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Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment

Overview of attention for article published in Microbiome, November 2017
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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 (91st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

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1 news outlet
blogs
1 blog
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27 X users

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53 Mendeley
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Title
Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment
Published in
Microbiome, November 2017
DOI 10.1186/s40168-017-0368-1
Pubmed ID
Authors

Sepideh Pakpour, Amit Bhanvadia, Roger Zhu, Abhimanyu Amarnani, Sean M. Gibbons, Thomas Gurry, Eric J. Alm, Laura A. Martello

Abstract

Colonization by the pathogen Clostridium difficile often occurs in the background of a disrupted microbial community. Identifying specific organisms conferring resistance to invasion by C. difficile is desirable because diagnostic and therapeutic strategies based on the human microbiota have the potential to provide more precision to the management and treatment of Clostridium difficile infection (CDI) and its recurrence. We conducted a longitudinal study of adult patients diagnosed with their first CDI. We investigated the dynamics of the gut microbiota during antibiotic treatment, and we used microbial or demographic features at the time of diagnosis, or after treatment, to predict CDI recurrence. To check the validity of the predictions, a meta-analysis using a previously published dataset was performed. We observed that patients' microbiota "before" antibiotic treatment was predictive of disease relapse, but surprisingly, post-antibiotic microbial community is indistinguishable between patients that recur or not. At the individual OTU level, we identified Veillonella dispar as a candidate organism for preventing CDI recurrence; however, we did not detect a corresponding signal in the conducted meta-analysis. Although in our patient population, a candidate organism was identified for negatively predicting CDI recurrence, results suggest the need for larger cohort studies that include patients with diverse demographic characteristics to generalize species that robustly confer colonization resistance against C. difficile and accurately predict disease relapse.

X Demographics

X Demographics

The data shown below were collected from the profiles of 27 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 21%
Student > Ph. D. Student 10 19%
Student > Master 6 11%
Student > Doctoral Student 5 9%
Student > Bachelor 5 9%
Other 5 9%
Unknown 11 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 21%
Biochemistry, Genetics and Molecular Biology 9 17%
Immunology and Microbiology 8 15%
Medicine and Dentistry 3 6%
Engineering 3 6%
Other 6 11%
Unknown 13 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 01 May 2023.
All research outputs
#1,375,884
of 25,382,440 outputs
Outputs from Microbiome
#462
of 1,757 outputs
Outputs of similar age
#27,456
of 336,988 outputs
Outputs of similar age from Microbiome
#16
of 36 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,757 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.3. This one has gotten more attention than average, scoring higher than 73% 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 336,988 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.