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Predicting recurrence of Clostridium difficile infection following encapsulated fecal microbiota transplantation

Overview of attention for article published in Microbiome, September 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)

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Title
Predicting recurrence of Clostridium difficile infection following encapsulated fecal microbiota transplantation
Published in
Microbiome, September 2018
DOI 10.1186/s40168-018-0549-6
Pubmed ID
Authors

Christopher Staley, Thomas Kaiser, Byron P. Vaughn, Carolyn T. Graiziger, Matthew J. Hamilton, Tauseef ur Rehman, Kevin Song, Alexander Khoruts, Michael J. Sadowsky

Abstract

Fecal microbiota transplantation (FMT) is an effective treatment for recurrent Clostridium difficile infection (rCDI). The use of freeze-dried, encapsulated donor material for FMT (cap-FMT) allows for an easy route of administration and remains clinically effective in the majority of rCDI patients. We hypothesized that specific shifts in the microbiota in response to cap-FMT could predict clinical outcome. We further evaluated the degree of donor microbiota engraftment to determine the extent that donor transfer contributed to recovery. In total, 89 patients were treated with 100 separate cap-FMTs, with a success rate (no rCDI 60 days post cap-FMT) of 80%. Among responders, the lower alpha diversity (ANOVA P < 0.05) observed among patient's pre-FMT samples was restored following cap-FMT. At 1 week post-FMT, community composition varied by clinical outcome (ANOSIM P < 0.001), with similar abundances among families (Lachnospiraceae, Ruminococcaceae, and Bacteroidaceae) in responder and donor samples. Families that showed differential abundances by outcome (response vs. recurrence) from samples collected 7 days following cap-FMT were used to construct a regression tree-based model to predict recurrence. Results showed a training accuracy of 100% to predict recurrence and the model was 97% accurate against a test data set of samples collected 8-20 days following cap-FMT. Evaluation of the extent of engraftment using the Bayesian algorithm SourceTracker revealed that approximately 50% of the post-FMT communities of responders were attributable to donor microbiota, while an additional 20-30% of the communities were similar to a composite healthy microbiota consisting of all donor samples. Regression tree-based analyses of microbial communities identified taxa significantly related to clinical response after 7 days, which can be targeted to improve microbial therapeutics. Furthermore, reinstatement of a healthy assemblage following cap-FMT was only partially attributable to explicit donor engraftment and continued to develop towards an overall healthy assemblage, independent of donor.

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The data shown below were collected from the profiles of 11 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 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 114 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 17%
Researcher 17 15%
Other 10 9%
Student > Bachelor 9 8%
Student > Master 8 7%
Other 17 15%
Unknown 34 30%
Readers by discipline Count As %
Medicine and Dentistry 25 22%
Biochemistry, Genetics and Molecular Biology 15 13%
Immunology and Microbiology 12 11%
Agricultural and Biological Sciences 10 9%
Nursing and Health Professions 3 3%
Other 15 13%
Unknown 34 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 08 February 2019.
All research outputs
#2,638,969
of 23,103,903 outputs
Outputs from Microbiome
#998
of 1,465 outputs
Outputs of similar age
#56,216
of 341,703 outputs
Outputs of similar age from Microbiome
#49
of 62 outputs
Altmetric has tracked 23,103,903 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,465 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 40.4. This one is in the 31st percentile – i.e., 31% 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 341,703 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 83% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.