Title |
Rapid diagnostics of tuberculosis and drug resistance in the industrialized world: clinical and public health benefits and barriers to implementation
|
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Published in |
BMC Medicine, August 2013
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DOI | 10.1186/1741-7015-11-190 |
Pubmed ID | |
Authors |
Francis Drobniewski, Vladyslav Nikolayevskyy, Horst Maxeiner, Yanina Balabanova, Nicola Casali, Irina Kontsevaya, Olga Ignatyeva |
Abstract |
In this article, we give an overview of new technologies for the diagnosis of tuberculosis (TB) and drug resistance, consider their advantages over existing methodologies, broad issues of cost, cost-effectiveness and programmatic implementation, and their clinical as well as public health impact, focusing on the industrialized world. Molecular nucleic-acid amplification diagnostic systems have high specificity for TB diagnosis (and rifampicin resistance) but sensitivity for TB detection is more variable. Nevertheless, it is possible to diagnose TB and rifampicin resistance within a day and commercial automated systems make this possible with minimal training. Although studies are limited, these systems appear to be cost-effective. Most of these tools are of value clinically and for public health use. For example, whole genome sequencing of Mycobacterium tuberculosis offers a powerful new approach to the identification of drug resistance and to map transmission at a community and population level. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 38% |
Rwanda | 1 | 13% |
Nigeria | 1 | 13% |
Ethiopia | 1 | 13% |
Unknown | 2 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 63% |
Practitioners (doctors, other healthcare professionals) | 2 | 25% |
Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 1% |
Spain | 2 | 1% |
Colombia | 1 | <1% |
Italy | 1 | <1% |
Germany | 1 | <1% |
Belgium | 1 | <1% |
Malaysia | 1 | <1% |
Unknown | 186 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 40 | 21% |
Researcher | 33 | 17% |
Student > Ph. D. Student | 24 | 12% |
Student > Bachelor | 23 | 12% |
Other | 12 | 6% |
Other | 33 | 17% |
Unknown | 30 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 58 | 30% |
Agricultural and Biological Sciences | 26 | 13% |
Biochemistry, Genetics and Molecular Biology | 16 | 8% |
Immunology and Microbiology | 12 | 6% |
Nursing and Health Professions | 11 | 6% |
Other | 33 | 17% |
Unknown | 39 | 20% |