Nombre: WENA DANTAS MARCARINI
Fecha de publicación: 17/06/2024
Junta de examinadores:
Nombre |
Papel |
|---|---|
| ANTÔNIO FERREIRA DE MELO JUNIOR | Examinador Externo |
| LIVIA CARLA DE MELO RODRIGUES | Examinador Interno |
| LUIS FELIPE DAS CHAGAS E SILVA DE CARVALHO | Examinador Externo |
| RITA GOMES WANDERLEY PIRES | Examinador Interno |
Sumario: Introduction: In December 2019, the outbreak of the novel coronavirus was reported to the World Health Organization. SARS-CoV-2 is an enveloped virus with positive- sense single-stranded RNA. The Spike protein is the main surface glycoprotein of the coronavirus and belongs to class I viral fusion proteins; this protein is essential in the pathogenesis, transmission, and virulence of SARS-CoV-2. Currently, the gold standard for virus detection is RT-PCR; however, a faster, more cost-effective, and multilocal detection method is needed for virus identification, as it is a technical necessity for the prevention and control of SARS-CoV-2 infection. Thus, this study applied Fourier-transform infrared spectroscopy (FT-IR), an analytical technique with high sensitivity and resolution used to identify functional groups present in biological samples. Objective: To propose a screening methodology as a new tool to assist in the diagnosis of COVID-19. Methodology: A convenience sampling was used, and symptomatic patients signed the informed consent form to participate in the research. After the RT-PCR sample collection, the same patients expelled saliva into a sterile tube for subsequent analysis using the FT-IR equipment. Results: This study included 237 patients, with 138 (58%) testing positive by RT-PCR and 99 (42%) testing negative. The most prevalent age group was young adults. The most common symptoms were fever, cough, runny nose, sore throat, and headache. Regarding comorbidities, hypertension and diabetes had the highest incidence. For the spectroscopic analysis, the FT-IR spectra were evaluated using unsupervised random forest (URF) and machine learning models for classification. Conclusion In the area of spectroscopy, it was noted that chemometric models complemented the analyzes and provided high sensitivity and specificity, as well as remarkable precision for detecting the virus in patients with COVID-19 symptoms. Therefore, we hope that in the future, we will have more advances in the area of spectroscopy, to assist in the mass screening of patients and even assist in the diagnosis of other diseases.
