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. 2015:2015:261925.
doi: 10.1155/2015/261925. Epub 2015 Mar 9.

A prospective study of tuberculosis drug susceptibility in sabah, malaysia, and an algorithm for management of isoniazid resistance

Affiliations

A prospective study of tuberculosis drug susceptibility in sabah, malaysia, and an algorithm for management of isoniazid resistance

Muhammad Redzwan S Rashid Ali et al. J Trop Med. 2015.

Abstract

Introduction. The burden of tuberculosis is high in eastern Malaysia, and rates of Mycobacterium tuberculosis drug resistance are poorly defined. Our objectives were to determine M. tuberculosis susceptibility and document management after receipt of susceptibility results. Methods. Prospective study of adult outpatients with smear-positive pulmonary tuberculosis (PTB) in Sabah, Malaysia. Additionally, hospital clinicians accessed the reference laboratory for clinical purposes during the study. Results. 176 outpatients were enrolled; 173 provided sputum samples. Mycobacterial culture yielded M. tuberculosis in 159 (91.9%) and nontuberculous Mycobacterium (NTM) in three (1.7%). Among outpatients there were no instances of multidrug resistant M. tuberculosis (MDR-TB). Seven people (4.5%) had isoniazid resistance (INH-R); all were switched to an appropriate second-line regimen for varying durations (4.5-9 months). Median delay to commencement of the second-line regimen was 13 weeks. Among 15 inpatients with suspected TB, 2 had multidrug resistant TB (one extensively drug resistant), 2 had INH-R, and 4 had NTM. Conclusions. Current community rates of MDR-TB in Sabah are low. However, INH-resistance poses challenges, and NTM is an important differential diagnosis in this setting, where smear microscopy is the usual diagnostic modality. To address INH-R management issues in our setting, we propose an algorithm for the treatment of isoniazid-resistant PTB.

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Figures

Figure 1
Figure 1
Outpatient study diagram showing enrolment and microbiological results.
Figure 2
Figure 2
Hospital inpatients with suspected mycobacterial infection.
Figure 3
Figure 3
Algorithm for managing isoniazid resistance.

References

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