COVID-19 clinical footprint to infer about mortality.

ABSTRACT: Information on 4.1 million patients identified as COVID-19 positive in Mexico is used to understand the relationship between comorbidities, symptoms, hospitalisations and deaths due to the COVID-19 disease. Using the presence or absence of these variables a clinical footprint for each patient is created. The risk, expected mortality and the prediction of death outcomes, among other relevant quantities, are obtained and analysed by means of a multivariate Bernoulli distribution. The proposal considers all possible footprint combinations resulting in a robust model suitable for Bayesian inference. The analysis is carried out considering the information on the monthly COVID-19 cases, from March 2020 to the first days of January 2022. This allows one to appreciate the evolution of the mortalit

SUBMITTER: Rodriguez CE 

PROVIDER: S-EPMC9877559 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature