Literature DB >> 23721277

Rapid diagnosis of Mycobacterium tuberculosis infection and drug susceptibility testing.

Michael L Wilson1.   

Abstract

CONTEXT: The global control of tuberculosis remains a challenge from the standpoint of diagnosis, detection of drug resistance, and treatment. This is an area of special concern to the health of women and children, particularly in regions of the world with high infant mortality rates and where women have limited access to health care.
OBJECTIVE: Because treatment can only be initiated when infection is detected, and is guided by the results of antimicrobial susceptibility testing, there recently has been a marked increase in the development and testing of novel assays designed to detect Mycobacterium tuberculosis complex, with or without simultaneous detection of resistance to isoniazid and/or rifampin. Both nonmolecular and molecular assays have been developed. This review will summarize the current knowledge about the use of rapid tests to detect M tuberculosis and drug resistance. DATA SOURCES: Review of the most recent World Health Organization Global Tuberculosis Report, as well as selected publications in the primary research literature, meta-analyses, and review articles.
CONCLUSIONS: To a large extent, nonmolecular methods are refinements or modifications of conventional methods, with the primary goal of providing more rapid test results. In contrast, molecular methods use novel technologies to detect the presence of M tuberculosis complex and genes conferring drug resistance. Evaluations of molecular assays have generally shown that these assays are of variable sensitivity for detecting the presence of M tuberculosis complex, and in particular are insensitive when used with smear-negative specimens. As a group, molecular assays have been shown to be of high sensitivity for detecting resistance to rifampin, but of variable sensitivity for detecting resistance to isoniazid.

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Year:  2013        PMID: 23721277     DOI: 10.5858/arpa.2011-0578-RA

Source DB:  PubMed          Journal:  Arch Pathol Lab Med        ISSN: 0003-9985            Impact factor:   5.534


  6 in total

1.  Sputum volume predicts sputum mycobacterial load during the first 2 weeks of antituberculosis treatment.

Authors:  Miriam N Karinja; Tonya M Esterhuizen; Sven O Friedrich; Andreas H Diacon
Journal:  J Clin Microbiol       Date:  2014-12-31       Impact factor: 5.948

2.  Mycobacterium tuberculosis as a cause of mandibular osteomyelitis in a young woman: a case report.

Authors:  Jorge Tellez-Rodriguez; Rubi Lopez-Fernandez; Rodolfo Rodriguez-Jurado; Hayde Nallely Moreno-Sandoval; Francisco Martinez-Perez; Juan Antonio Gonzalez-Barrios
Journal:  J Med Case Rep       Date:  2016-12-20

3.  Detection of Mycobacterium tuberculosis in clinical sputum by a unique gene in MTB strains called Conserved protein TB18.5 (TB18.5).

Authors:  Juanxiu Luo; Xiaofei Li; Yuzhu Song; Hongwei Liu; Kexi Zheng; Xueshan Xia; A-Mei Zhang
Journal:  J Clin Lab Anal       Date:  2021-09-30       Impact factor: 2.352

4.  Phylogenetic lineages of tuberculosis isolates and their association with patient demographics in Tanzania.

Authors:  Beatrice Kemilembe Mutayoba; Norbert Heinrich; Moses L Joloba; Eligius Lyamuya; Andrew Martin Kilale; Nyagosya Segere Range; Bernard James Ngowi; Nyanda Elias Ntinginya; Saidi Mwinjuma Mfaume; Amani Wilfred; Basra Doulla; Johnson Lyimo; Riziki Kisonga; Amri Kingalu; Jupiter Marina Kabahita; Ocung Guido; Joel Kabugo; Isa Adam; Moses Luutu; Maria Magdalene Namaganda; Joanitah Namutebi; George William Kasule; Hasfah Nakato; Henry Byabajungu; Pius Lutaaya; Kenneth Musisi; Denis Oola; Gerald Mboowa; Michel Pletschette
Journal:  BMC Genomics       Date:  2022-08-05       Impact factor: 4.547

5.  MUBII-TB-DB: a database of mutations associated with antibiotic resistance in Mycobacterium tuberculosis.

Authors:  Jean-Pierre Flandrois; Gérard Lina; Oana Dumitrescu
Journal:  BMC Bioinformatics       Date:  2014-04-14       Impact factor: 3.169

6.  Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis.

Authors:  Salma Jamal; Mohd Khubaib; Rishabh Gangwar; Sonam Grover; Abhinav Grover; Seyed E Hasnain
Journal:  Sci Rep       Date:  2020-03-26       Impact factor: 4.379

  6 in total

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