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X Demographics
Mendeley readers
Attention Score in Context
| Title |
High specificity of line-immunoassay based algorithms for recent HIV-1 infection independent of viral subtype and stage of disease
|
|---|---|
| Published in |
BMC Infectious Diseases, September 2011
|
| DOI | 10.1186/1471-2334-11-254 |
| Pubmed ID | |
| Authors |
Jörg Schüpbach, Leslie R Bisset, Stephan Regenass, Philippe Bürgisser, Meri Gorgievski, Ingrid Steffen, Corinne Andreutti, Gladys Martinetti, Cyril Shah, Sabine Yerly, Thomas Klimkait, Martin Gebhardt, Franziska Schöni-Affolter, Martin Rickenbach, the Swiss HIV Cohort Study |
| Abstract |
Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have shown that a patient's antibody reaction in a confirmatory line immunoassay (INNO-LIA HIV I/II Score, Innogenetics) provides information on the duration of infection. Here, we sought to further investigate the diagnostic specificity of various Inno-Lia algorithms and to identify factors affecting it. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 133% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Argentina | 1 | 3% |
| Unknown | 28 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 21% |
| Student > Ph. D. Student | 4 | 14% |
| Student > Master | 3 | 10% |
| Student > Bachelor | 3 | 10% |
| Professor > Associate Professor | 2 | 7% |
| Other | 7 | 24% |
| Unknown | 4 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 48% |
| Nursing and Health Professions | 2 | 7% |
| Agricultural and Biological Sciences | 2 | 7% |
| Engineering | 2 | 7% |
| Computer Science | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 6 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 10 November 2011.
All research outputs
#12,557,899
of 22,653,392 outputs
Outputs from BMC Infectious Diseases
#2,837
of 7,626 outputs
Outputs of similar age
#79,218
of 131,235 outputs
Outputs of similar age from BMC Infectious Diseases
#36
of 92 outputs
Altmetric has tracked 22,653,392 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,626 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 62% 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 131,235 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 92 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 60% of its contemporaries.