Impact of COVID-19 on healthcare-associated infections: Antimicrobial consumption does not follow antimicrobial resistance

Background: This study aimed to analyze the Healthcare-Associated Infections (HAI) rates and antimicrobial consumption in Intensive Care Units (ICU) in São Paulo city during the COVID-19 pandemic and compare them with the pre-pandemic period. Methods: This cohort included all hospitals that reported HAI rates (Central-Line-Associated Bloodstream Infection ‒ CLABSI and Ventilator-Associated Pneumonia ‒ VAP), the proportion of microorganisms that caused CLABSI, the proportion of resistant microorganisms, and antimicrobial consumption from January 2017 ‒ December 2020. Hospitals were stratified by the number of beds, Central Venous Catheter (CVC) utilization rate, Mechanical-Ventilation (MV) utilization rate, and type of funding. Statistical analyses were based on time-series plots and regression models. Results: 220 ICUs were included. The authors observed an abrupt increase in CLABSI rates after the pandemic onset. High CLABSI rates during the pandemic were associated with hospital size, funding (public and non-profit private), and low CVC use (≤ 50%). An increase in VAP rates was associated with public hospitals, and high MV use (> 35%). The susceptibility profile of microorganisms did not differ from that of the pre-pandemic period. polymyxin, glycopeptides, and antifungal use increased, especially in COVID-19 ICUs. Conclusions: HAI increased during COVID-19. The microorganisms’ susceptibility profile did not change with the pandemic, but the authors observed a disproportionate increase in large-spectrum antimicrobial drug use

Confiabilidade do Instrumento para Classificação de Idosos quanto à Capacidade para o Autocuidado

OBJECTIVE: To evaluate the reliability of an instrument for classifying elderly people regarding their capacity for self-care, which was developed to assist occupational therapists in attending elderly people at primary healthcare units. METHODS: Stability and internal consistency tests were carried out. To validate the instrument, tests were applied to a sample of 30 individuals aged 60 years and over, on two occasions. The statistical analysis was performed after careful grouping of the responses. This led to the formulation of a simplified version of the instrument. The stability of this version was assessed using the kappa coefficient and the internal consistency by Cronbach's alpha coefficient. RESULTS: The stability ranged from moderate to excellent. The internal consistency was checked only for areas that were shown to be appropriate for using the methodology, based on calculations of Cronbach's alpha: three of the six questions in the "social profile" area and the blocks of basic and instrumental activities of daily living in the "functional capacity" area, which respectively consisted of nine and eight activities. CONCLUSIONS: Following the stability and internal consistency tests, the instrument made it possible to succinctly and simply classify elderly people with regard to their functional capacity for basic and instrumental activities, and to characterize them regarding other aspects of self-care. The evidence regarding its reliability and validity could be expanded by means of new studies.OBJETIVO: Avaliar a confiabilidade do Instrumento para Classificação de Idosos quanto à Capacidade para o Autocuidado, desenvolvido para auxiliar o terapeuta ocupacional na atenção a idosos em unidades básicas de saúde. MÉTODOS: Foram realizados testes de estabilidade e consistência interna. Para validação do Instrumento, os testes foram aplicados à amostra de 30 indivíduos com 60 anos ou mais, em dois momentos. A análise estatística foi realizada a partir de agrupamentos criteriosos de respostas, o que levou à formulação de uma versão simplificada do Instrumento. A estabilidade desta versão foi avaliada pelo coeficiente kappa e a consistência interna pelo coeficiente alpha de Cronbach. RESULTADOS: A estabilidade variou de moderada a excelente. A consistência interna foi verificada somente para áreas que se mostraram adequadas para o uso da metodologia baseada no cálculo do alpha de Cronbach: três das seis questões da área "perfil social" e os blocos das atividades básicas e instrumentais de vida diária da área "capacidade funcional", respectivamente com nove e oito atividades. CONCLUSÕES: Após os testes de estabilidade e consistência interna, o Instrumento possibilita classificação sucinta e simplificada de idosos quanto à capacidade funcional para atividades básicas e instrumentais e sua caracterização quanto aos demais aspectos do autocuidado. Evidências acerca de sua confiabilidade e validade podem ser ampliadas por meio de novos estudos

Beta-2 adrenergic receptor gene polymorphisms Gln27Glu, Arg16Gly in patients with heart failure

<p>Abstract</p> <p>Background -</p> <p>Beta-2 adrenergic receptor gene polymorphisms Gln27Glu, Arg16Gly and Thr164Ile were suggested to have an effect in heart failure. We evaluated these polymorphisms relative to clinical characteristics and prognosis of alarge cohort of patients with heart failure of different etiologies.</p> <p>Methods -</p> <p>We studied 501 patients with heart failure of different etiologies. Mean age was 58 years (standard deviation 14.4 years), 298 (60%) were men. Polymorphisms were identified by polymerase chain reaction-restriction fragment length polymorphism.</p> <p>Results -</p> <p>During the mean follow-up of 12.6 months (standard deviation 10.3 months), 188 (38%) patients died. Distribution of genotypes of polymorphism Arg16Gly was different relative to body mass index (χ²= 9.797;p = 0.04). Overall the probability of survival was not significantly predicted by genotypes of Gln27Glu, Arg16Gly, or Thr164Ile. Allele and haplotype analysis also did not disclose any significant difference regarding mortality. Exploratory analysis through classification trees pointed towards a potential association between the Gln27Glu polymorphism and mortality in older individuals.</p> <p>Conclusion -</p> <p>In this study sample, we were not able to demonstrate an overall influence of polymorphisms Gln27Glu and Arg16Gly of beta-2 receptor gene on prognosis. Nevertheless, Gln27Glu polymorphism may have a potential predictive value in older individuals.</p

Association of Malaria Infection During Pregnancy With Head Circumference of Newborns in the Brazilian Amazon.

Importance: Malaria during pregnancy is associated with adverse events for the fetus and newborn, but the association of malaria during pregnancy with the head circumference of the newborn is unclear. Objective: To investigate the association of malaria during pregnancy with fetal head growth. Design, Setting, and Participants: Two cohort studies were conducted at the general maternity hospital of Cruzeiro do Sul (Acre, Brazil) in the Amazonian region. One cohort study prospectively enrolled noninfected and malaria-infected pregnant women who were followed up until delivery, between January 2013 and April 2015. The other cohort study was assembled retrospectively using clinical and malaria data from all deliveries that occurred between January 2012 and December 2013. Data analyses were conducted from January to August 2017 and revised in November 2018. Clinical data from pregnant women and anthropometric measures of their newborns were evaluated. A total of 600 pregnant women were enrolled through volunteer sampling (prospective cohort study), and 4697 pregnant women were selected by population-based sampling (retrospective cohort study). After application of exclusion criteria, data from 251 (prospective cohort study) and 232 (retrospective cohort study) malaria-infected and 158 (prospective cohort study) and 3650 (retrospective cohort study) noninfected women were evaluated. Exposure: Malaria during pregnancy. Main Outcomes and Measures: The primary end point was the incidence of altered head circumference in newborns delivered from malaria-infected mothers compared with that from noninfected mothers. Secondary end points included measures of placental pathology relative to newborn head circumference. Results: In total, 4291 maternal-child pairs were analyzed. Among 409 newborns in the prospective cohort study, the mothers of 251 newborns had malaria during pregnancy, infected with Plasmodium vivax, Plasmodium falciparum, or both. Among 3882 newborns in the retrospective cohort study, 232 were born from mothers that had malaria during pregnancy. The prevalence of newborns with a small head (19 [30.7%] in the prospective cohort study and 30 [36.6%] in the retrospective cohort study) and the prevalence of microcephaly among newborns (5 [8.1%] in the prospective cohort study and 6 [7.3%] in the retrospective cohort study) were higher among newborns from women infected with P falciparum during pregnancy. Multivariate logistic regression analyses revealed that P falciparum infection during pregnancy represented a significant risk factor for the occurrence of small head circumference in newborns (prospective cohort study: odds ratio, 3.15; 95% CI, 1.52-6.53; P = .002; retrospective cohort study: odds ratio, 1.91; 95% CI, 1.21-3.04; P = .006). Placental pathologic findings corroborated this association, with more syncytial nuclear aggregates and inflammatory infiltrates occurring in placentas of newborns born with decreased head circumference. Conclusions and Relevance: This study indicates that falciparum malaria during pregnancy is associated with decreased head circumference in newborns, which is in turn associated with evidence of placental malaria

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

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