Logistic modeling and risk factors associated with COVID-19 patients, Brazil

• Autor(a) principal: Freitas, Jucarlos Rufino de
• Data de Publicação: 2020
• Outros Autores: Pereira, Mickaelle Maria de Almeida, Silva, Laura Alves Pacifico da, Pessoa, Ruben Vivaldi Silva, Santana, Leika Irabele Tenório de, Silva, Joelma Mayara da, Lima, Claudia Regina Oliveira de Paiva, Albuquerque, Cristiane Rocha, Cunha Filho, Moacyr
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/11028
• topic: COVID-19; Regressão; Comorbidades; Diagnóstico.; COVID-19; Regresión; Comorbilidades; Diagnóstico.; COVID-19; Regression; Comorbidities; Diagnosis.

Objective: Through a logistic regression model, the clinical profile of the affected individuals was drawn. Methods: We used data from the number of confirmed cases of COVID-19, available through SEPLAG-PE, in partnership with SES and ATI, from March 12, 2020 to July 13, 2020. Results: The group with the highest frequency of deaths belongs to the age group above 50 years, becoming statistically significant in relation to the evolution of the disease. Among the patients who died, the majority presented diabetes, hypertension and other comorbidities, being statistically significant in relation to the evolution of the clinical picture of OVID-19. Conclusion: The results provide significant assessments for the understanding of possible risk factors related to deaths by OVID-19, becoming a useful tool in decision-making for health professionals.