Frontiers
Browse
Data_Sheet_1_Modeling mortality risk in patients with severe COVID-19 from Mexico.PDF (430.82 kB)

Data_Sheet_1_Modeling mortality risk in patients with severe COVID-19 from Mexico.PDF

Download (430.82 kB)
dataset
posted on 2023-05-26, 13:05 authored by Arturo Cortes-Telles, Esperanza Figueroa-Hurtado, Diana Lizbeth Ortiz-Farias, Gerald Stanley Zavorsky
Background

Severe acute respiratory syndrome caused by a coronavirus (SARS-CoV-2) is responsible for the COVID-19 disease pandemic that began in Wuhan, China, in December 2019. Since then, nearly seven million deaths have occurred worldwide due to COVID-19. Mexicans are especially vulnerable to the COVID-19 pandemic as Mexico has nearly the worst observed case-fatality ratio (4.5%). As Mexican Latinos represent a vulnerable population, this study aimed to determine significant predictors of mortality in Mexicans with COVID-19 who were admitted to a large acute care hospital.

Methods

In this observational, cross-sectional study, 247 adult patients were consecutively admitted to a third-level referral center in Yucatan, Mexico, from March 1st, 2020, to August 31st, 2020, with COVID-19-related symptoms, participated in this study. Lasso logistic and binary logistic regression were used to identify clinical predictors of death.

Results

After a hospital stay of about eight days, 146 (60%) patients were discharged; however, 40% died by the twelfth day (on average) after hospital admission. Out of 22 possible predictors, five crucial predictors of death were found, ranked by the most to least important: (1) needing to be placed on a mechanical ventilator, (2) reduced platelet concentration at admission, (3) increased derived neutrophil to lymphocyte ratio, (4) increased age, and (5) reduced pulse oximetry saturation at admission. The model revealed that these five variables shared ~83% variance in outcome.

Conclusion

Of the 247 Mexican Latinos patients admitted with COVID-19, 40% died 12  days after admission. The patients’ need for mechanical ventilation (due to severe illness) was the most important predictor of mortality, as it increased the odds of death by nearly 200-fold.

History