Application of a Cuban mortality-predictive model in seriously-ill patients with Covid-19 in Lombardy, Italy

Authors

Keywords:

mortality, COVID-19, predictive model

Abstract

Introduction: COVID-19 pneumonia is an infectious disease that has revolutionized the world in the last months. The diagnosis goes thought several moments: clinical features, blood analytic and images. Death risk stratification is very important to optimize resources.

Objective: to validate the Cuban mathematic predictive model of mortality in patients admitted due to COVID-19.

Materials and methods: cohort study with 191 seriously-ill patients who were admitted to Maggiore di Crema Hospital, Cremona, Lombardy region, Italy, in the period April-May 2020. The universe were 191 patients and no sample was chosen. The variables were: age; patient’s status; plasma creatinine levels; respiratory rate; heart rate; arterial pressure; blood oxygen and carbon dioxide levels; values of sodium and hemoglobin.

Results: 22 % of mortality in seriously-ill and critical patients, with average age in Group 1: 59 years, in Group 2: 73 years; t-Student = 0.00. Hosmer-Lemenshow test (0.766) with high adjustment. Sensitivity= 93 %. Area below the curve=0.957. Success percentage in logistic regression of 86.4 % and 91.2 % in the neuronal net. Model media per groups: Group 1= 4 458; Group 2= 2 911, t-Student = 0.00.

Conclusions: the model showed to be very useful in the flow chart of patients attended with COVID-19. It allowed to early detect the patients at high death risk five days from admission and discriminating those who were not at risk, in a way that they could be treated in minimal care units.

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References

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Published

2021-03-10

How to Cite

1.
García Álvarez PJ, Morejón Ramos L, Grasso Leyva F. Application of a Cuban mortality-predictive model in seriously-ill patients with Covid-19 in Lombardy, Italy. Rev Méd Electrón [Internet]. 2021 Mar. 10 [cited 2025 Jan. 23];43(2):325-38. Available from: https://revmedicaelectronica.sld.cu/index.php/rme/article/view/3958

Issue

Vol. 43 No. 2 (2021)

Section

Research article

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