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

Authors

DOI:

https://doi.org/10.33448/rsd-v9i12.11028

Keywords:

COVID-19; Regression; Comorbidities; Diagnosis.

Abstract

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.

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18/12/2020

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FREITAS, J. R. de; PEREIRA, M. M. de A. .; SILVA, L. A. P. da .; PESSOA, R. V. S.; SANTANA, L. I. T. de .; SILVA, J. M. da; LIMA, C. R. O. de P.; ALBUQUERQUE, C. R. .; CUNHA FILHO, M. . Logistic modeling and risk factors associated with COVID-19 patients, Brazil. Research, Society and Development, [S. l.], v. 9, n. 12, p. e17391211028, 2020. DOI: 10.33448/rsd-v9i12.11028. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/11028. Acesso em: 5 nov. 2024.

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Vol. 9 No. 12

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Health Sciences

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Copyright (c) 2020 Jucarlos Rufino de Freitas; Mickaelle Maria de Almeida Pereira; Laura Alves Pacifico da Silva; Ruben Vivaldi Silva Pessoa; Leika Irabele Tenório de Santana; Joelma Mayara da Silva; Claudia Regina Oliveira de Paiva Lima; Cristiane Rocha Albuquerque; Moacyr Cunha Filho

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