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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Detection of Clostridium difficile infection clusters, using the temporal scan statistic, in a community hospital in southern Ontario, Canada, 2006–2011
|
|---|---|
| Published in |
BMC Infectious Diseases, May 2014
|
| DOI | 10.1186/1471-2334-14-254 |
| Pubmed ID | |
| Authors |
Meredith C Faires, David L Pearl, William A Ciccotelli, Olaf Berke, Richard J Reid-Smith, J Scott Weese |
| Abstract |
In hospitals, Clostridium difficile infection (CDI) surveillance relies on unvalidated guidelines or threshold criteria to identify outbreaks. This can result in false-positive and -negative cluster alarms. The application of statistical methods to identify and understand CDI clusters may be a useful alternative or complement to standard surveillance techniques. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting CDI clusters and determine if there are significant differences in the rate of CDI cases by month, season, and year in a community hospital. |
X Demographics
The data shown below were collected from the profiles of 5 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 | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 40% |
| Scientists | 2 | 40% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 3% |
| Unknown | 32 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 24% |
| Student > Bachelor | 6 | 18% |
| Professor > Associate Professor | 4 | 12% |
| Other | 2 | 6% |
| Librarian | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 8 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 24% |
| Medicine and Dentistry | 6 | 18% |
| Environmental Science | 2 | 6% |
| Social Sciences | 2 | 6% |
| Nursing and Health Professions | 1 | 3% |
| Other | 6 | 18% |
| Unknown | 8 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 18 June 2014.
All research outputs
#13,408,565
of 22,755,127 outputs
Outputs from BMC Infectious Diseases
#3,335
of 7,665 outputs
Outputs of similar age
#111,607
of 227,160 outputs
Outputs of similar age from BMC Infectious Diseases
#77
of 156 outputs
Altmetric has tracked 22,755,127 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,665 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has gotten more attention than average, scoring higher than 54% 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 227,160 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 156 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.