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Deep sequencing approach for investigating infectious agents causing fever

Overview of attention for article published in European Journal of Clinical Microbiology & Infectious Diseases, May 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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1 blog
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7 X users

Citations

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57 Mendeley
Title
Deep sequencing approach for investigating infectious agents causing fever
Published in
European Journal of Clinical Microbiology & Infectious Diseases, May 2016
DOI 10.1007/s10096-016-2644-6
Pubmed ID
Authors

T. N. Susilawati, A. R. Jex, C. Cantacessi, M. Pearson, S. Navarro, A. Susianto, A. C. Loukas, W. J. H. McBride

Abstract

Acute undifferentiated fever (AUF) poses a diagnostic challenge due to the variety of possible aetiologies. While the majority of AUFs resolve spontaneously, some cases become prolonged and cause significant morbidity and mortality, necessitating improved diagnostic methods. This study evaluated the utility of deep sequencing in fever investigation. DNA and RNA were isolated from plasma/sera of AUF cases being investigated at Cairns Hospital in northern Australia, including eight control samples from patients with a confirmed diagnosis. Following isolation, DNA and RNA were bulk amplified and RNA was reverse transcribed to cDNA. The resulting DNA and cDNA amplicons were subjected to deep sequencing on an Illumina HiSeq 2000 platform. Bioinformatics analysis was performed using the program Kraken and the CLC assembly-alignment pipeline. The results were compared with the outcomes of clinical tests. We generated between 4 and 20 million reads per sample. The results of Kraken and CLC analyses concurred with diagnoses obtained by other means in 87.5 % (7/8) and 25 % (2/8) of control samples, respectively. Some plausible causes of fever were identified in ten patients who remained undiagnosed following routine hospital investigations, including Escherichia coli bacteraemia and scrub typhus that eluded conventional tests. Achromobacter xylosoxidans, Alteromonas macleodii and Enterobacteria phage were prevalent in all samples. A deep sequencing approach of patient plasma/serum samples led to the identification of aetiological agents putatively implicated in AUFs and enabled the study of microbial diversity in human blood. The application of this approach in hospital practice is currently limited by sequencing input requirements and complicated data analysis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 14%
Student > Master 7 12%
Professor 7 12%
Student > Bachelor 7 12%
Student > Ph. D. Student 6 11%
Other 10 18%
Unknown 12 21%
Readers by discipline Count As %
Medicine and Dentistry 11 19%
Agricultural and Biological Sciences 9 16%
Biochemistry, Genetics and Molecular Biology 7 12%
Immunology and Microbiology 4 7%
Engineering 3 5%
Other 7 12%
Unknown 16 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 07 July 2016.
All research outputs
#3,168,658
of 24,885,505 outputs
Outputs from European Journal of Clinical Microbiology & Infectious Diseases
#227
of 2,951 outputs
Outputs of similar age
#49,984
of 320,356 outputs
Outputs of similar age from European Journal of Clinical Microbiology & Infectious Diseases
#6
of 52 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,951 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has done particularly well, scoring higher than 92% of its peers.
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 320,356 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.