Prediction of long-term treatment in patients with COVID-19 based on analysis of their primary examination data

Abstract

The COVID-19 pandemic has caused enormous social and economic damage. A significant part of people who have contracted this infection have serious health problems. To prevent the long-term consequences of COVID-19, models for predicting the duration of treatment based on prognostic factors obtained at the beginning of the disease are needed. In 2020-2021, a survey of 832 patient with COVID-19 was conducted. With the help of computer programs Microsoft Excel 2021 and Statistica 12.0 Trial Version for Windows, the collected database was processed. The model was built using the tool Data Mining – Trees/Partitioning -Classification and Regression Tree. Established interrelationship between clinical symptoms in with COVID-19 will allow timely detection of possible complications in patients. Implementation of a built decision-making model based on leading predictors will help doctors predict the duration of the infection and develop effective measures to prevent serious post-infection consequences.