Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros











Base de dados
Intervalo de ano de publicação
1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22279787

RESUMO

BackgroundEvaluating the performance of SARS-CoV-2 serological assays and clearly articulating the utility of selected antigen, isotypes and thresholds is crucial to understanding the prevalence of infection within selected communities. MethodsThis cross-sectional study, implemented in 2020, screened PCR-confirmed COVID-19 patients (n=86), banked pre-pandemic and negative donors (n=96), health care workers and family members (n=552), and university employees (n=327) for anti-SARS-CoV-2 receptor-binding domain (RBD), trimeric spike protein (S), and nucleocapsid protein (N) IgG and IgA antibodies with a laboratory developed Enzyme-Linked Immunosorbent Assay (ELISA) and tested how antigen, isotype and threshold choices affected the seroprevalence. The following threshold methods were evaluated: (i) mean + 3 standard deviations of the negative controls; (ii) 100% specificity for each antigen/isotype combination; and (iii) the maximal Youden index. ResultsWe found vastly different seroprevalence estimates depending on selected antigens, isotypes and the applied threshold method, ranging from 0.0% to 85.4%. Subsequently, we maximized specificity and reported a seroprevalence, based on more than one antigen, ranging from 9.3% to 25.9%. ConclusionsThis study revealed the importance of evaluating serosurvey tools for antigen, isotype, and threshold-specific sensitivity and specificity, in order to interpret qualitative serosurvey outcomes reliably and consistently across studies.

2.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22271627

RESUMO

The clinical course of infection due to respiratory viruses such as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2), the causative agent of Coronavirus Disease 2019 (COVID-19) is thought to be influenced by the community of organisms that colonizes the upper respiratory tract, the oropharyngeal microbiome. In this study, we examined the oropharyngeal microbiome of suspected COVID-19 patients presenting to the Emergency Department and an inpatient COVID-19 unit with symptoms of acute COVID-19. Of 115 enrolled patients, 74 were confirmed COVID-19+ and 50 had symptom duration of 14 days or less; 38 acute COVID-19+ patients (76%) went on to require respiratory support. Although no microbiome features were found to be significantly different between COVID-19+ and COVID-19-patients, when we conducted random forest classification modeling (RFC) to predict the need of respiratory support for the COVID-19+ patients our analysis identified a subset of organisms and metabolic pathways whose relative abundance, when combined with clinical factors (such as age and Body Mass Index), was highly predictive of the need for respiratory support (F1 score 0.857). Microbiome Multivariable Association with Linear Models (MaAsLin2) analysis was then applied to the features identified as predicative of the need for respiratory support by the RFC. This analysis revealed reduced abundance of Prevotella salivae and metabolic pathways associated with lipopolysaccharide and mycolic acid biosynthesis to be the strongest predictors of patients requiring respiratory support. These findings suggest that composition of the oropharyngeal microbiome in COVID-19 may play a role in determining who will suffer from severe disease manifestations. ImportanceThe microbial community that colonizes the upper airway, the oropharyngeal microbiome, has the potential to affect how patients respond to respiratory viruses such as SARS-CoV2, the causative agent of COVID-19. In this study, we investigated the oropharyngeal microbiome of COVID-19 patients using high throughput DNA sequencing performed on oral swabs. We combined patient characteristics available at intake such as medical comorbidities and age, with measured abundance of bacterial species and metabolic pathways and then trained a machine learning model to determine what features are predicative of patients needing respiratory support in the form of supplemental oxygen or mechanical ventilation. We found that decreased abundance of some bacterial species and increased abundance of pathways associated bacterial products biosynthesis was highly predictive of needing respiratory support. This suggests that the oropharyngeal microbiome affects disease course in COVID-19 and could be targeted for diagnostic purposes to determine who may need oxygen, or therapeutic purposes such as probiotics to prevent severe COVID-19 disease manifestations.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA