Abstract
OBJECTIVE. To validate the polymerase chain reaction-based universal heteroduplex generator (PCR UHG-Rif) assay for identifying rifampin-resistant and multidrug-resistant (MDR, resistant to isoniazid and rifampin) Mycobacterium tuberculosis in patients with pulmonary tuberculosis from communities in Lima (Peru) with a high incidence of resistant tuberculosis. DESIGN. To compare the results of antituberculosis drug susceptibility testing in clinical samples performed by the proportion method with those obtained by the PCR UHG-Rif assay, with the aim of analyzing the diagnostic capability of PCR UHG-Rif. RESULTS. Concordance for the identification of antituberculosis drug susceptibility was 0.95 (κ = 0.899; P < .05), with a sensitivity and specificity of 0.973 and 0.922 (P < .05), respectively. The positive predictive value was 0.939 (95% CI: 0.879-0.970) and the negative predictive value was 0.965 (95% CI: 0.902-0.988). Nevertheless, the probability for MDR prediction was 0.981 (P < .05). PCR UHG-Rif allows the detection of mixed populations; discordant results can be explained by the presence of point mutations, missense mutations and mutations outside the rpoB "hot" region associated with rifampin-resistance. CONCLUSIONS. The PCR UHG-Rif assay detects mutations in the rpoB gene with excellent sensitivity and specificity, and suitable predictive values when compared with the standard method for determining susceptibility to antituberculosis drugs. This test can be considered an excellent tool that can contribute to tuberculosis control by correctly identifying patients infected with resistant and MDR bacilli, leading to a reduction in the cases of tuberculosis and resistant tuberculosis.
| Translated title of the contribution | Validation of the PCR-based universal heteroduplex generator assay for identification of rifampicin-resistant and multiresistant Mycobacterium tuberculosis in Lima, Peru |
|---|---|
| Original language | Spanish |
| Pages (from-to) | 495-499 |
| Number of pages | 5 |
| Journal | Enfermedades Infecciosas y Microbiologia Clinica |
| Volume | 24 |
| Issue number | 8 |
| DOIs | |
| State | Published - Oct 2006 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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