The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Drug resistant tuberculosis: Implications for transmission, diagnosis, and disease management
Open accessAbstract
Drug resistant tuberculosis contributes significantly to the global burden of antimicrobial resistance, often consuming a large proportion of the healthcare budget and associated resources in many endemic countries. The rapid emergence of resistance to newer tuberculosis therapies signals the need to ensure appropriate antibiotic stewardship, together with a concerted drive to develop new regimens that are active against currently circulating drug resistant strains. Herein, we highlight that the current burden of drug resistant tuberculosis is driven by a combination of ongoing transmission and the intra-patient evolution of resistance through several mechanisms. Global control of tuberculosis will require interventions that effectively address these and related aspects. Interrupting tuberculosis transmission is dependent on the availability of novel rapid diagnostics which provide accurate results, as near-patient as is possible, together with appropriate linkage to care. Contact tracing, longitudinal follow-up for symptoms and active mapping of social contacts are essential elements to curb further community-wide spread of drug resistant strains. Appropriate prophylaxis for contacts of drug resistant index cases is imperative to limit disease progression and subsequent transmission. Preventing the evolution of drug resistant strains will require the development of shorter regimens that rapidly eliminate all populations of mycobacteria, whilst concurrently limiting bacterial metabolic processes that drive drug tolerance, mutagenesis and the ultimate emergence of resistance. Drug discovery programs that specifically target bacterial genetic determinants associated with these processes will be paramount to tuberculosis eradication. In addition, the development of appropriate clinical endpoints that quantify drug tolerant organisms in sputum, such as differentially culturable/detectable tubercle bacteria is necessary to accurately assess the potential of new therapies to effectively shorten treatment duration. When combined, this holistic approach to addressing the critical problems associated with drug resistance will support delivery of quality care to patients suffering from tuberculosis and bolster efforts to eradicate this disease.
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Cites
Definitions and guidelines for research on antibiotic persistence
Balaban, N. Q., Helaine, S., Lewis, K., Ackermann, M., Aldridge, B., Andersson, D. I., Brynildsen, M. P., Bumann, D., Camilli, A., Collins, J. J., et al. (2019) · Nature Reviews Microbiology · doi:10.1038/s41579-019-0196-3 · Cited by 1,313
Antibiotic resistance and persistence—implications for human health and treatment perspectives
Huemer, M., Mairpady Shambat, S., Brugger, S. D., & Zinkernagel, A. S. (2020) · The EMBO Reports · doi:10.15252/embr.202051034 · Cited by 850
Metformin as adjunct antituberculosis therapy
Singhal, A., Jie, L., Kumar, P., Hong, G. S., Leow, M. K.-S., Paleja, B., Tsenova, L., Kurepina, N., Chen, J., Zolezzi, F., et al. (2014) · Science Translational Medicine · doi:10.1126/scitranslmed.3009885 · Cited by 547
Mechanisms and clinical relevance of bacterial heteroresistance
Andersson, D. I., Nicoloff, H., & Hjort, K. (2019) · Nature Reviews Microbiology · doi:10.1038/s41579-019-0218-1 · Cited by 513
Asymmetry and Aging of Mycobacterial Cells Lead to Variable Growth and Antibiotic Susceptibility
Aldridge, B. B., Fernandez-Suarez, M., Heller, D., Ambravaneswaran, V., Irimia, D., Toner, M., & Fortune, S. M. (2012) · Science · doi:10.1126/science.1216166 · Cited by 454
Deletion of a mycobacterial divisome factor collapses single-cell phenotypic heterogeneity
Rego, E. H., Audette, R. E., & Rubin, E. J. (2017) · Nature · doi:10.1038/nature22361 · Cited by 186
The Epidemiological Importance of Subclinical Tuberculosis. A Critical Reappraisal
Kendall, E. A., Shrestha, S., & Dowdy, D. W. (2021) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202006-2394pp · Cited by 185
Single-cell dynamics of the chromosome replication and cell division cycles in mycobacteria
Santi, I., Dhar, N., Bousbaine, D., Wakamoto, Y., & McKinney, J. D. (2013) · Nature Communications · doi:10.1038/ncomms3470 · Cited by 170
Williams, C. M., Abdulwhhab, M., Birring, S. S., De Kock, E., Garton, N. J., Townsend, E., Pareek, M., Al-Taie, A., Pan, J., Ganatra, R., et al. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(19)30707-8 · Cited by 142
Aerosolization of Mycobacterium tuberculosis by Tidal Breathing
Dinkele, R., Gessner, S., McKerry, A., Leonard, B., Leukes, J., Seldon, R., Warner, D. F., & Wood, R. (2022) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202110-2378oc · Cited by 83
Metadata
- Authors
- Liebenberg, D., Gordhan, B. G., & Kana, B. D.
- Venue
- Frontiers in Cellular and Infection Microbiology
- Publisher
- Frontiers Media SA
- Published
- 2022-09-23
- Volume
- 12
- Pages
- 943545-943545
- ISSN
- 2235-2988 (ISSN-L)
- OpenAlex
- W4297009263
- Cited by
- 184
- References
- 12
- FWCI
- 14.29
- Type
- journal article
- Language
- en
- Open access
- gold
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- Liebenberg, D., Gordhan, B. G., & Kana, B. D. (2022). Drug resistant tuberculosis: Implications for transmission, diagnosis, and disease management. Frontiers in Cellular and Infection Microbiology. https://doi.org/10.3389/fcimb.2022.943545
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.