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Globally, drug-resistant tuberculosis (DR-TB) is responsible for 13% of mortality attributable to antimicrobial resistance. In Ethiopia, extrapulmonary tuberculosis (EPTB) is a significant public health challenge, and drug resistance (DR) in EPTB is often overlooked. In a cross-sectional study conducted between August 2022 and October 2023, we aimed to explore the magnitude of phenotypic drug resistance and identify genetic mutations linked to resistance using 189 Mycobacterium tuberculosis (MTB) isolates cultured from extrapulmonary clinical specimens.

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Tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a major global public health problem, resulting in > 1 million deaths each year. Drug resistance (DR), including the multi-drug form (MDR-TB), is challenging control of the disease. Whilst many DR mutations in the Mtb genome are known, analysis of large datasets generated using whole genome sequencing (WGS) platforms can reveal new variants through the assessment of genotype-phenotype associations.

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The catalogue of Mycobacterium tuberculosis mutations associated with drug resistance to 12 drugs in China from a nationwide survey: a genomic analysis.

Lancet Microbe

November 2024

National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China; National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Shenzhen, China. Electronic address:

Background: WHO issued the first edition catalogue of Mycobacterium tuberculosis complex (MTBC) mutations associated with drug resistance in 2021. However, country-specific issues might lead to arising complex and additional drug-resistant mutations. We aimed to fully reflect the characteristics of drug resistance mutations in China.

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There remains a clinical need for better approaches to rapid drug susceptibility testing in view of the increasing burden of multidrug resistant tuberculosis. Binary susceptibility phenotypes only capture changes in minimum inhibitory concentration when these cross the critical concentration, even though other changes may be clinically relevant. We developed a machine learning system to predict minimum inhibitory concentration from unassembled whole-genome sequencing data for 13 anti-tuberculosis drugs.

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Objectives: Readability of patient-facing information of oral antibiotics detailed in the WHO all oral short (6 months, 9 months) has not been described to date. The aim of this study was therefore to examine (i) how readable patient-facing TB antibiotic information is compared to readability reference standards and (ii) if there are differences in readability between high-incidence countries versus low-incidence countries.

Methods: Ten antibiotics, including bedaquiline, clofazimine, ethambutol, ethionamide, isoniazid, levofloxacin, linezolid, moxifloxacin, pretomanid, pyrazinamide, were investigated.

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