Prediction of chronic kidney disease in patients with hemorrhagic fever with renal syndrome

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".

Keywords

• hemorrhagic fever with renal syndrome
• early and late convalescence
• prognosis of chronic kidney disease
• computer photoplethysmography
• discriminant analysis