Treatment of multiple drug-resistant tuberculosis (MDR-TB) in Iran

The objective of the study: to identify risk factors for relapses in patients after the effective course of chemotherapy for multiple drug resistant tuberculosis (MDR TB). Subjects and methods. Medical files of 346 adult MDR TB patients were analyzed, they all had the effective treatment as per regimen IV in Tomsk Phthisiopulmonology Medical Center in 2009-2011. They were divided into 2 groups: Group 1 included 35 patients who developed a relapse of tuberculosis over the next 5 years; Group 2 consisted of 311 patients who had no relapse of the disease over the next 5 years. Results. The relapse rate in effectively treated MDR TB patients made 10.1% (35/346 patients). The following social factors contributed to higher chances of the relapse: retirement age (p = 0.045; OR = 2.86 [1.14-7.20]) and disability due to somatic diseases (p < 0.001; OR = 4.82 [2.13-10.90]); while biomedical factors were the following: HIV infection (OR = 19.19 [5.29-69.56]), mental illness (OR = 5.85 [2.27-15.03]), tobacco smoking (OR = 3.16 [1.08-9.20]). People with history of tuberculosis relapses (OR = 12.17 [4.19-35.34]) have higher chances of relapse, as well as those having the following characteristics of the tuberculosis disease during the effective chemotherapy course: destruction of lung tissue (OR = 7.48 [1.76-31.80]), positive results of sputum smear microscopy (OR = 2.91 [1.28-6.61]), persisting bacterial excretion (by culture) after 2 months of chemotherapy (OR = 4.98 [2.41-10.29]).

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Machine Learning for Prediction of Relapses in Multiple Drug Resistant Tuberculosis Patients

Tuberculosis and lung diseases ◽

10.21292/2075-1230-2021-99-11-27-34 ◽

2021 ◽

Vol 99 (11) ◽

pp. 27-34

Author(s):

A. S. Аlliluev ◽

O. V. Filinyuk ◽

E. E. Shnаyder ◽

S. V. Аksenov

Keyword(s):

Machine Learning ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Gradient Boosting ◽

Multiple Drug ◽

Drug Resistant ◽

Drug Resistant Tuberculosis ◽

Resistant Tuberculosis ◽

Multiple Drug Resistant ◽

Mdr Tb

The objective of the study: to evaluate the possibility of using machine learning algorithms for prediction of relapses in multiple drug resistant tuberculosis (MDR TB) patients.Subjects and Methods. Сlinical, epidemiological, gender, sex, social, biomedical parameters and chemotherapy parameters were analyzed in 346 cured MDR TB patients. The tools of the scikit-learn library, Version 0.24.2 in the Google Colaboratory interactive cloud environment were used to build forecasting models.Results. Analysis of the characteristics of relapse prediction models in cured MDR TB patients using machine learning algorithms including decision tree, random forest, gradient boosting, and logistic regression using K-block stratified validation revealed high sensitivity (0.74 ± 0.167; 0.91 ± 0.17; 0.91 ± 0.14; 0.91 ± 0.16, respectively) and specificity (0.97 ± 0.03; 0.98 ± 0.02; 0.98 ± 0.02; 0.98 ± 0.02, respectively).Five main predictors of relapse in cured MDR-TB patients were identified: repeated courses of chemotherapy; length of history of tuberculosis; destructive process in the lungs; total duration of treatment less than 22 months; and use of less than five effective anti-TB drugs in the regimen of chemotherapy.

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Predictors of primary multiple drug resistant tuberculosis (MDR-TB) transmission in Lima, Peru

International Journal of Infectious Diseases ◽

10.1016/j.ijid.2010.02.1544 ◽

2010 ◽

Vol 14 ◽

pp. e25-e26

Author(s):

L. Shah ◽

H. Choi ◽

F. Krapp ◽

C. Zamudio ◽

C. Seas ◽

...

Keyword(s):

Multiple Drug ◽

Drug Resistant ◽

Drug Resistant Tuberculosis ◽

Resistant Tuberculosis ◽

Multiple Drug Resistant ◽

Mdr Tb

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OTOTOXICITY IN MDR-TB PATIENTS ON CATEGORY-4 REGIMEN: A CASE REPORT

Era s journal of medical research ◽

10.24041/ejmr2020.45 ◽

2020 ◽

Vol 7 (2) ◽

pp. 257-259

Author(s):

Tanish Baqar ◽

Sharique Ahmad ◽

Silky Rai

Keyword(s):

Case Report ◽

Large Scale ◽

Multiple Drug Resistance ◽

Multiple Drug ◽

Drug Resistant ◽

Drug Resistant Tuberculosis ◽

Medical Progress ◽

Resistant Tuberculosis ◽

Multiple Drug Resistant ◽

Mdr Tb

Multiple drug-resistant tuberculosis (MDR-TB) is a critical situation affecting adults as properly as children across the globe (1). To determine the incidence and risk factors associated with Multiple Drug Resistant Tuberculosis (MDR-TB) (2), we studied Ototoxicity on 18 culture confirmed MDR-TB patients in Eras' Lucknow Medical College and Hospital, Lucknow from September, 2019 to January, 2020. This case follows a well documented report of a patient describing an unusual and novel occurrence of ototoxicity when undergoing treatment concerning multiple drug resistance tuberculosis along with symptoms, signs, diagnosis, treatment and follow-up (3). For descriptive convenience, the patient will be classified as patient 1. The following case is the cornerstones of medical progress and provides many new ideas in medicine. Containing an extensive review of the relevant literature on the topic, the case report is a rapid short communication between busy clinicians who may not have time or resources to conduct large scale research.(4)

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