Abstract
This is a cross-sectional study, with secondary data from Brazilian hospitals in the state of Paraíba, between January 2021 and January 2022. The evolution of clinical cases configured the dependent variable (cure or death), while the predictive variables were sociodemographic data, risk factors, use of ventilatory support, and vaccination against COVID-19. With the help of R software, the following tests were used: chi-square, Pearson's chi-square, and Fisher's exact adherence. Simple logistic regression models were constructed, and odds ratios (95% CI) were estimated using the LR test and Wald test. 7373 cases were reported, with a mean age of 58.1. Of the reported cases, 63.8% died. The most frequent sociodemographic profile included male people, of mixed race, with less than eight years of schooling. Chronic cardiovascular disease (OR 1.28; 95% CI: 1.13-1.45), diabetes (OR 1.41; 95% CI: 1.24-1.61), lung disease (OR 1.52; 95% CI: 1.11-2.09), and the use of invasive ventilatory support (OR 14.1; 95% CI: 10.56-18.59) were all associated with increased mortality. Nonvaccination was associated with a decreased risk of death (OR 0.74; 95% CI: 0.65-0.84). Male patients, nonwhite, and those with low education were more likely to have a worse clinical outcome. The risk factors studied were related to deaths, and those who did not require ventilatory support were related to cure.