The use of computer techniques to optimize the diagnosis of tuberculosis in HIV-infected patients at the secondary diseases stage

Abstract

ВACKGROUND: The course of tuberculosis in HIV-infected patients has no significant clinical and diagnostic differences from damage to organs and systems of other etiology. The growth of new cases of HIV/TB co-infection necessitates a revision of diagnostic approaches, their improvement in order to increase the efficiency of examination and management of HIV-infected patients, depending on the stage and indicators of the immune status.

AIM: Of the study was to determine by the method of complex statistical processing the main clinical and laboratory-instrumental criteria for improving the diagnosis of tuberculosis in HIV-infected patients at the stage of secondary diseases.

MATERIALS AND METHODS: The study design was retrospective. The object of the research was the case histories of 113 patients with HIV infection at the stage of secondary diseases (classification by V.I. Pokrovsky), of parametric and nonparametric statistics, computer analysis of images with the gradient program proposed by Dr. Sci. A.N. Gerasimov, to assess the possibility of using micro- and macro-preparations of tissues and organs of patients with HIV infection.

RESULTS: Using the method of correlation adaptometry, it was found that there are no significant differences in the clinical course of HIV-infected patients with tuberculosis of various localization, and with lesions of the respiratory organs of other etiology. The use of multivariate probability models made it possible to identify significant diagnostic risk factors for lethal outcome ― 66.7% of patients with further lethal outcome complained of chest pain during breathing (p=0.004), and ESR was significantly accelerated in patients with a lethal outcome in the hospital ― 77±1.99 (p=0.019).

CONCLUSION: The multicomplex instrumental and laboratory examination makes it possible to diagnose tuberculosis of various localization at the initial stage of development. The use of computer techniques optimizes and unifies the diagnostic search in patients with HIV infection and determines the timely treatment tactics.

Keywords

HIV infection at the secondary diseases stage / tuberculosis / computer analysis / radiation diagnostics

References

[1] UNAIDS report shows that people living with HIV face a double jeopardy, HIV and COVID-19, while key populations and children continue to be left behind in access to HIV services. Available from: http://www.unaids.org/en. Accessed: 15.11.2020.

[2] UNAIDS report shows that people living with HIV face a double jeopardy, HIV and COVID-19, while key populations and children continue to be left behind in access to HIV services. Режим доступа: http://www.unaids.org/en. Дата обращения: 15.11.2020.

[3] Official website of the Federal Service for Supervision of Consumer Rights Protection and Human Well-being. Available from: https://rospotrebnadzor.ru.

[4] Официальный сайт Федеральной службы по надзору в сфере защиты прав потребителей и благополучия человека. Режим доступа: https://rospotrebnadzor.ru.

[5] Zimina VN, Vasilyeva IA, Kravchenko AV, et al. Diagnosis of tuberculosis in patients with HIV infection. Tuberculosis and Lung Diseases. 2014;(10):3–10. (In Russ). doi: 10.21292/2075-1230-2014-0-10-87-92

[6] Зимина В.Н., Васильева И.А., Кравченко А.В., и др. Диагностика туберкулеза у больных ВИЧ-инфекцией // Туберкулез и болезни легких. 2014. № 10. С. 3–10. doi: 10.21292/2075-1230-2014-0-10-87-92

[7] Panteleev AM. Tuberculosis of the respiratory organs in patients with HIV infection. HIV Infection Immunosuppression. 2010;2(1):16–22. (In Russ).

[8] Пантелеев А.М. Туберкулез органов дыхания у больных ВИЧ-инфекцией // ВИЧ-инфекция и иммуносупрессия. 2010. Т. 2, № 1. С. 16–22.

[9] Pokrovsky VV. HIV infection and AIDS. National leadership. Moscow: GEOTAR-Media; 2013. Р. 144–146. (In Russ).

[10] Покровский В.В. ВИЧ-инфекция и СПИД. Национальное руководство. Москва: ГЭОТАР-Медиа, 2013. С. 144–146.

[11] Mordyk AV, Puzyreva LV, Desenko AS, Rusanova NN. Tuberculosis of the central nervous system and meninges in the Omsk region for 2009–2012. Medicine Education in Siberia. 2013;(5):10–14. (In Russ).

[12] Мордык А.В., Пузырева Л.В., Десенко А.С., Русанова Н.Н. Туберкулез центральной нервной системы и мозговых оболочек в Омской области за 2009–2012 годы // Медицина и образование в Сибири. 2013. № 5. С. 10–14.

[13] Mathur M, Badhan RK, Kumari S, et al. Radiological manifestations of pulmonary tuberculosis ― a comparative study between immunocompromised and immunocompetent patients. J Clin Diagn Res. 2017;11(9):TC06–TC09. doi: 10.7860/JCDR/2017/28183.10535

[14] Mathur M., Badhan RK., Kumari S., et al. Radiological manifestations of pulmonary tuberculosis ― a comparative study between immunocompromised and immunocompetent patients // J Clin Diagn Res. 2017. Vol. 11, N 9. P. TC06–TC09. doi: 10.7860/JCDR/2017/28183.10535

[15] Boyle D. Tuberculosis Diagnostics Technology and Market Landscape. 5th Edition. Vernier: World Health Organization Unitaid Secretariat, 2017.

[16] UNAIDS calls for an integrated approach to HIV and TB services. GENEVA, 2 March 2012. Available from: http://www.unaids.org/en/media/unaids/contentassets/documents/pressstatement/2012/03/20120302_PS_HIV_TB_en.pdf. Accessed: 15.11.2020.

[17] UNAIDS calls for an integrated approach to HIV and TB services. GENEVA, 2 March 2012. Режим доступа: http://www.unaids.org/en/media/unaids/contentassets/documents/pressstatement/2012/03/20120302_PS_HIV_TB_en.pdf. Дата обращения: 15.11.2020.

[18] Gerasimov A.N. Medical statistics. Moscow: MIA; 2007; p. 480

[19] Герасимов А.Н. Медицинская статистика. Москва: МИА; 2007. 480 с.

[20] Bagdasarov VV, Bagdasarova EA, Gerasimov AN, et al. Possibilities of predicting the outcome of acute intestinal ischemia in the framework of multivariate regression analysis. Surgical Practice. 2015;(3):39–46.

[21] Багдасаров В.В., Багдасарова Е.А., Герасимов А.Н., и др. Возможности прогнозирования исхода острой интестинальной ишемии в рамках многофакторного регрессионного анализа // Хирургическая практика. 2015. № 3. С. 39–46.

[22] Golub AV, Bokarev IN, Popova LV, et al. A model for calculating the risk of venous thrombosis. Russian Journal of Cardiology. 2019;24(5): 37–43. (In Russ). doi: 10.15829/1560-4071-2019-5-37-43.

[23] Голубь А.В., Бокарев И.Н., Попова Л.В., и др. Модель расчета риска венозных тромбозов // Российский кардиологический журнал. 2019. Т. 24, № 5. С. 37–43. doi: 10.15829/1560-4071-2019-5-37-43.

RIGHTS & PERMISSIONS

Eco-vector