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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comparison of predicted susceptibility between genotype and virtual phenotype HIV drug resistance interpretation systems among treatment-naive HIV-infected patients in Asia: TASER-M cohort analysis
|
|---|---|
| Published in |
BMC Research Notes, October 2012
|
| DOI | 10.1186/1756-0500-5-582 |
| Pubmed ID | |
| Authors |
Awachana Jiamsakul, Rami Kantor, Patrick CK Li, Sunee Sirivichayakul, Thira Sirisanthana, Pacharee Kantipong, Christopher KC Lee, Adeeba Kamarulzaman, Winai Ratanasuwan, Rossana Ditangco, Thida Singtoroj, Somnuek Sungkanuparph |
| Abstract |
Accurate interpretation of HIV drug resistance (HIVDR) testing is challenging, yet important for patient care. We compared genotyping interpretation, based on the Stanford University HIV Drug Resistance Database (Stanford HIVdb), and virtual phenotyping, based on the Janssen Diagnostics BVBA's vircoTYPE™ HIV-1, and investigated their level of agreement in antiretroviral (ARV) naive patients in Asia, where non-B subtypes predominate. |
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 % |
|---|---|---|
| United States | 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Philippines | 1 | 3% |
| Unknown | 34 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 26% |
| Researcher | 5 | 14% |
| Other | 3 | 9% |
| Student > Postgraduate | 2 | 6% |
| Student > Ph. D. Student | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 11 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 29% |
| Biochemistry, Genetics and Molecular Biology | 3 | 9% |
| Agricultural and Biological Sciences | 3 | 9% |
| Immunology and Microbiology | 3 | 9% |
| Nursing and Health Professions | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 13 | 37% |
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 19 November 2012.
All research outputs
#14,610,406
of 22,684,168 outputs
Outputs from BMC Research Notes
#2,089
of 4,252 outputs
Outputs of similar age
#110,675
of 183,365 outputs
Outputs of similar age from BMC Research Notes
#51
of 80 outputs
Altmetric has tracked 22,684,168 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,252 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 50% 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 183,365 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 80 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.