Risk Prediction of Death in Inpatient Adults With COVID-19 from Mexico

BACKGROUND: There is substantial variation in COVID-19 lethality across countries. In addition, in countries with populations with extreme economic inequalities, such as Mexico, there are regional and local differences in risk factors for COVID-19 death. The goal of this study was to test the hypothesis that the risk of death in Mexican COVID-19 patients was associated with the time between symptom onset and hospitalization and/or with the healthcare site. Also, death prognostic models were developed. METHODS: The study included two COVID-19 inpatient cohorts, one prospective and one retrospective from Chiapas, Mexico. Demographic, clinical and laboratory variables were collected, and the diagnosis of SARS-CoV-2 infection was performed using RT-qPCR in samples collected seven days since symptom onset. The 30-day mortality, since symptom onset, was the outcome, and clinical variables at the first 48 hours of hospitalization were independent factors. Multivariate logistic regression analyses were conducted. RESULTS: Of the 392 patients included, 233 died (59.4%). The time between symptom onset and hospitalization, the healthcare site and sex were not related to the 30-day mortality. Three death prognostic models were developed (AUC between 0.726 and 0.807). Age, LDH, AST, and lymphocyte count were included in all models, OSI-WHO Classification (Non-invasive ventilation or high-flow oxygen, and mechanical ventilation with or without organ support/ECMO) and leukocyte count in two models, and diabetes and diarrhea in one model. CONCLUSION: The population evaluated had underlying deteriorated health before COVID-19 compared with regional and country population. The factors that determine the COVID-19 mortality risk in a relatively healthy population are sex, age and comorbidities. However, as this study shows, when populations have underlying poor health, some of these factors lose their associations with mortality risk, and others become more important.