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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Dynamic changes in short- and long-term bacterial composition following fecal microbiota transplantation for recurrent Clostridium difficile infection
|
|---|---|
| Published in |
Microbiome, March 2015
|
| DOI | 10.1186/s40168-015-0070-0 |
| Pubmed ID | |
| Authors |
Alexa Weingarden, Antonio González, Yoshiki Vázquez-Baeza, Sophie Weiss, Gregory Humphry, Donna Berg-Lyons, Dan Knights, Tatsuya Unno, Aleh Bobr, Johnthomas Kang, Alexander Khoruts, Rob Knight, Michael J Sadowsky |
| Abstract |
Fecal microbiota transplantation (FMT) is an effective treatment for recurrent Clostridium difficile infection (CDI) that often fails standard antibiotic therapy. Despite its widespread recent use, however, little is known about the stability of the fecal microbiota following FMT. Here we report on short- and long-term changes and provide kinetic visualization of fecal microbiota composition in patients with multiply recurrent CDI that were refractory to antibiotic therapy and treated using FMT. Fecal samples were collected from four patients before and up to 151 days after FMT, with daily collections until 28 days and weekly collections until 84 days post-FMT. The composition of fecal bacteria was characterized using high throughput 16S rRNA gene sequence analysis, compared to microbiota across body sites in the Human Microbiome Project (HMP) database, and visualized in a movie-like, kinetic format. FMT resulted in rapid normalization of bacterial fecal sample composition from a markedly dysbiotic state to one representative of normal fecal microbiota. While the microbiome appeared most similar to the donor implant material 1 day post-FMT, the composition diverged variably at later time points. The donor microbiota composition also varied over time. However, both post-FMT and donor samples remained within the larger cloud of fecal microbiota characterized as healthy by the HMP. Dynamic behavior is an intrinsic property of normal fecal microbiota and should be accounted for in comparing microbial communities among normal individuals and those with disease states. This also suggests that more frequent sample analyses are needed in order to properly assess success of FMT procedures. |
X Demographics
The data shown below were collected from the profiles of 59 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 24 | 41% |
| United Kingdom | 7 | 12% |
| Spain | 3 | 5% |
| France | 1 | 2% |
| Switzerland | 1 | 2% |
| Venezuela, Bolivarian Republic of | 1 | 2% |
| Myanmar | 1 | 2% |
| Australia | 1 | 2% |
| Austria | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 18 | 31% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 39 | 66% |
| Scientists | 15 | 25% |
| Practitioners (doctors, other healthcare professionals) | 5 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 340 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | 3% |
| Denmark | 2 | <1% |
| South Africa | 1 | <1% |
| France | 1 | <1% |
| Brazil | 1 | <1% |
| New Zealand | 1 | <1% |
| Unknown | 323 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 73 | 21% |
| Researcher | 69 | 20% |
| Student > Bachelor | 42 | 12% |
| Student > Master | 37 | 11% |
| Professor > Associate Professor | 15 | 4% |
| Other | 50 | 15% |
| Unknown | 54 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 89 | 26% |
| Medicine and Dentistry | 55 | 16% |
| Biochemistry, Genetics and Molecular Biology | 47 | 14% |
| Immunology and Microbiology | 29 | 9% |
| Engineering | 9 | 3% |
| Other | 45 | 13% |
| Unknown | 66 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 119. 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
#357,919
of 25,837,817 outputs
Outputs from Microbiome
#86
of 1,789 outputs
Outputs of similar age
#4,012
of 279,924 outputs
Outputs of similar age from Microbiome
#3
of 17 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,789 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.8. This one has done particularly well, scoring higher than 95% 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 279,924 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 98% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.