Prediction of chronic kidney disease in patients with hemorrhagic fever with renal syndrome
- Authors: Stulova M.V.1, Konstantinov D.Y.1, Popova L.L.1, Lyubushkina A.V.1, Nedugov G.V.1
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Affiliations:
- Samara State Medical University
- Issue: Vol 7, No 1 (2022)
- Pages: 35-38
- Section: Infectious diseases
- URL: https://ogarev-online.ru/2500-1388/article/view/96354
- DOI: https://doi.org/10.35693/2500-1388-2022-7-1-35-38
- ID: 96354
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Abstract
Aim – to develop, using mathematical and statistical analysis of clinical, laboratory and instrumental data, a method for predicting the development of chronic kidney disease (CKD) in patients with hemorrhagic fever with renal syndrome (HFRS).
Material and methods. 244 patients at the age from 18 to 50 years with a confirmed diagnosis of HFRS were examined. Patients were observed in the following periods: oliguric, polyuric, early (30th day of illness) and late (90th and 180th day of illness) convalescence. Clinical, laboratory and instrumental data, including computer photoplethysmography, were evaluated.
Results. Prediction of CKD in patients with HFRS (polyuria period) based on a linear discriminant model is possible with an accuracy index of 92.2%. In subsequent periods, the accuracy index increases: in early convalescence – 98.4%, in late convalescence up to 100%. The following markers were the most informative: RI before ischemia, leukocytes and platelets in the general blood test, total protein and creatinine in the biochemical blood test, GFR calculated using the CKD-EPI and MDRD formulas, daily microalbuminuria, BMI and weight.
Conclusion. A complex of discriminant models for predicting the development of CKD in patients with HFRS at various stages of the disease, including convalescence, with an accuracy index from 92 to 100% has been developed. These models are implemented in the software "Calculator for predicting CKD after HFRS".
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##article.viewOnOriginalSite##About the authors
Mariуa V. Stulova
Samara State Medical University
Author for correspondence.
Email: mariastulova@gmail.com
ORCID iD: 0000-0002-6169-1701
assistant of the Department of Infectious diseases with epidemiology
Russian Federation, SamaraDmitrii Yu. Konstantinov
Samara State Medical University
Email: dk.samgmu@mail.ru
ORCID iD: 0000-0002-6177-8487
PhD, Associate professor, Head of the Department of Infectious diseases with epidemiology
Russian Federation, SamaraLarisa L. Popova
Samara State Medical University
Email: ll_popova@mail.ru
ORCID iD: 0000-0003-0549-361X
PhD, Professor of the Department of Infectious diseases with epidemiology
Russian Federation, SamaraAnna V. Lyubushkina
Samara State Medical University
Email: a.lyubushkina@mail.ru
ORCID iD: 0000-0002-0348-9118
PhD, assistant of the Department of Infectious diseases with epidemiology
Russian Federation, SamaraGerman V. Nedugov
Samara State Medical University
Email: nedugovh@mail.ru
ORCID iD: 0000-0002-7380-3766
PhD, Associate professor of the Department of Forensic medicine
Russian Federation, SamaraReferences
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