Mathematical prognosis of the outcome of the disease of a patient with tuberculosis with HIV infection upon admission to the hospital of the Federal Penitentiary Service

Author:

Borovitsky V. S.1,Sinitsyn M. V.2

Affiliation:

1. Research Institute of the Federal Penitentiary Service of Russia; Medical and Sanitary Unit No. 43 of the Federal Penitentiary Service, Tuberculosis Hospital branch

2. National Research Center for Phthisiopulmonology and Infectious Diseases; Pirogov Russian National Research Medical University

Abstract

Objective. To identify a mathematical pattern for the subsequent calculation of the prognosis of the outcome of a tuberculosis patient with HIV infection upon admission to the hospital of the Federal Penitentiary Service.Materials and methods. The object of the study was 363 patients with tuberculosis and HIV infection who were admitted for treatment at the hospital of the Federal Penitentiary Service. Discriminant analysis was used to evaluate the features most associated with the discrimination of observations, a priori divided into groups, and reclassify them. As a result, new discriminant axes were obtained, in the space of which the compared groups have the maximum difference.Results and discussion. Formulas were obtained for predicting the outcome of a tuberculosis patient with HIV infection upon admission to a medical institution of the Federal Penitentiary Service: favorable outcome =–91.2138+4.2971×(body mass index)+0.4426×(«experience» of smoking, years)+0.5143×(hemoglobin level, g/l)+0.6158×(stab neutrophils, %)+ 0.4913×(leukocyte T-cell index);unfavorable outcome =–81.8053+3.9467×(body mass index)+0.4071×(«experience» of smoking, years)+0.4724×(hemoglobin level, g/l)+0.6861×(stab neutrophils, %)+0.6630×(leukocyte T-cell index); progression or chronicity =–91.9349+4.2025×(body mass index)+0.5119×(smoking experience, years)+0.5103×(hemoglobin level, g/l)+0.5901×(stab neutrophils, %)+0.5×(leukocyte T-cell index).Conclusion. Simple formulas have been obtained that can be successfully used to calculate the prognosis of the course of the disease upon admission to a hospital in a patient with tuberculosis with concomitant HIV infection.

Publisher

Baltic Medical Education Center

Reference11 articles.

1. WHO consolidated guidelines on tuberculosis: tuberculosis preventive treatment: Module 1: prevention [Internet]. Geneva: World Health Organization, 2020.

2. Dyuzheva E.V. Indicators and dynamics of mortality in institutions of the penitentiary system. Scientific works of FKU NII FSIN of RUSSIA: scientific and practical quarterly publication of PKU NII FSIN of Russia. Moscow, 2021. Iss. 2, рр. 262–266 (In Russ.).

3. Dyuzheva E.V. Assessing awareness of risk factors for HIV infection and other infectious diseases in institutions of the penitentiary system. Scientific works of FKU NII FSIN of RUSSIA: scientific and practical quarterly publication of PKU NII FSIN of Russia. Moscow, 2020. Iss. 2, рр. 291–295 (In Russ.).

4. Ponomarev D.S., Sterlikov S.A., Ponomarev S.B., Averyanova E.L. Using an artificial neural network to model prognosis in patients with a combination of HIV infection and tuberculosis in places of deprivation of liberty. Tuberculosis and Lung Diseases, 2019, No. 5, рр. 78–79 (In Russ.). doi: 10.21292/2075-1230-2019-97-5-78-79.

5. Mikhailova Yu.V., Ponomarev S.B., Ponomarev D.S., Polishchuk V.E. et al. On the issue of developing an information system for assessing the severity of HIV infection in convicts. Healthcare Manager, 2019, No. 10, рр. 37–41 (In Russ.).

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