AN INTEGRATED SYSTEM FOR PREDICTION OF ADVERSE OUTCOME DURING ANTI-TUBERCULOSIS TREATMENT
Abstract
Тo develop a comprehensive method for evaluating the risk of an adverse outcome during anti-tuberculosis (anti-TB) treatment. Materials and Methods: We recruited 10,398 adult patients with either primary pulmonary TB or TB relapse. All patients were divided into 2 groups: 7,249 patients with a favorable outcome and 3,149 patients with an adverse outcome. We then assessed a number of social and medical factors which could be significant predictors of an adverse outcome. For the statistical analysis, we used the likelihood ratio (LR) method. Results: All variables were stratified into levels or classes. We then calculated LR for each level or class and further calculated diagnostic ratios for the integrated evaluation of each factor in predicting the adverse outcome. Conclusions: Our original integrated system may assist in calculating the risk of an adverse outcome during anti-TB treatment.
About the Authors
Т. Tatiana V. Pianzova
Kemerovo State Medical University
Russian Federation
Russian Federation
Е.С. Elena S. Kagan
Kemerovo State University
Russian Federation
Russian Federation
А. Anastasia A. Abros'kina
Kemerovo State University
Russian Federation
Russian Federation
References
1. Felker IG, Filinyuk OV, Yanova GV, Schegertsov DY. Predictors of treatment failure for the program DOTS-PLUS in patients with multidrug-resistant tuberculosis. Bulletin of the Siberian medicine. 2012; (4): 171-173. Russian (Фелькер И.Г., Филинюк О.В., Янова Г.В., Щегерцов Д.Ю. Предикторы неудачи в лечении по программе DOTS-PLUS у пациентов, страдающих множественно лекарственно-устойчивым туберкулезом // Бюллетень сибирской медицины. 2012. № 4. С. 171-173.
2. Moiseeva OV, Soklakova AV. Mathematical techniques in forecasting epidemiological indicators in children. Tuberculosis and Pulmonology. 2015. (2/10): 225-233. Russian (Моисеева О.В., Соклакова А.В. Математические технологии в прогнозировании эпидемиологических показателей у детей // Фтизиатрия и пульмонология. 2015. №2 (10). С. 225-233).
3. Mordyk AV, Puzyreva LV, Batishcheva TL. Factors determining the outcome of the first diagnosed infiltrative tuberculosis in social intact patients. Zemsky doctor. 2015; (2/26): 31-35. Russian (Мордык А.В., Пузырева Л.В., Батищева Т.Л. Факторы, определяющие исход впервые выявленного инфильтративного туберкулеза у социально сохранных пациентов // Земский врач. 2015. № 2 (26). С. 31-35).
4. Alavi Naini R., Moghtaderi A., Metanat M., Mohammadi M., Zabetian M. Factors associated with mortality in tuberculosis patients. Journal of Research in Medical Sciences. 2013; (18): 52-55.
5. Zorina SP, Lineva ZE. Modelling of primary disability due to pulmonary. Bulletin RAMS. 2011; (2): 202-205. Russian (Зорина С.П., Линева З.Е. Моделирование первичной инвалидности вследствие туберкулеза легких // Бюллетень ВСНЦ СО РАМН. 2011. №2. С. 202-205).
6. Krasnov VA, Chernyshev VM, Strelchenko OV et al. Obstacles to improve the TB situation in the regions of the Siberian Federal District. Tuberculosis and Lung Disease. 2012; 10: 8-14. Russian (Краснов В.А., Чернышев В.М., Стрельченко О.В. и др. Факторы, препятствующие улучшению ситуации по туберкулезу в субъектах Сибирского Федерального округа // Туберкулез и болезни легких. 2012. №10. С. 8-14).
7. Shilova MV. Tuberculosis in Russia: M.: Promobyuro, 2014. 244 p. Russian (Шилова М.В. Туберкулез в России. М.: Промобюро, 2014. 244 с.).
8. Sheegan EN. The application of modern mathematical approaches and computational tools in healthcare. M.: Publisher Samus, 1973. p. 41. Russian (Шиган Е.Н. Применение современных математических подходов и вычислительных средств в здравоохранении. М.: Издательство САМУС, 1973. С.41).
9. Kagan ES, Pyanzova TV. Application of the likelihood ratio for a comprehensive assessment of social risk factors of low efficiency of anti-tuberculosis therapy. Bulletin of the Academy of Sciences of Moldova Medicine. 2012; (4/36): 45-48. Russian (Каган Е.С., Пьянзова Т.В. Применение метода отношения правдоподобия для комплексной оценки социальных факторов риска низкой эффективности противотуберкулезной терапии // Бюллетень Академии наук Молдовы. Медицина. 2012. №4 (36). С. 45-48).
Review
For citations:
Tatiana V. Pianzova , Elena S. Kagan , Anastasia A. Abros'kina AN INTEGRATED SYSTEM FOR PREDICTION OF ADVERSE OUTCOME DURING ANTI-TUBERCULOSIS TREATMENT. Fundamental and Clinical Medicine. 2016;1(1):33-38. (In Russ.)
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