Outpatient diagnosis of endogenous intoxication in surgery

Author:

Solomakha A. A.1,Vlasov A. P.2ORCID,Gorbachenko V. I.1ORCID

Affiliation:

1. Penza State University

2. National Research Mordovian State University named after N.P. Ogarev

Abstract

Introduction. In recent years, there has been an increase in the number of patients with purulent surgical diseases with severe endogenous intoxication and renal dysfunction. The problem of early diagnosis of purulent diseases is still not completely solved. The health systems of developed industrial Western countries do not always manage to provide all citizens with adequate high-quality medical care. This is due to the current health crisis. The problems of diagnosis, treatment, prevention and prediction of purulent diseases in surgery can be solved thanks to advanced digital technologies.Aim of the study. To develop a diagnostic method for early detection of endogenous intoxication in outpatient surgery.Materials and methods. We created three groups of observations for the design of a neural network system for the diagnosis of endogenous intoxication syndrome and chronic kidney disease. In the first group, the hematological parameters of 150 healthy people were studied. In the second group, the hematological parameters of 40 patients with chronic kidney disease without chronic kidney failure were studied. The third group included 84 patients with chronic kidney disease and end-stage chronic kidney failure. The following 25 laboratory parameters were studied: hemoglobin, red blood cells, color index, white blood cells, rod-shaped neutrophil white blood cells, segmental neutrophil white blood cells, eosinophils, basophils, lymphocytes, monocytes, ESR, total protein, albumins, urea, creatinine, bilirubin, beta-lipoproteins, cholesterol, glucose, seromucoid, sialic acid, potassium, sodium, chlorine, calcium. Statistical, neural network and algorithms with elements of fuzzy neural networks were used on a sample consisting of hematological parameters of 274 patients with chronic kidney disease and healthy ones based on 25 laboratory parameters. Mathematical modeling was carried out at the Department of “Computer Technologies” of the Penza State University.Results. The effectiveness of neural network diagnostics of endogenous intoxication syndrome in patients with chronic kidney disease without chronic kidney failure reached 88.2%, and in patients with chronic kidney disease and chronic kidney failure – 97.6%.Conclusion. The neural network method of diagnosis can help improve the early diagnosis of endogenous intoxication syndrome in outpatient surgery. 

Publisher

Remedium, Ltd.

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