The DOI matches its Crossref record; 82 of the 82 references it cites were found in a registry or an index.
Drug-resistant enteric fever worldwide, 1990 to 2018: a systematic review and meta-analysis
Open accessAbstract
Background: Antimicrobial resistance (AMR) is an increasing threat to global health. There are > 14 million cases of enteric fever every year and > 135,000 deaths. The disease is primarily controlled by antimicrobial treatment, but this is becoming increasingly difficult due to AMR. Our objectives were to assess the prevalence and geographic distribution of AMR in Salmonella enterica serovars Typhi and Paratyphi A infections globally, to evaluate the extent of the problem, and to facilitate the creation of geospatial maps of AMR prevalence to help targeted public health intervention. Methods: We performed a systematic review of the literature by searching seven databases for studies published between 1990 and 2018. We recategorised isolates to allow the analysis of fluoroquinolone resistance trends over the study period. The prevalence of multidrug resistance (MDR) and fluoroquinolone non-susceptibility (FQNS) in individual studies was illustrated by forest plots, and a random effects meta-analysis was performed, stratified by Global Burden of Disease (GBD) region and 5-year time period. Heterogeneity was assessed using the I2 statistics. We present a descriptive analysis of ceftriaxone and azithromycin resistance. Findings: We identified 4557 articles, of which 384, comprising 124,347 isolates (94,616 S. Typhi and 29,731 S. Paratyphi A) met the pre-specified inclusion criteria. The majority (276/384; 72%) of studies were from South Asia; 40 (10%) articles were identified from Sub-Saharan Africa. With the exception of MDR S. Typhi in South Asia, which declined between 1990 and 2018, and MDR S. Paratyphi A, which remained at low levels, resistance trends worsened for all antimicrobials in all regions. We identified several data gaps in Africa and the Middle East. Incomplete reporting of antimicrobial susceptibility testing (AST) and lack of quality assurance were identified. Interpretation: Drug-resistant enteric fever is widespread in low- and middle-income countries, and the situation is worsening. It is essential that public health and clinical measures, which include improvements in water quality and sanitation, the deployment of S. Typhi vaccination, and an informed choice of treatment are implemented. However, there is no licenced vaccine for S. Paratyphi A. The standardised reporting of AST data and rollout of external quality control assessment are urgently needed to facilitate evidence-based policy and practice. Trial registration: PROSPERO CRD42018029432.
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Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000097 · Cited by 64,042
Measuring inconsistency in meta-analyses
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003) · BMJ · doi:10.1136/bmj.327.7414.557 · Cited by 63,139
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
Wang, G., Ma, R., Qiao, G., Wada, K., Aizawa, Y., & Satoh, T. (2015) · Integrative Medicine International · doi:10.1159/000368408 · Cited by 18,657
Vandenbroucke, J. P., von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., Egger, M., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040297 · Cited by 8,613 · cited 2×
“The absence of robust AST data may reflect weaknesses, varying testing methodology and performance across laboratories in LMICs, but partially also reflects the lack of clear and coherent reporting guidelines for microbiology data, comparable to STROBE [121].”
ResultPerformance standards for antimicrobial susceptibility testing
Weinstein, M. P., & Clinical (2019) · Clinical and Laboratory Standards Institute eBooks · Cited by 4,341
Global increase and geographic convergence in antibiotic consumption between 2000 and 2015
Klein, E. Y., Van Boeckel, T. P., Martinez, E. M., Pant, S., Gandra, S., Levin, S. A., Goossens, H., & Laxminarayan, R. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1717295115 · Cited by 3,232
Approximate is Better than “Exact” for Interval Estimation of Binomial Proportions
Agresti, A., & Coull, B. A. (1998) · The American Statistician · doi:10.1080/00031305.1998.10480550 · Cited by 3,223
Gupta, K., Hooton, T. M., Naber, K. G., Wullt, B., Colgan, R., Miller, L. G., Moran, G. J., Nicolle, L. E., Raz, R., Schaeffer, A. J., et al. (2011) · Clinical Infectious Diseases · doi:10.1093/cid/ciq257 · Cited by 3,038
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Model Generalization on COVID-19 Fake News Detection
Bang, Y., Ishii, E., Cahyawijaya, S., Ji, Z., & Fung, P. (2021) · Communications in Computer and Information Science · doi:10.1007/978-3-030-73696-5_13 · Cited by 52
Metadata
- Authors
- Browne, A. J., Kashef Hamadani, B. H., Kumaran, E. A. P., Rao, P., Longbottom, J., Harriss, E., Moore, C. E., Dunachie, S., Basnyat, B., Baker, S., Lopez, A. D., Day, N. P. J., Hay, S. I., & Dolecek, C.
- Venue
- BMC Medicine
- Published
- 2020-01-03
- Volume
- 18
- Issue
- 1
- Pages
- 1-1
- ISSN
- 1741-7015 (ISSN-L)
- OpenAlex
- W2999170785
- Cited by
- 396
- References
- 82
- FWCI
- 9.99
- Type
- journal article
- Language
- en
- Open access
- gold
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- Browne, A. J., Kashef Hamadani, B. H., Kumaran, E. A. P., Rao, P., Longbottom, J., Harriss, E., Moore, C. E., Dunachie, S., Basnyat, B., Baker, S., Lopez, A. D., Day, N. P. J., Hay, S. I., & Dolecek, C. (2020). Drug-resistant enteric fever worldwide, 1990 to 2018: a systematic review and meta-analysis. BMC Medicine. https://doi.org/10.1186/s12916-019-1443-1
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