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Prevalence of current patterns and predictive trends of multidrug-resistant Salmonella Typhi in Sudan

Overview of attention for article published in Annals of Clinical Microbiology and Antimicrobials, November 2017
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Title
Prevalence of current patterns and predictive trends of multidrug-resistant Salmonella Typhi in Sudan
Published in
Annals of Clinical Microbiology and Antimicrobials, November 2017
DOI 10.1186/s12941-017-0247-4
Pubmed ID
Authors

Ayman A. Elshayeb, Abdelazim A. Ahmed, Marmar A. El Siddig, Adil A. El Hussien

Abstract

Enteric fever has persistence of great impact in Sudanese public health especially during rainy season when the causative agent Salmonella enterica serovar Typhi possesses pan endemic patterns in most regions of Sudan - Khartoum. The present study aims to assess the recent state of antibiotics susceptibility of Salmonella Typhi with special concern to multidrug resistance strains and predict the emergence of new resistant patterns and outbreaks. Salmonella Typhi strains were isolated and identified according to the guidelines of the International Standardization Organization and the World Health Organization. The antibiotics susceptibilities were tested using the recommendations of the Clinical Laboratories Standards Institute. Predictions of emerging resistant bacteria patterns and outbreaks in Sudan were done using logistic regression, forecasting linear equations and in silico simulations models. A total of 124 antibiotics resistant Salmonella Typhi strains categorized in 12 average groups were isolated, different patterns of resistance statistically calculated by (y = ax - b). Minimum bactericidal concentration's predication of resistance was given the exponential trend (y = n e(x)) and the predictive coefficient R(2) > 0 < 1 are approximately alike. It was assumed that resistant bacteria occurred with a constant rate of antibiotic doses during the whole experimental period. Thus, the number of sensitive bacteria decreases at the same rate as resistant occur following term to the modified predictive model which solved computationally. This study assesses the prediction of multi-drug resistance among S. Typhi isolates by applying low cost materials and simple statistical methods suitable for the most frequently used antibiotics as typhoid empirical therapy. Therefore, bacterial surveillance systems should be implemented to present data on the aetiology and current antimicrobial drug resistance patterns of community-acquired agents causing outbreaks.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 72 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 17%
Student > Ph. D. Student 8 11%
Student > Master 8 11%
Student > Doctoral Student 6 8%
Student > Bachelor 5 7%
Other 11 15%
Unknown 22 31%
Readers by discipline Count As %
Medicine and Dentistry 19 26%
Immunology and Microbiology 8 11%
Biochemistry, Genetics and Molecular Biology 7 10%
Agricultural and Biological Sciences 5 7%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Other 8 11%
Unknown 23 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 November 2017.
All research outputs
#18,576,001
of 23,007,887 outputs
Outputs from Annals of Clinical Microbiology and Antimicrobials
#461
of 611 outputs
Outputs of similar age
#249,058
of 325,276 outputs
Outputs of similar age from Annals of Clinical Microbiology and Antimicrobials
#10
of 11 outputs
Altmetric has tracked 23,007,887 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 611 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 325,276 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.