Analysis of risk factors and comorbidities associated with mortality of hospitalized patients with Covid-19 in the high sertão of Paraiba

Authors

DOI:

https://doi.org/10.33448/rsd-v11i6.29380

Keywords:

Covid-19; Comorbidity; Mortality; Hospitalization; Teaching.

Abstract

The current Covid-19 pandemic is an international public health problem, given the consequences generated by its existence. In view of this scenario, the study aimed to identify and evaluate the impact of risk factors and comorbidities associated with the mortality of patients hospitalized with Covid-19 in Alto Sertão Paraibano. It is an exploratory, descriptive and analytical study. The research used data extracted from the SIVEP database through OpenDataSUS, from March 2020 to August 2021. In the data analysis, descriptive statistical techniques were used. Regarding the results in the years 2020 and 2021, respectively, we had the variables female (52.9%) and (42.8%), male (47.1%) and (57.2%), place of residence Urban Zone (78.4%) and (77.1%), Rural Zone (21.6%), and 22.9%) and as for symptoms, cough, dyspnea, hyposaturation and respiratory distress had the highest percentages in both the years under study and regarding the presence or absence of risk factors, it was found that most of them had some risk factor or comorbidities. Therefore, the analysis provides an overview of the Pandemic and the determining factors in this process in the municipalities of Alto Sertão Paraibano and the eligible variables showed that symptoms and comorbidities were significant predictors for hospitalization and disease evolution, and the outcome for death and/or cure.

References

Almeida, J. S. Cardoso, J. A. Cordeiro, E. C. Lemos, M.Araújo, T. M. E. & Sardinha, H. L. (2020). Caracterização Epidemiológica Dos Casos De Covid-19 No Maranhão: Uma Breve Análise. https://preprints.scielo.org/index.php/scielo/preprint/view/314/377.

Andrade, M. M. (2005). Introdução à metodologia do trabalho científico. (7a ed.), Atlas.

Brasil. (2020). Ministério Da Saúde (Ms). Biblioteca Virtual Em Saúde. Vigilância Em Saúde. http://bvsms.saude.gov.br/bvs/svs/inf_sist_informacao.php.

Brasil. (2020). Ministério da Saúde. Secretaria de Vigilância em Saúde. Guia de Vigilância Epidemiológica. Emergência de Saúde Pública de Importância Nacional pela Doença pelo Coronavírus. Vigilância Integrada de Síndromes Respiratórias Agudas. Doença pelo coronavírus 2019, influenza e outros vírus respiratórios. Brasil: Ministério da Saúde.

Brasil, (2020). Ministério da Saúde- Painel Coronavírus. In www.covid.saude.gov.br Organização Pan-Americana de Saúde/ Organização Mundial de Saúde. Folha Informativa COVID-19 (doença causada pelo novo coronavírus) – OPAS/OMS – https://www.paho.org .

Brasil, (2020). Ministério da Saúde. Protocolo de Manejo Clínico para o novo coronavírus). Ministério da saúde.

Brasil, (2021). Ministério da Saúde (BR). Secretaria de Vigilância em Saúde. Centro de Operações de Emergências em Saúde.

Cai, Q. et al. (2020) Obesity and Covid-19 severity in a designated hospital in Shenzhen, China. Diabetes Care. 2020;43(7):1392-98. http://dx.doi. org/10.2337/dc200576.

Castilho, D. (2020). Um vírus com DNA da globalização: o espectro da perversidade. Espaço e Economia: Revista brasileira de geografia econômica, n. 17.

Chen, Y. Liu, Q. & Guo, D. (2020). Emerging coronaviruses: genome structure, replication, and pathogenesis. J Med Virol. Apr; 92(4):418-423. https://www.ncbi.nlm.nih.gov/pubmed/31967327.

Costa, L. M. F.& Barreto, S. M., (2003). Tipos de estudos epidemiológicos: conceitos básicos e aplicações na área do envelhecimento. Epidemiologia e Serviços de Saúde, 12(4), 189-201,

Dolin, R. (2020). Common viral respiratory infections and severe acute respiratory syndrome (SARS). In: Fauci, A.S. et al. Harrison's Principles of Internal Medicine. (17a ed.), MacGraw-Hill.

Guan, W. et al. (2020). Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med https://doi. Org/10.1056/nejmoa2002032.

Jiang, W., Josse, J. & Lavielle, M. (2020). Logistic regression with missing covariates Parameter estimation, model selection and prediction within a joint-modeling framework. Computational Statistics & Data Analysis. 145, 106907.

knight, M. et al. (2020). Characteristics and outcomes of pregnant women admitted to hospital with confirmed SARS-cov-2 infection in UK: National population based cohort study. BMJ, [s. L.], v. 369, p. 2017.

Lai, C. C., Liu, Y. H., Wang, C. Y., Wang, Y-H, Hsueh, S-C, Yen, M-Y. et al. (2020). Asymptomatic carrier state, acute respiratory disease, and pneumonia due to severe acute respiratory syndrome coronavirus 2 (SARS-cov-2): Facts and myths. J Microbiol Immunol Infect. 53(3): 404-12. Http:// doi.org/10.1016/j.jmii.

Li, R. et al. (2020). Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-cov2). Sience, 368(6490), 489-493, https://doi. Org/10.1126/science.abb3221.

Li L. Q, et al. (2020). Covid-19 patients’ clinical characteristics, discharge rate, and fatality rate of meta-analysis. J Med Virol 92(6): 577-83. Http://doi.org/10.1002/jmv.25757» https://doi.org/http://doi.org/10.1002/jmv.25757.

Li, B. et al. (2020). Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin Res Cardiol.;109. P. 531–538.

Liu. K. Chen, Y. Lin, R & Han K. (2020). Clinical features of COVID-19 in elderly patients: A comparison with young and middle-aged patients. J Infect.;80(6):E14-8. Http://dx.doi.org/10.1016/j.jinf.2020.03.005. Pmid:32171866.

Matos. M. (2020). Pandemia Covid-19 e as mulheres. Bol Cientistas Sociais. http://www.anpocs.com/index.php/ciencias-sociais/destaques/2322-boletim-n-11- pandemia-Covid-19-e-as-mulheres.

Nandy, K. et al. (2020). Coronavirus disease (Covid-19): a systematic review and meta-analysis to evaluate the impact of various comorbidities on serious events. Diabetes Metab Syndr.;14(5):1017-1025. http://dx.doi. Org/10.1016/j.dsx.2020.06.064.

Nunes, B. et al. (2020). Envelhecimento, multimorbidade e risco para Covid-19 grave: ELSI-Brasil. Scielo Preprints.]. https://preprints. Scielo.org/index.php/scielo/preprint/view/703.

Ruan, Q. Yang, K. Wang, W. Jiang, L & Song J. (2020). Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med 46(5):846-8. Http://dx.doi. Org/10.1007/s00134-020-05991-x. Pmid:32125452.

Wu, Z & Mcgoogan, J.M. (2020). Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the chinese center for disease control and prevention. JAMA. 7;323(13):1239-42. Doi: http://dx.doi.org/10.1001/jama.2020.2648.

Yang, J. et al. (2020). Prevalence of comorbidities in the novel Wuhan coronavirus (COVID-19) infection: a systematic review and meta-analysis. Int J Infect Dis [1];94:91-5. https://doi.org/10.1016/j.ijid.2020.03.017.

Zhang, J-J et al. (2020). Clinical characteristics of 140 patients infected with SARS-cov-2 in Wuhan, China. Allergy. https://doi.org/10.1111/all.14238.

Published

03/05/2022

How to Cite

NASCIMENTO, S. G. da S. .; LEITE, J. C. de L. Analysis of risk factors and comorbidities associated with mortality of hospitalized patients with Covid-19 in the high sertão of Paraiba. Research, Society and Development, [S. l.], v. 11, n. 6, p. e45011629380, 2022. DOI: 10.33448/rsd-v11i6.29380. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/29380. Acesso em: 14 nov. 2024.

Issue

Section

Health Sciences