Evaluation of direct detection of Mycobacterium tuberculosis complex in respiratory and non-respiratory clinical specimens using the Cepheid Gene Xpert® system

Autor: Souad M, Al-Ateah, Maha M, Al-Dowaidi, Noura A, El-Khizzi
Rok vydání: 2012
Předmět:
Zdroj: Saudi medical journal. 33(10)
ISSN: 0379-5284
Popis: To compare the sensitivity and specificity of Cepheid Gene Xpert®, MTB/RIF assay for direct detection of Mycobacterium tuberculosis complex (MTBC) and rifampin (RIF) resistance with conventional methods in respiratory and non-respiratory clinical specimens.We used a cross sectional design to evaluate a diagnostic test at the TB Section of the Division of Microbiology, Central Military Laboratory and Blood Bank, Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia from October 2011 to January 2012. The detection of MTBC and RIF resistance using the Xpert® MTB/RIF assay was assessed in 239 (172 respiratory, and 67 non respiratory) specimens received from 234 patients suspected of TB, and compared with conventional smear microscopy and culture methods.Out of the 239 specimens investigated, 62 (25.9%) were MTBC positive by culture, while 59 (24.6%) were positive by Xpert® assay. Three samples showed false negative Xpert® results. Compared with the culture, the Xpert® assay achieved 95.4% (95% CI: 89-100%) sensitivity, and 100% (95% CI: 93.6-100%) specificity for respiratory samples, while the sensitivity for non-respiratory specimens was 94.4% (95% CI: 90.2-98.5), and the specificity for non-respiratory specimens was 100% (95% CI: 95.8-100%). Overall, a 95.2% (95% CI: 87.6-100) sensitivity, and 100% (95% CI: 92.4-100%) specificity, was observed for the Xpert® MTB/RIF assay compared with conventional methods for MTBC detection.The gene Xpert® MTB/RIF assay is a helpful tool for the detection of MTBC and RIF resistance in respiratory and non-respiratory clinical samples with a high sensitivity and specificity within 2 hours as compared with conventional methods, which took a much longer time.
Databáze: OpenAIRE