Introduction:

severe acute respiratory syndrome became a pandemic, and caused high morbidity and mortality worldwide, since there was no effective treatment or timely recognition of individuals with the worst prognosis.

Objective:

to assess the ability to predict the risk of dying in patients with COVID-19, using a model based on prognostic factors.

Methodos:

a cohort analytical study was carried out in patients with covid-19 treated in the services of the "COVID-19" hospital of the "Carlos Manuel de Céspedes" provincial general hospital of the Bayamo municipality, Granma province, since january 1, 2020 until december 31, 2022.

Results:

the binary logistic regression model adjusted by the introduce method showed that the outstanding factors were, in order of importance, suffering from cancer (OR= 8.21; 95 % CI= 1.58-11.35; p= 0.023) followed by protein C reactive (OR= 7.91; 95 % CI= 4.46-9.87; p= 0.000) and arterial hypertension (OR= 7.15; 95 % CI= 4.41-11.42; p= 0.000). The Hosmer and Lemeshow test with a value of p= 0.582 with an indicator of good calibration of the model. The area under the ROC curve was 0.894 (confidence interval: 0.846-0.942; p=0.000), demonstrating the validity of the model.

Conclusions:

the place of a history of cancer and high blood pressure as comorbidity related to the risk of dying from COVID-19is demonstrated, as well as inflammation reactants, where C-reactive protein, lactic dehydrogenase and erythrocyte sedimentation rate stand out. A model with adequate discriminative capacity is obtained.

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