Associations between cesarean delivery and child mortality: A national record linkage longitudinal study of 17.8 million births in Brazil.

BACKGROUND: There is an increasing use of cesarean delivery (CD) based on preference rather than on medical indication. However, the extent to which nonmedically indicated CD benefits or harms child survival remains unclear. Our hypothesis was that in groups with a low indication for CD, this procedure would be associated with higher child mortality and in groups with a clear medical indication CD would be associated with improved child survival chances. METHODS AND FINDINGS: We conducted a population-based cohort study in Brazil by linking routine data on live births between January 1, 2012 and December 31, 2018 and assessing mortality up to 5 years of age. Women with a live birth who contributed records during this period were classified into one of 10 Robson groups based on their pregnancy and delivery characteristics. We used propensity scores to match CD with vaginal deliveries (1:1) and prelabor CD with unscheduled CD (1:1) and estimated associations with child mortality using Cox regressions. A total of 17,838,115 live births were analyzed. After propensity score matching (PSM), we found that live births to women in groups with low expected frequencies of CD (Robson groups 1 to 4) had a higher death rate up to age 5 years if they were born via CD compared with vaginal deliveries (HR = 1.25, 95% CI: 1.22 to 1.28; p < 0.001). The relative rate was greatest in the neonatal period (HR = 1.39, 95% CI: 1.34 to 1.45; p < 0.001). There was no difference in mortality rate when comparing offspring born by a prelabor CD to those born by unscheduled CD. For the live births to women with a CD in a prior pregnancy (Robson group 5), the relative rates for child mortality were similar for those born by CD compared with vaginal deliveries (HR = 1.05, 95% CI: 1.00 to 1.10; p = 0.024). In contrast, for live births to women in groups with high expected rates of CD (Robson groups 6 to 10), the child mortality rate was lower for CD than for vaginal deliveries (HR = 0.90, 95% CI: 0.89 to 0.91; p < 0.001), particularly in the neonatal period (HR = 0.84, 95% CI: 0.83 to 0.85; p < 0.001). Our results should be interpreted with caution in clinical practice, since relevant clinical data on CD indication were not available. CONCLUSIONS: In this study, we observed that in Robson groups with low expected frequencies of CD, this procedure was associated with a 25% increase in child mortality. However, in groups with high expected frequencies of CD, the findings suggest that clinically indicated CD is associated with a reduction in child mortality

Determinants of intensive insulin therapeutic regimens in patients with type 1 diabetes: data from a nationwide multicenter survey in Brazil

Background: To evaluate the determinants of intensive insulin regimens (ITs) in patients with type 1 diabetes (T1D).Methods: This multicenter study was conducted between December 2008 and December 2010 in 28 public clinics in 20 Brazilian cities. Data were obtained from 3,591 patients (56.0% female, 57.1% Caucasian). Insulin regimens were classified as follows: group 1, conventional therapy (CT) (intermediate human insulin, one to two injections daily); group 2 (three or more insulin injections of intermediate plus regular human insulin); group 3 (three or more insulin injections of intermediate human insulin plus short-acting insulin analogues); group 4, basal-bolus (one or two insulin injections of long-acting plus short-acting insulin analogues or regular insulin); and group 5, basal-bolus with continuous subcutaneous insulin infusion (CSII). Groups 2 to 5 were considered IT groups.Results: We obtained complete data from 2,961 patients. Combined intermediate plus regular human insulin was the most used therapeutic regimen. CSII was used by 37 (1.2%) patients and IT by 2,669 (90.2%) patients. More patients on IT performed self-monitoring of blood glucose and were treated at the tertiary care level compared to CT patients (p < 0.001). the majority of patients from all groups had HbA1c levels above the target. Overweight or obesity was not associated with insulin regimen. Logistic regression analysis showed that economic status, age, ethnicity, and level of care were associated with IT (p < 0.001).Conclusions: Given the prevalence of intensive treatment for T1D in Brazil, more effective therapeutic strategies are needed for long term-health benefits.Farmanguinhos/Fundacao Oswaldo Cruz/National Health MinistryBrazilian Diabetes SocietyFundacao do Amparo a Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Univ Estado Rio de Janeiro, Unit Diabet, BR-20551030 Rio de Janeiro, BrazilBaurus Diabet Assoc, São Paulo, BrazilFed Univ São Paulo State, Diabet Unit, São Paulo, BrazilFed Univ Hosp Porto Alegre, Porto Alegre, BrazilUniv Hosp São Paulo, Diabet Unit, São Paulo, BrazilUniv Fed Rio de Janeiro, Rio de Janeiro, BrazilUniv Fed Ceara, Fortaleza, Ceara, BrazilSanta Casa Misericordia, Belo Horizonte, MG, BrazilSanta Casa Misericordia São Paulo, São Paulo, BrazilUniv Fed Amazonas, Manaus, Amazonas, BrazilHosp Geral de Bonsucesso, Rio de Janeiro, BrazilHosp Univ Clementino Fraga Filho IPPMG, Rio de Janeiro, BrazilUniv Hosp São Paulo, São Paulo, BrazilFac Ciencias Med Santa Casa São Paulo, São Paulo, BrazilUniv São Paulo, Inst Crianca, Hosp Clin, São Paulo, BrazilUniv São Paulo, Fac Med Ribeirao Preto, Hosp Clin, Ribeirao Preto, BrazilAmbulatorio Fac Estadual Med Sao Jose Rio Preto, Ribeirao Preto, BrazilEscola Paulista Med, Ctr Diabet, Ribeirao Preto, BrazilClin Endocrinol Santa Casa Belo Horizonte, Belo Horizonte, MG, BrazilUniv Estadual Londrina, Londrina, BrazilUniv Fed Parana, Hosp Clin, Porto Alegre, RS, BrazilInst Crianca Com Diabet Rio Grande Sul, Rio Grande Do Sul, RS, BrazilGrp Hosp Conceicao, Inst Crianca Com Diabet, Porto Alegre, RS, BrazilHosp Univ Santa Catarina, Florianopolis, SC, BrazilInst Diabet Endocrinol Joinville, Joinville, BrazilHosp Reg Taguatinga, Brasilia, DF, BrazilHosp Geral Goiania, Goiania, Go, BrazilCtr Diabet & Endocrinol Estado Bahia, Goiania, Go, BrazilUniv Fed Maranhao, Sao Luis, BrazilCtr Integrado Diabet & Hipertensao Ceara, Fortaleza, Ceara, BrazilUniv Fed Sergipe, Aracaju, BrazilHosp Univ Alcides Carneiro, Campina Grande, BrazilHosp Univ Joao de Barros Barreto, Belem, Para, BrazilFed Univ São Paulo State, Diabet Unit, São Paulo, BrazilUniv Hosp São Paulo, Diabet Unit, São Paulo, BrazilUniv Hosp São Paulo, São Paulo, BrazilEscola Paulista Med, Ctr Diabet, Ribeirao Preto, BrazilWeb of Scienc

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

Regional differences in clinical care among patients with type 1 diabetes in Brazil: Brazilian Type 1 Diabetes Study Group

Background\ud To determine the characteristics of clinical care offered to type 1 diabetic patients across the four distinct regions of Brazil, with geographic and contrasting socioeconomic differences. Glycemic control, prevalence of cardiovascular risk factors, screening for chronic complications and the frequency that the recommended treatment goals were met using the American Diabetes Association guidelines were evaluated.\ud \ud Methods\ud This was a cross-sectional, multicenter study conducted from December 2008 to December 2010 in 28 secondary and tertiary care public clinics in 20 Brazilian cities in north/northeast, mid-west, southeast and south regions. The data were obtained from 3,591 patients (56.0% females and 57.1% Caucasians) aged 21.2 ± 11.7 years with a disease duration of 9.6 ± 8.1 years (<1 to 50 years).\ud \ud Results\ud Overall, 18.4% patients had HbA1c levels <7.0%, and 47.5% patients had HbA1c levels ≥ 9%. HbA1c levels were associated with lower economic status, female gender, age and the daily frequency of self-blood glucose monitoring (SBGM) but not with insulin regimen and geographic region. Hypertension was more frequent in the mid-west (32%) and north/northeast (25%) than in the southeast (19%) and south (17%) regions (p<0.001). More patients from the southeast region achieved LDL cholesterol goals and were treated with statins (p<0.001). Fewer patients from the north/northeast and mid-west regions were screened for retinopathy and nephropathy, compared with patients from the south and southeast. Patients from the south/southeast regions had more intensive insulin regimens than patients from the north/northeast and mid-west regions (p<0.001). The most common insulin therapy combination was intermediate-acting with regular human insulin, mainly in the north/northeast region (p<0.001). The combination of insulin glargine with lispro and glulisine was more frequently used in the mid-west region (p<0.001). Patients from the north/northeast region were younger, non-Caucasian, from lower economic status, used less continuous subcutaneous insulin infusion, performed less SBGM and were less overweight/obese (p<0.001).\ud \ud Conclusions\ud A majority of patients, mainly in the north/northeast and mid-west regions, did not meet metabolic control goals and were not screened for diabetes-related chronic complications. These results should guide governmental health policy decisions, specific to each geographic region, to improve diabetes care and decrease the negative impact diabetes has on the public health system.We thank Mrs. Karianne Aroeira Davidson, Mrs. Anna Maria Ferreira, Mrs. Elisangela Santos and Sandro Sperandei for their technical assistance.This work was supported by grants from Farmanguinhos/Fundação Oswaldo Cruz/National Health Ministry, the Brazilian Diabetes Society, Fundação do Amparo à Pesquisa do Estado do Rio de Janeiro, and Conselho Nacional de Desenvolvimento Científico e Tecnológico do Brasil

Genomic Surveillance of Yellow Fever Virus Epizootic in São Paulo, Brazil, 2016 – 2018

São Paulo, a densely inhabited state in southeast Brazil that contains the fourth most populated city in the world, recently experienced its largest yellow fever virus (YFV) outbreak in decades. YFV does not normally circulate extensively in São Paulo, so most people were unvaccinated when the outbreak began. Surveillance in non-human primates (NHPs) is important for determining the magnitude and geographic extent of an epizootic, thereby helping to evaluate the risk of YFV spillover to humans. Data from infected NHPs can give more accurate insights into YFV spread than when using data from human cases alone. To contextualise human cases, identify epizootic foci and uncover the rate and direction of YFV spread in São Paulo, we generated and analysed virus genomic data and epizootic case data from NHPs in São Paulo. We report the occurrence of three spatiotemporally distinct phases of the outbreak in São Paulo prior to February 2018. We generated 51 new virus genomes from YFV positive cases identified in 23 different municipalities in São Paulo, mostly sampled from NHPs between October 2016 and January 2018. Although we observe substantial heterogeneity in lineage dispersal velocities between phylogenetic branches, continuous phylogeographic analyses of generated YFV genomes suggest that YFV lineages spread in São Paulo at a mean rate of approximately 1km per day during all phases of the outbreak. Viral lineages from the first epizootic phase in northern São Paulo subsequently dispersed towards the south of the state to cause the second and third epizootic phases there. This alters our understanding of how YFV was introduced into the densely populated south of São Paulo state. Our results shed light on the sylvatic transmission of YFV in highly fragmented forested regions in São Paulo state and highlight the importance of continued surveillance of zoonotic pathogens in sentinel species

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

18S rDNA sequences from microeukaryotes reveal oil indicators in mangrove sediment.

BACKGROUND: Microeukaryotes are an effective indicator of the presence of environmental contaminants. However, the characterisation of these organisms by conventional tools is often inefficient, and recent molecular studies have revealed a great diversity of microeukaryotes. The full extent of this diversity is unknown, and therefore, the distribution, ecological role and responses to anthropogenic effects of microeukaryotes are rather obscure. The majority of oil from oceanic oil spills (e.g., the May 2010 accident in the Gulf of Mexico) converges on coastal ecosystems such as mangroves, which are threatened with worldwide disappearance, highlighting the need for efficient tools to indicate the presence of oil in these environments. However, no studies have used molecular methods to assess the effects of oil contamination in mangrove sediment on microeukaryotes as a group. METHODOLOGY/PRINCIPAL FINDINGS: We evaluated the population dynamics and the prevailing 18S rDNA phylotypes of microeukaryotes in mangrove sediment microcosms with and without oil contamination, using PCR/DGGE and clone libraries. We found that microeukaryotes are useful for monitoring oil contamination in mangroves. Our clone library analysis revealed a decrease in both diversity and species richness after contamination. The phylogenetic group that showed the greatest sensitivity to oil was the Nematoda. After contamination, a large increase in the abundance of the groups Bacillariophyta (diatoms) and Biosoecida was detected. The oil-contaminated samples were almost entirely dominated by organisms related to Bacillariophyta sp. and Cafeteria minima, which indicates that these groups are possible targets for biomonitoring oil in mangroves. The DGGE fingerprints also indicated shifts in microeukaryote profiles; specific band sequencing indicated the appearance of Bacillariophyta sp. only in contaminated samples and Nematoda only in non-contaminated sediment. CONCLUSIONS/SIGNIFICANCE: We believe that the microeukaryotic targets indicated by our work will be of great applicability in biomonitoring hydrocarbons in mangroves under oil contamination risk or during recovery strategies