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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Determination of clinical and demographic predictors of laboratory-confirmed influenza with subtype analysis
|
|---|---|
| Published in |
BMC Infectious Diseases, June 2012
|
| DOI | 10.1186/1471-2334-12-129 |
| Pubmed ID | |
| Authors |
Tabitha Woolpert, Stephanie Brodine, Hector Lemus, Jill Waalen, Patrick Blair, Dennis Faix |
| Abstract |
Rapid influenza diagnosis is important for early identification of outbreaks, effective management of high-risk contacts, appropriate antiviral use, decreased inappropriate antibiotic use and avoidance of unnecessary laboratory testing. Given the inconsistent performance of many rapid influenza tests, clinical diagnosis remains integral for optimizing influenza management. However, reliable clinical diagnostic methods are not well-established. This study assesses predictors of influenza, and its various subtypes, in a broad population at the point of care, across age groups, then evaluates the performance of clinical case definitions composed of identified predictors. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Uzbekistan | 1 | 2% |
| United States | 1 | 2% |
| Taiwan | 1 | 2% |
| Unknown | 60 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 13% |
| Researcher | 8 | 13% |
| Student > Bachelor | 8 | 13% |
| Professor > Associate Professor | 7 | 11% |
| Student > Master | 5 | 8% |
| Other | 14 | 22% |
| Unknown | 13 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 21 | 33% |
| Agricultural and Biological Sciences | 5 | 8% |
| Biochemistry, Genetics and Molecular Biology | 4 | 6% |
| Nursing and Health Professions | 3 | 5% |
| Immunology and Microbiology | 3 | 5% |
| Other | 12 | 19% |
| Unknown | 15 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 25 October 2012.
All research outputs
#18,308,895
of 22,668,244 outputs
Outputs from BMC Infectious Diseases
#5,555
of 7,640 outputs
Outputs of similar age
#128,592
of 166,837 outputs
Outputs of similar age from BMC Infectious Diseases
#61
of 86 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,640 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one is in the 15th percentile – i.e., 15% 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 166,837 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 86 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.