Clinical and laboratory predictors of poor outcome in COVID-19 patients

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Abstract

BACKGROUND: Many researchers have reported numerous predictors of severe COVID-19 and poor prognosis. However, to make a quick decision, the doctor needs to have a certain set of data that he can use in routine practice to predict the outcome in patients with this disease.

AIMS: This study aimed to develop and describe a predictive model for determining an unfavorable outcome in COVID-19 patients based on age, objective, laboratory and instrumental data, and comorbid pathology.

MATERIALS AND METHODS: The study included 447 patients with a laboratory-confirmed diagnosis of COVID-19 who underwent inpatient treatment in the period from March 2020 to January 2021. Discriminant analysis was used with cross-validation to build a predictive model.

RESULTS: Based on discriminant analysis, a predictive model was developed to predict the outcome in patients with COVID-19. Evaluation of clinical findings, such as respiratory rate, heart rate, SpO2, laboratory data, and computed tomography results on admission to the hospital, showed their significance as predictors of poor outcome. The discrimination constant was 0.4435. The sensitivity of the model is 96.4%, and the specificity is 90.4%.

CONCLUSION: The developed model will help medical institutions predict the outcome of the disease when a patient is admitted to the hospital and, on this basis, optimize and prioritize the provision of necessary medical care.

About the authors

Irina A. Lizinfeld

Central Research Institute of Epidemiology

Email: irinalizinfeld@gmail.com
ORCID iD: 0000-0002-8114-1002
SPIN-code: 2046-1407

MD

Russian Federation, 3A, Novogireyevskaya street, Moscow, 111123

Natalia Yu. Pshenichnaya

Central Research Institute of Epidemiology

Email: natalia-pshenichnaya@yandex.ru
ORCID iD: 0000-0003-2570-711X
SPIN-code: 5633-7265

MD, Dr. Sci. (Med.), Professor

Russian Federation, 3A, Novogireyevskaya street, Moscow, 111123

Olga V. Bunyaeva

Domodedovo Central City Hospital

Email: olya-bunyaeva@mail.ru
ORCID iD: 0000-0002-4889-5566

MD

Russian Federation, Domodedovo

Irina M. Shilkina

Domodedovo Central City Hospital

Email: shim-48@mail.ru
ORCID iD: 0000-0002-9900-038X

MD

Russian Federation, Domodedovo

Olga A. Shmailenko

City Hospital № 1 N.A. Semashko, City Hospital No. 1 named after N.A. Semashko of Rostov-on-Don

Email: Shmailenko@mail.ru
ORCID iD: 0000-0002-4680-590X

MD

Russian Federation, Rostov-on-Don

Galina V. Gopatsa

Central Research Institute of Epidemiology

Email: GopatsaG@mail.ru
ORCID iD: 0000-0001-8703-7671

MD, Cand. Sci. (Med.)

Russian Federation, 3A, Novogireyevskaya street, Moscow, 111123

Dmitrii V. Siziakin

City Hospital № 1 N.A. Semashko, City Hospital No. 1 named after N.A. Semashko of Rostov-on-Don; Rostov State Medical University

Email: Siziakin@gmail.com
ORCID iD: 0000-0001-7125-1374
SPIN-code: 8681-3345

MD, Dr. Sci. (Med.), Professor

Russian Federation, Rostov-on-Don; Rostov-on-Don

Evgeniia V. Chigaeva

City Hospital № 1 N.A. Semashko, City Hospital No. 1 named after N.A. Semashko of Rostov-on-Don; Rostov State Medical University

Author for correspondence.
Email: ChigaevaEV@gmail.com

MD, Cand. Sci. (Med.)

Russian Federation, Rostov-on-Don; Rostov-on-Don

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2. Fig. Age analysis in COVID-19 patients вased on outcome.

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Copyright (c) 2022 Lizinfeld I.A., Pshenichnaya N.Y., Bunyaeva O.V., Shilkina I.M., Shmailenko O.A., Gopatsa G.V., Siziakin D.V., Chigaeva E.V.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
 


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