aim was to assess the performance of the ABC2-SPH score to predict in-hospital mortality and mechanical ventilation support in pregnant patients with COVID-19, to assess the frequency of adverse pregnancy outcomes, and characteristics of pregnant women who died. Methods This multicenter cohort included consecutive pregnant patients with COVID-19 admitted to the participating hospitals, from April/2020 to March/2022. Primary outcomes were in-hospital mortality and the composite outcome of mechanical ventilation support and in-hospital mortality. Secondary endpoints were pregnancy outcomes. The overall discrimination of the model was presented as the area under the receiver operating characteristic curve (AUROC). Overall performance was assessed using the Brier score. Results From 350 pregnant patients (median age 30 [interquartile range (25.2, 35.0)] years-old]), 11.1% had hypertensive disorders, 19.7% required mechanical ventilation support and 6.0% died. The AUROC for in-hospital mortality and for the composite outcome were 0.809 (95% IC: 0.641–0.944) and 0.704 (95% IC: 0.617–0.792), respectively, with good overall performance (Brier = 0.0384 and 0.1610, respectively). Calibration was good for the prediction of in-hospital mortality, but poor for the composite outcome. Women who died had a median age 4 years-old higher, higher frequency of hypertensive disorders (38.1% vs. 9.4%, p < 0.001) and obesity (28.6% vs. 10.6%, p = 0.025) than those who were discharged alive, and their newborns had lower birth weight (2000 vs. 2813, p = 0.001) and five-minute Apgar score (3.0 vs. 8.0, p < 0.001). Conclusions The ABC2-SPH score had good overall performance for in-hospital mortality and the composite outcome mechanical ventilation and in-hospital mortality. Calibration was good for the prediction of in-hospital mortality, but it was poor for the composite outcome. Therefore, the score may be useful to predict in-hospital mortality in pregnant patients with COVID-19, in addition to clinical judgment. Newborns from women who died had lower birth weight and Apgar score than those who were discharged alive