Distribution of Blastocystis subtypes isolated from humans from an urban community in Rio de Janeiro, Brazil

Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Estudos Integrados em Protozoologia. Rio de Janeiro, RJ. Brasil.Fundação Oswaldo Cruz. Instituto Fernandes Figueira. Departamento de Ginecologia e Obstetrícia. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Faculdade de Medicina, Departamento de Medicina Preventiva. Rio de Janeiro, RJ, brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Estudos Integrados em Protozoologia. Rio de Janeiro, RJ. Brasil.Universidade Federal Fluminense. Hospital Universitário Antonio Pedro. Niterói, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Estudos Integrados em Protozoologia. Rio de Janeiro, RJ. Brasil.Blastocystis is a cosmopolitan protist parasite found in the human gastrointestinal tract and is highly prevalent in developing countries. Recent molecular studies have revealed extensive genetic diversity, which has been classified into different subtypes (STs) based on sequence analysis of small subunit ribosomal RNA gene. Blastocystis is one of the most common fecal parasites in Brazil, but the diversity of subtypes remains unknown in the country. This study aimed to determine the distribution of Blastocystis STs in an urban community in Duque de Caxias, Rio de Janeiro, Brazil

Spatial and Molecular Epidemiology of Giardia intestinalis Deep in the Amazon, Brazil

Current control policies for intestinal parasitosis focuses on soil-transmitted helminths, being ineffective against Giardia intestinalis, a highly prevalent protozoon that impacts children's nutritional status in developing countries. The objective of this study was to explore spatial and molecular epidemiology of Giardia intestinalis in children of Amerindian descent in the Brazilian Amazon.A cross sectional survey was performed in the Brazilian Amazon with 433 children aged 1 to 14 years. Fecal samples were processed through parasitological techniques and molecular characterization. Prevalence of G. intestinalis infection was 16.9% (73/433), reaching 22.2% (35/158) among children aged 2-5 years, and a wide distribution throughout the city with some hot spots. Positivity-rate was similar among children living in distinct socioeconomic strata (48/280 [17.1%] and 19/116 [16.4%] below and above the poverty line, respectively). Sequencing of the β-giardin gene revealed 52.2% (n = 12) of assemblage A and 47.8% (n = 11) of assemblage B with high haplotype diversity for the latter. The isolates clustered into two well-supported G. intestinalis clades. A total of 38 haplotypes were obtained, with the following subassemblages distribution: 5.3% (n = 2) AII, 26.3% (n = 10) AIII, 7.9% (n = 3) BIII, and 60.5% (n = 23) new B genotypes not previously described.Giardia intestinalis infection presents a high prevalence rate among Amerindian descended children living in Santa Isabel do Rio Negro/Amazon. The wide distribution observed in a small city suggests the presence of multiple sources of infection, which could be related to environmental contamination with feces, possibly of human and animal origin, highlighting the need of improving sanitation, safe water supply and access to diagnosis and adequate treatment of infections

Can acute clinical outcomes predict health-related quality of life after stroke: a one-year prospective study of stroke survivors

Abstract Background Health-related quality of life (HRQoL) is a key metric to understand the impact of stroke from patients’ perspective. Yet HRQoL is not readily measured in clinical practice. This study aims to investigate the extent to which clinical outcomes during admission predict HRQoL at 3 months and 1 year post-stroke. Methods Stroke patients admitted to five tertiary hospitals in Singapore were assessed with Shah-modified Barthel Index (Shah-mBI), National Institute of Health Stroke Scale (NIHSS), Modified Rankin Scale (mRS), Mini-Mental State Examination (MMSE), and Frontal Assessment Battery (FAB) before discharge, and the EQ-5D questionnaire at 3 months and 12 months post-stroke. Association of clinical measures with the EQ index at both time points was examined using multiple linear regression models. Forward stepwise selection was applied and consistently significant clinical measures were analyzed for their association with individual dimensions of EQ-5D in multiple logistic regressions. Results All five clinical measures at baseline were significant predictors of the EQ index at 3 months and 12 months, except that MMSE was not significantly associated with the EQ index at 12 months. NIHSS (3-month standardized β = − 0.111; 12-month standardized β = − 0.109) and mRS (3-month standardized β = − 0.122; 12-month standardized β = − 0.080) were shown to have a larger effect size than other measures. The contribution of NIHSS and mRS as significant predictors of HRQoL was mostly explained by their association with the mobility, self-care, and usual activities dimensions of EQ-5D. Conclusions HRQoL at 3 months and 12 months post-stroke can be predicted by clinical outcomes in the acute phase. NIHSS and mRS are better predictors than BI, MMSE, and FAB