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An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings

Overview of attention for article published in Journal of Visualized Experiments, March 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

twitter
11 tweeters
video
1 video uploader

Citations

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18 Dimensions

Readers on

mendeley
47 Mendeley
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1 CiteULike
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Title
An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
Published in
Journal of Visualized Experiments, March 2014
DOI 10.3791/51242
Pubmed ID
Authors

Justen Manasa, Siva Danaviah, Sureshnee Pillay, Prevashinee Padayachee, Hloniphile Mthiyane, Charity Mkhize, Richard John Lessells, Christopher Seebregts, Tobias F. Rinke de Wit, Johannes Viljoen, David Katzenstein, Tulio De Oliveira

Abstract

HIV-1 drug resistance has the potential to seriously compromise the effectiveness and impact of antiretroviral therapy (ART). As ART programs in sub-Saharan Africa continue to expand, individuals on ART should be closely monitored for the emergence of drug resistance. Surveillance of transmitted drug resistance to track transmission of viral strains already resistant to ART is also critical. Unfortunately, drug resistance testing is still not readily accessible in resource limited settings, because genotyping is expensive and requires sophisticated laboratory and data management infrastructure. An open access genotypic drug resistance monitoring method to manage individuals and assess transmitted drug resistance is described. The method uses free open source software for the interpretation of drug resistance patterns and the generation of individual patient reports. The genotyping protocol has an amplification rate of greater than 95% for plasma samples with a viral load >1,000 HIV-1 RNA copies/ml. The sensitivity decreases significantly for viral loads <1,000 HIV-1 RNA copies/ml. The method described here was validated against a method of HIV-1 drug resistance testing approved by the United States Food and Drug Administration (FDA), the Viroseq genotyping method. Limitations of the method described here include the fact that it is not automated and that it also failed to amplify the circulating recombinant form CRF02_AG from a validation panel of samples, although it amplified subtypes A and B from the same panel.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 2%
Tanzania, United Republic of 1 2%
Unknown 45 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 19%
Student > Ph. D. Student 9 19%
Researcher 7 15%
Student > Postgraduate 5 11%
Professor 4 9%
Other 13 28%
Readers by discipline Count As %
Medicine and Dentistry 13 28%
Biochemistry, Genetics and Molecular Biology 8 17%
Agricultural and Biological Sciences 8 17%
Unspecified 4 9%
Computer Science 3 6%
Other 11 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 08 December 2016.
All research outputs
#1,806,165
of 12,494,627 outputs
Outputs from Journal of Visualized Experiments
#580
of 5,414 outputs
Outputs of similar age
#29,932
of 191,089 outputs
Outputs of similar age from Journal of Visualized Experiments
#10
of 70 outputs
Altmetric has tracked 12,494,627 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,414 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 89% 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 191,089 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.