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Predictors of Outcome in Drug Resistant Tuberculosis Patients | OMICS International | Abstract
ISSN: 2161-105X

Journal of Pulmonary & Respiratory Medicine
Open Access

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Research Article

Predictors of Outcome in Drug Resistant Tuberculosis Patients

Arivudainambi Periasamy*

K.A.P.Viswanatham Government Medical College, Tiruchirappalli, India

*Corresponding Author:
Arivudainambi Periasamy
K.A.P.Viswanatham Government Medical College
Tiruchirappalli, India
Tel: +919443248165
E-mail: [email protected]

Received date: November 05, 2016; Accepted date: January 27, 2017; Published date: January 30, 2017

Citation: Periasamy A (2017) Predictors of Outcome in Drug Resistant Tuberculosis Patients. J Pulm Respir Med 7:391. doi: 10.4172/2161-105X.1000391

Copyright: © 2017 Periasamy A. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Introduction: Multi-drug-resistant tuberculosis (MDRTB) is a major public health problem due to longer duration of treatment and unfavourable outcome in comparison with sensitive TB.
Aim: Registered Drug resistant tuberculosis (DRTB) patients were prospectively followed from 2011-2015. Analysis of treatment outcomes was by done by their demographic and clinical data which were hypothesized to be outcome predictors.
Methods: Logistic regression and univariate logistic regression were used upon data of patients registered for MDRTB treatment in Trichy district Tamilnadu, India. Totally 63 MDRTB patients were treated from 2011-15. Outcomes were reported as success & failure. Success included cured and treatment completed patients and Failure included treatment failure, death, defaulted, untraceable cases. SPSS 21 was used.
Results: Out of total 63 cases, 33 cases had failed outcome and 30 cases had successful outcome. Among variables Diabetes, XDRTB suspects, drug abuse & smoking were associated with failed outcome. Sex, age, chest x-ray lesion, pre-treatment resistance profile, did not affect the outcome. By logistic regression (enter) method the odds of failed outcome were 11.737 with smoking, the odds of failed outcome was 12.43 with XDRTB suspects, and the odds of failure with diabetes was 12.61. The P-value of smoking, XDRTB suspect, diabetes obtained was 0.019, 0.049, and 0.036 respectively. Chi square test showed significant P-value for variables sex, diabetes, XDR suspects, smoking and drug abuse, but insignificant P-value for HIV, comorbid illness like renal failure. Similarly, age, chest x-ray lesion like cavitary, caseous lesion, did not affect the outcome as per logistic regression analysis.
Conclusion: Smoking, PreXDRTB, Diabetes, were factors affecting the outcome of treatment independently hence predictors of outcome in MDRTB. The emergence of preXDRTB as independent factor determining the outcome is significant emphasizing the earlier switch to XDRTB regimen.