Desenvolvimento de plataforma biofotônica de larga escala para aplicação na triagem diagnóstica da COVID-19 por meio da saliva

• Ano de defesa: 2022
• Autor(a) principal: Cardoso de Sousa, Léia
• Tipo de documento: Tese
• Tipo de acesso: Acesso embargado
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Ciências da Saúde
• Palavras-chave em Português: Covid-19; SARS-CoV-2; ATR-FTIR; diagnóstico salivar; CNPQ::CIENCIAS DA SAUDE; Ciências médicas; Vírus - Isolamento; Fisiopatologia
• Link de acesso: https://repositorio.ufu.br/handle/123456789/34181; http://doi.org/10.14393/ufu.te.2022.114

SARS-CoV-2, identified in 2020, was responsible to promote a pandemic scenario. The virus belongs to the Coronaviridae family and is responsible for causing, in severe cases, Severe Acute Respiratory Syndrome. The diagnosis of Covid-19 disease is performed by sampling nasopharyngeal swabs or invasive blood from RT-PCR or immunological tests, which are of personalized use and require technical work for execution. Considering the context, ATR-FTIR spectroscopy and machine learning classification on saliva platform coupled with large-scale sample may provide an alternative screening tool for Covid-19. The work aimed to select the best material to be used to make the sample platform well presented as a Covid-19 (n: 100) and not Covid-19 (n: 100) using an ATRFTIR technique coupled to a device performance and machine learning tool. PCA-LDA analysis of salivary spectra showed a sensitivity of 78%, specificity of 76% and accuracy of 77% between non-Covid-19 and Covid-19 patients. Briefly, the data obtained allowed a selection of a suitable material for the making of a sample platform and how of the possible ATR-FTIR platforms coupled to a highperformance device as a sustainable, reagent-free and non-invasive tool for Covid-19 patients.