Introduction:

risk prediction and predictive models are known for their usefulness in estimating disease planning and action. The present work has the objective of developing a system of algorithms for risk stratification in the care process of patients with COVID-19.Introducción.

Objective:

to develop a system of algorithms for risk stratification in the care process of patients with COVID-19.

Methods:

the algorithms were designed based on a predictive model developed in a cohort of 150 patients from the “Manuel Fajardo” Hospital with the diagnosis of COVID-19 in the period from March to June 2020. They were constructed with the results obtained in the different stages of the research and the expert criteria of the authors. It includes the application of the risk prediction nomogram created with the variables that are part of the definitive results of the model.

Results:

for the initial evaluation of patients, age, comorbidities, clinical manifestations and the Quick SOFA prognostic scale were taken into account, which define where the patient is admitted. Chest X-ray and the application of the predictive nomogram, which classifies patients as high or low risk, are included in the hospitalization wards. Guidelines are established for the management of high-risk patients and treatment recommendations are made once the alterations in the complementary tests have been determined.

Conclusions:

risk stratification algorithms constitute a tool for the treatment of patients with COVID-19 and offer therapeutic interventions that halt disease progression.

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