CCL3, CCL5, IL-15, IL-1Ra and VEGF compose a reliable algorithm to discriminate classes of adverse events following 17DD-YF primary vaccination according to cause-specific definitions

Autor: Marília Lima Cruz Rocha, Eva Lídia Arcoverde Medeiros, Izabela Maurício de Rezende, Valeria Valim, Maira Alves Pereira, Matheus de Souza Gomes, Ana Carolina Campi-Azevedo, Daniel Garkauskas Ramos, Josiane Dias Gusmão, Maria Auxiliadora-Martins, Talita Émile Ribeiro Adelino, Regina Coeli Magalhães Rodrigues, Marcos Vieira Silva, Andréa Teixeira-Carvalho, Francieli Fontana Sutile Tardetti Fantinato, Alessandro Pecego Martins Romano, Laurence Rodrigues do Amaral, Rodrigo Fabiano do Carmo Said, Glauco de Carvalho Pereira, Sandra Carvalho, Eder Gatti Fernandes, Jordana Rodrigues Barbosa Fradico, Jordana Grazziela Alves Coelho-dos-Reis, Elaine Spezialli Faria, Betânia Paiva Drumond, Vanessa Peruhype-Magalhães, Janaina Fonseca Almeida, Felipe Campos de Melo Iani, José Geraldo Leite Ribeiro, Roberta Barros da Silva, Olindo Assis Martins-Filho

Publikováno v: Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP

In the present study, a range of serum biomarkers were quantified in suspected cases of adverse events following YF immunization (YEL-AEFI) to propose a reliable laboratorial algorithm to discriminate confirmed YEL-AEFI (“A1” class) from cases wi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9315b7a1435ed6f6a41a3b27ad2f72d7
https://doi.org/10.1016/j.vaccine.2021.05.101