Abstract
Introduction. The identification of predictors of mortality in COVID-19 remains one of the primary directions among all studies devoted to this topic. The search and selection of the most sensitive prognostic tools is the basis for improving the prognosis in patients with COVID-19 and for the proper allocation of health resources. Aim. The aim is to develop a prognostic model for assessing the risk of an adverse outcome in the first two days in patients with COVID-19 hospitalized in an infectious diseases hospital. Material and Methods: the clinical and anamnestic data of 148 patients with an unfavorable (fatal) outcome in the first two days after hospitalization and 364 patients with a favorable outcome up to 10 bed days were analyzed. Statistical analysis was carried out using the StatTech v. 2.8.8 program (developed by Stattech OOO, Russia). Results and discussion. According to the results of our study, the following predictors were included in the prognostic model: age, male gender, degree of respiratory failure, type 2 diabetes mellitus, obesity, arterial hypertension and coronary heart disease. Under the influence of a set of predictors, the risk of an unfavorable outcome in patients with COVID-19 increased in male patients by 1.1 times, with an increase in age by 1 year by 1.1 times, in the presence of grade 2 respiratory failure by 5.9 times, grade 3 respiratory failure by 17.4 times, type 2 diabetes by 1.1 times, obesity by 1.4 times, arterial hypertension by 1.8 times, coronary heart disease by 3.7 times. Conclusion. The obtained prognostic model for assessing the risk of an adverse outcome in patients with COVID-19 has good prognostic abilities, its sensitivity and specificity were 76.5% and 77.8%, respectively. The resulting model can help optimize the prediction of outcome in hospitalized patients with COVID-19
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
