Prognostic factors of COVID-19 severity and mortality in the Yucatecan ethnic of México contrast with other populations

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Abstract

Introduction: Previous studies that identified the prognostic factors for the severity of the new coronavirus disease 2019 (COVID-19) in different populations have generated controversial conclusions. The lack of a standard definition of COVID-19 severity and the differences between clinical diagnoses might make it difficult to provide optimum care according to the characteristics of each population. Methodology: We investigated the factors that impacted the severe outcome or death from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in patients treated at the Mexican Institute of Social Security in Yucatán, México in 2020. A cross-sectional study of COVID-19 confirmed cases was done to know the prevalence and association of the demographic and clinical characteristics with a severe or fatal outcome. Information from the National Epidemiological Surveillance System (SINAVE) database was used and SPSS v 21 was used for statistical analyses. We used the World Health Organization (WHO) and the Centers for Diseases Control and Prevention (CDC) symptomatology classifications to define severe cases. Results: Diabetes and pneumonia increased the risk of death and having diabetes was a prognostic factor for severe illness following SARS-CoV-2 infection. Conclusions: Our results highlight the influence of cultural and ethnic factors, the necessity to standardize the parameters for clinical diagnoses, and to use the same criteria for the definition of COVID-19 severity to establish the clinical conditions that contribute to the pathophysiology of this disease in each population.

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APA

Sánchez-Burgos, G. G., Aguilar-Erosa, J. A., & Alcocer-Ayuso, N. R. (2023). Prognostic factors of COVID-19 severity and mortality in the Yucatecan ethnic of México contrast with other populations. Journal of Infection in Developing Countries, 17(4), 425–431. https://doi.org/10.3855/jidc.17428

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