Predicting the duration of inpatient treatment for COVID-19 patients
https://doi.org/10.21518/2079-701X-2020-17-82-90
Abstract
Introduction. In the context of a high load on all links in the structure of providing medical care to patients with COVID-19, solving the issue of effective triage of patients seems to be extremely urgent. The duration of inpatient treatment is one of the most objective and unambiguously interpreted indicators that can be used to indirectly assess the severity of the patient’s condition.
Objective. Develop a machine learning model to predict the duration of inpatient care for patients with COVID-19 based on routine clinical indicators assessed at the prehospital stage.
Materials and methods. A total of 564 patients were examined with diagnoses: U07.1 COVID-19, virus identified (n = 367) and U07.2 COVID-19, virus not identified (n = 197). The study included 270 patients, of whom in 50.37% of patients the duration of inpatient treatment did not exceed 7 days, in 49.63% of patients the duration of inpatient treatment was more than 10 days. Eleven clinical parameters were chosen as the most important predictors for predicting the duration of inpatient treatment: age, height and weight of the patient, SpO2 level, body temperature, body mass index, pulse rate, number of days from the onset of illness, respiratory rate, systolic and diastolic arterial pressure.
Results. The accuracy of our machine learning model for predicting the duration of inpatient treatment more than 10 days was 83.75% (95% CI: 73.82–91.05%), sensitivity — 82.50%, specificity — 85.00%. AUC = 0.86.
Conclusion. The method developed by us based on machine learning is characterized by high accuracy in predicting the duration of inpatient treatment of patients with COVID-19, which makes it possible to consider it as a promising new tool to support medical decisions on further tactics of patient management and to resolve the issue of the need for hospitalization.
About the Authors
V. V. Tsvetkov
Smorodintsev Research Institute of Influenza
Russian Federation
Russian Federation
Valeriy V. Tsvetkov, Cand. of Sci (Med.), Senior Researcher
15/17, Professor Popov St., St Petersburg, 197376
I. I. Tokin
Smorodintsev Research Institute of Influenza;
North-Western State Medical University named after I.I. Mechnikov
Russian Federation
Russian Federation
Tokin, Cand. of Sci (Med.), Leading Researcher, Head of the Department of Clinical Experimental Research, Federal State Budgetary Institution “Smorodintsev Research Institute of Influenza” of the Ministry of Health of the Russian Federation; Associate Professor of the Department of Infectious Diseases, Federal State Budgetary Institution of Higher Education “North-Western State Medical University named after I.I. Mechnikov” of the Ministry of Health of the Russian Federation
15/17, Professor Popov St., St Petersburg, 197376,
191015, St Petersburg
D. A. Lioznov
Smorodintsev Research Institute of Influenza;
Pavlov First Saint Petersburg State Medical University
Russian Federation
Russian Federation
Dmitry A. Lioznov, Dr. of Sci. (Med.), Acting director, Federal State Budgetary Institution “Smorodintsev Research Institute of Influenza” of the Ministry of Health of the Russian Federation; Head of the Department of Infectious Diseases and Epidemiology, Federal State Budgetary Educational Institution of Higher Education “Pavlov First Saint Petersburg State Medical University” of the Ministry of Healthcare of Russian Federation
15/17, Professor Popov St., St Petersburg, 197376,
6–8, Lev Tolstoy St., St Petersburg, 197022
E. V. Venev
Smorodintsev Research Institute of Influenza;
Clinical Infectious Disease Hospital named after S.P. Botkin
Russian Federation
Russian Federation
Evgeny V. Venev, Postgraduate Student, Senior Lecturer, Federal State Budgetary Institution “Smorodintsev Research Institute of Influenza” of the Ministry of Health of the Russian Federation; infectious disease doctor, St Petersburg State Budgetary Institution “Clinical Infectious Disease Hospital named after S.P. Botkin”
15/17, Professor Popov St., St Petersburg, 197376,
49, Piskaryovsky Ave., St Petersburg, 195067
A. N. Kulikov
Pavlov First Saint Petersburg State Medical University
Russian Federation
Russian Federation
Alexandr N. Kulikov, Dr. of Sci. (Med.), Professor, Deputy Chief Physician of the Clinic for Therapy, Head of the Department of Clinical Physiology and Functional Diagnostics
6–8, Lev Tolstoy St., St Petersburg, 197022
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Review
For citations:
Tsvetkov VV, Tokin II, Lioznov DA, Venev EV, Kulikov AN. Predicting the duration of inpatient treatment for COVID-19 patients. Meditsinskiy sovet = Medical Council. 2020;(17):82-90. (In Russ.) https://doi.org/10.21518/2079-701X-2020-17-82-90
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